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For more information and to register, please click on a course title. You can also register by telephone, fax or email.
Design of Experiments, General
Start date: Tuesday, September 01, 2009 (week 36)
Language: English(UK)
Price: 1200 EUR
Last day to register:
2009-08-11
Design of Experiments
Design of experiments is a rational and cost-effective approach to practical experimentation that allows the effect of variables to be assessed using a minimum of resources. Discover how to optimise your company's experiments, products and processes for increased throughput and enhanced profitability.
The course splits between lectures and hands-on analysis of real data using Umetrics' state-of-the-art software package MODDE.
After completing the course, participants will know how to:
| • |
Create efficient designs to match the experimental objectives. |
| • |
Analyse experimental data using sound statistical principles. |
| • |
Improve and optimise products and processes. |
| • |
Report results in a simple graphical format. |
| • |
Design, measure, analyse, interpret, and optimize. |
| • |
Construct predictive models and apply them in practice |
Who should participate?
The course is intended for researchers, scientists and engineers from all sectors of industry and academia. No prior knowledge of statistics is assumed.
Course schedule
Lunch daily between 12:00 - 13:00 |
| Day one |
| 09:00 |
Course start.
How and when should design of experiments be used? Problem formulation, selection of goals, factors, responses, type of model and design.
Full factorials, the basis of other designs. Analysis of full factorial designs I, evaluation of raw data, regression analysis and model interpretation.
Computer exercises followed by discussions. |
| 17:00 |
End of lectures and exercises. |
| Day two |
| 09:00 |
Analysis of full factorials II. Fault detection.
Screening designs, which factors dominate and what are their optimal ranges.
What to do after screening, optimization or modification of the design. Optimization designs, how do we find an optimum or a compromise?
Computer exercises followed by discussions. |
| 17:00 |
End of lectures and exercises. |
| Day three |
| 09:00 |
Robustness testing, verification that the method or process is robust within given specifications.
Exercises using participants' or Umetrics' examples.
Discussion of participants' own data including creation of new designs.
Course summary. |
| 15:00 |
End of course. |
Cost and conditions
Early bird registration: if you book at least 2 months prior to course date the price DISCOUNT is 17%. Also if you are more than three participants from one company booking the same course date you will receive an 8% DISCOUNT/person.
Course fee (+VAT) includes coffee, lunch and course documentation. An invoice will be sent and payment is required within 30 days of the invoice date. Course application is binding. Cancellations registered later than two weeks before the course start will not be refunded. Provided that Umetrics AB is notified, the registering company may substitute its participant(s).
If the customer cancels prior to 14 days of the course, 10% of the class fee will be applied to cover processing costs. The balance of class fees already paid to Umetrics may be credited towards a future course. The registering company may substitute its participant(s) provided that Umetrics is notified.
Umetrics holds courses based on a sufficient number of registrants. Therefore, Umetrics reserves the right to cancel the course 14 days prior to the course start date if the number of registrants is too low. Full refund will be made to these registrants. Alternately a 10% refund will be made to any registrant(s) enrolling in the next available course.
To register, please use the button "Begin registration" in this window frame, or send an email to Umetrics Academy.
Direct link to this course: http://www.umetrics.com/default.asp/pagename/Courselist/c/2/link/2372
|
Multivariate Data Analysis, General
Start date: Tuesday, September 15, 2009 (week 38)
Language: English(UK)
Price: 1200 EUR
Last day to register:
2009-08-25
Multivariate Analysis, General
Using the latest multivariate techniques, participants will learn how to interpret complex data quickly and confidently. Discover the secrets of overviewing data tables and also learn how to build robust predictive models that turn data into decisions.
The course is composed of lectures, demonstrations and computer exercises in software SIMCA-P+, based on real-life datasets.
After completing the course, participants will know how to:
| • |
Apply PCA (Principal Component Analysis) to detect outliers, trends, patterns and to classify groups within complex data |
| • |
Relate multiple responses to multiple inputs using PLS (Partial Least Squares) modelling |
| • |
Interpret models to gain scientific insights |
| • |
Learn how to construct predictive models and apply them in practice. Use multivariate calibration to predict and improve quality |
| • |
Classification of raw materials and ingredients |
| • |
Analysing a multivariate problem. |
Who should participate?
The course is intended for researchers, scientists and engineers from all sectors of industry and academia. No prior knowledge of statistics is assumed.
Course schedule
Lunch daily between 12:00 - 13:00 |
| Day one |
| 9:00 |
Introduction and presentation of the need for multivariate data analysis. Introduction to three kinds of problem: overview, classification, and quantification and prediction.
Principal Component Analysis (PCA) for over-views of data tables: variable scaling, geometrical interpretation, and model evaluation.
PCA examples: quality control of manufacturing, process control (SPC) and environmental monitoring.
Computer exercises followed by discussions. |
| 17:00 |
End of lectures and exercises. |
| Day two |
| 9:00 |
Partial Least Squares (PLS): prediction of responses Y from control parameters X.
Variable scaling, geometrical interpretation, algebraic solution and model evaluation.
Model diagnoses and validation of a PLS model.
PLS examples: process and quality control.
Computer exercises followed by discussions. |
| 17:00 |
End of lectures and exercises. |
| Day three |
| 9:00 |
Multivariate calibration: prediction of chemical contents from spectroscopic data. Multivariate classification; two types of classification techniques will be discussed; SIMCA classification and PLS-DA (discriminant analysis). Exercises and discussion of participants’ own data. Course summary. |
| 15:00 |
End of course. |
Cost and conditions
Early bird registration: if you book at least 2 months prior to course date the price DISCOUNT is 17%. Also if you are more than three participants from one company booking the same course date you will receive an 8% DISCOUNT/person.
Course fee (+VAT) includes coffee, lunch and course documentation. An invoice will be sent and payment is required within 30 days of the invoice date. Course application is binding. Cancellations registered later than two weeks before the course start will not be refunded. Provided that Umetrics AB is notified, the registering company may substitute its participant(s).
If the customer cancels prior to 14 days of the course, 10% of the class fee will be applied to cover processing costs. The balance of class fees already paid to Umetrics may be credited towards a future course. The registering company may substitute its participant(s) provided that Umetrics is notified.
Umetrics holds courses based on a sufficient number of registrants. Therefore, Umetrics reserves the right to cancel the course 14 days prior to the course start date if the number of registrants is too low. Full refund will be made to these registrants. Alternately a 10% refund will be made to any registrant(s) enrolling in the next available course.
To register, please use the button "Begin registration" in this window frame, or send an email to Umetrics Academy.
Direct link to this course: http://www.umetrics.com/default.asp/pagename/Courselist/c/2/link/2373
|
Design of Experiments, General
Start date: Tuesday, September 15, 2009 (week 38)
Language: English(UK)
Price: 1200 EUR
Last day to register:
2009-08-25
Design of Experiments
Design of experiments is a rational and cost-effective approach to practical experimentation that allows the effect of variables to be assessed using a minimum of resources. Discover how to optimise your company's experiments, products and processes for increased throughput and enhanced profitability.
The course splits between lectures and hands-on analysis of real data using Umetrics' state-of-the-art software package MODDE.
After completing the course, participants will know how to:
| • |
Create efficient designs to match the experimental objectives. |
| • |
Analyse experimental data using sound statistical principles. |
| • |
Improve and optimise products and processes. |
| • |
Report results in a simple graphical format. |
| • |
Design, measure, analyse, interpret, and optimize. |
| • |
Construct predictive models and apply them in practice |
Who should participate?
The course is intended for researchers, scientists and engineers from all sectors of industry and academia. No prior knowledge of statistics is assumed.
Course schedule
Lunch daily between 12:00 - 13:00 |
| Day one |
| 09:00 |
Course start.
How and when should design of experiments be used? Problem formulation, selection of goals, factors, responses, type of model and design.
Full factorials, the basis of other designs. Analysis of full factorial designs I, evaluation of raw data, regression analysis and model interpretation.
Computer exercises followed by discussions. |
| 17:00 |
End of lectures and exercises. |
| Day two |
| 09:00 |
Analysis of full factorials II. Fault detection.
Screening designs, which factors dominate and what are their optimal ranges.
What to do after screening, optimization or modification of the design. Optimization designs, how do we find an optimum or a compromise?
Computer exercises followed by discussions. |
| 17:00 |
End of lectures and exercises. |
| Day three |
| 09:00 |
Robustness testing, verification that the method or process is robust within given specifications.
Exercises using participants' or Umetrics' examples.
Discussion of participants' own data including creation of new designs.
Course summary. |
| 15:00 |
End of course. |
Cost and conditions
Early bird registration: if you book at least 2 months prior to course date the price DISCOUNT is 17%. Also if you are more than three participants from one company booking the same course date you will receive an 8% DISCOUNT/person.
Course fee (+VAT) includes coffee, lunch and course documentation. An invoice will be sent and payment is required within 30 days of the invoice date. Course application is binding. Cancellations registered later than two weeks before the course start will not be refunded. Provided that Umetrics AB is notified, the registering company may substitute its participant(s).
If the customer cancels prior to 14 days of the course, 10% of the class fee will be applied to cover processing costs. The balance of class fees already paid to Umetrics may be credited towards a future course. The registering company may substitute its participant(s) provided that Umetrics is notified.
Umetrics holds courses based on a sufficient number of registrants. Therefore, Umetrics reserves the right to cancel the course 14 days prior to the course start date if the number of registrants is too low. Full refund will be made to these registrants. Alternately a 10% refund will be made to any registrant(s) enrolling in the next available course.
To register, please use the button "Begin registration" in this window frame, or send an email to Umetrics Academy.
Direct link to this course: http://www.umetrics.com/default.asp/pagename/Courselist/c/2/link/2376
|
Multivariate Data Analysis, General
Start date: Tuesday, September 15, 2009 (week 38)
Language: English(UK)
Price: 1095 GBP
Last day to register:
2009-08-25
Multivariate Data Analysis and Modelling
Using the latest multivariate techniques, participants will learn how to interpret complex data quickly and confidently. Discover the secrets of overviewing data tables and also learn how to build robust predictive models that turn data into decisions.
The course is composed of lectures, demonstrations and computer exercises in software SIMCA-P+, based on real-life datasets.
After completing the course, participants will know how to:
| • |
Apply PCA (Principal Component Analysis) to detect outliers, trends, patterns and to classify groups within complex data |
| • |
Relate multiple responses to multiple inputs using PLS (Partial Least Squares) modelling |
| • |
Interpret models to gain scientific insights |
| • |
Learn how to model processes and use multivariate calibration to improve quality |
| • |
Characterise raw materials and ingredients |
| • |
Construct predictive models and apply them in practice |
Who should participate?
The course is intended for researchers, scientists and engineers from all sectors of industry and academia. No prior knowledge of statistics is assumed.
Course schedule
Lunch daily between 12:00 - 13:00 |
| Day one |
| 09:00 |
Introduction and presentation of three kinds of problem: overview, classification, and quantification and prediction.
Principal Component Analysis (PCA) for over-views of data tables: variable scaling, geometrical interpretation, and model evaluation.
PCA examples: quality control of manufacturing, process control (SPC) and environmental monitoring.
Computer exercises followed by discussions. |
| 17:30 |
End of lectures and exercises. |
| Day two |
| 09:00 |
Partial Least Squares (PLS): prediction of responses Y from control parameters X.
Variable scaling, geometrical interpretation, algebraic solution and model evaluation.
Multivariate characterisation: quantification of qualitative or discrete differences, such as change of batches, raw material, chemicals or suppliers.
PLS examples: raw material for detergent etc.
Computer exercises followed by discussions. |
| 17:30 |
End of lectures and exercises. |
| Day three |
| 09:00 |
Multivariate calibration: prediction of chemical contents from spectroscopic data. Multivariate process modelling. Exercises and discussion of participants’ own data. Course summary. |
| 16:00 |
End of course. |
Cost and conditions
The course fee (+VAT) includes lunch each day and the course dinner on Tuesday evening. The course will be held at our offices in Winkfield Ascot. B&B accommodation is available at the nearby Harte & Garter hotel in Windsor at preferential rates. Umetrics will organise accommodation at the hotel but delegates are responsible for settling their own bills. Cancellations received later than two weeks before the course starts will be charged at the full rate. Providing that Umetrics is notified, the registering company may substitute participants.
To register, please use the button "Begin registration" in this window frame, or send an email to Umetrics Academy.
Direct link to this course: http://www.umetrics.com/default.asp/pagename/Courselist/c/2/link/2343
|
Multivariate Data Analysis, General
Start date: Tuesday, September 15, 2009 (week 38)
Language: English(UK)
Price: 1200 EUR
Last day to register:
2009-08-25
Multivariate Analysis, General
Using the latest multivariate techniques, participants will learn how to interpret complex data quickly and confidently. Discover the secrets of overviewing data tables and also learn how to build robust predictive models that turn data into decisions.
The course is composed of lectures, demonstrations and computer exercises in software SIMCA-P+, based on real-life datasets.
After completing the course, participants will know how to:
| • |
Apply PCA (Principal Component Analysis) to detect outliers, trends, patterns and to classify groups within complex data |
| • |
Relate multiple responses to multiple inputs using PLS (Partial Least Squares) modelling |
| • |
Interpret models to gain scientific insights |
| • |
Learn how to construct predictive models and apply them in practice. Use multivariate calibration to predict and improve quality |
| • |
Classification of raw materials and ingredients |
| • |
Analysing a multivariate problem. |
Who should participate?
The course is intended for researchers, scientists and engineers from all sectors of industry and academia. No prior knowledge of statistics is assumed.
Course schedule
Lunch daily between 12:00 - 13:00 |
| Day one |
| 9:00 |
Introduction and presentation of the need for multivariate data analysis. Introduction to three kinds of problem: overview, classification, and quantification and prediction.
Principal Component Analysis (PCA) for over-views of data tables: variable scaling, geometrical interpretation, and model evaluation.
PCA examples: quality control of manufacturing, process control (SPC) and environmental monitoring.
Computer exercises followed by discussions. |
| 17:00 |
End of lectures and exercises. |
| Day two |
| 9:00 |
Partial Least Squares (PLS): prediction of responses Y from control parameters X.
Variable scaling, geometrical interpretation, algebraic solution and model evaluation.
Model diagnoses and validation of a PLS model.
PLS examples: process and quality control.
Computer exercises followed by discussions. |
| 17:00 |
End of lectures and exercises. |
| Day three |
| 9:00 |
Multivariate calibration: prediction of chemical contents from spectroscopic data. Multivariate classification; two types of classification techniques will be discussed; SIMCA classification and PLS-DA (discriminant analysis). Exercises and discussion of participants’ own data. Course summary. |
| 15:00 |
End of course. |
Cost and conditions
Early bird registration: if you book at least 2 months prior to course date the price DISCOUNT is 17%. Also if you are more than three participants from one company booking the same course date you will receive an 8% DISCOUNT/person.
Course fee (+VAT) includes coffee, lunch and course documentation. An invoice will be sent and payment is required within 30 days of the invoice date. Course application is binding. Cancellations registered later than two weeks before the course start will not be refunded. Provided that Umetrics AB is notified, the registering company may substitute its participant(s).
If the customer cancels prior to 14 days of the course, 10% of the class fee will be applied to cover processing costs. The balance of class fees already paid to Umetrics may be credited towards a future course. The registering company may substitute its participant(s) provided that Umetrics is notified.
Umetrics holds courses based on a sufficient number of registrants. Therefore, Umetrics reserves the right to cancel the course 14 days prior to the course start date if the number of registrants is too low. Full refund will be made to these registrants. Alternately a 10% refund will be made to any registrant(s) enrolling in the next available course.
To register, please use the button "Begin registration" in this window frame, or send an email to Umetrics Academy.
Direct link to this course: http://www.umetrics.com/default.asp/pagename/Courselist/c/2/link/2382
|
Multivariate Data Analysis, General
Start date: Wednesday, September 16, 2009 (week 38)
Language: English
Price: $1,795 US
Last day to register:
2009-08-26
Multivariate Analysis, Basic
The methods that will be introduced and discussed have been developed to account for the fact that almost every problem in R&D is multivariate in nature. That is, there exists a multitude of variables that jointly and simultaneously influence each other.
The course will include both tutorial lectures and practical exercises using the well-established material from Umetrics, using SIMCA-P+ software. The attendees will also be given the opportunity to ventilate their own problems.
After completing the course, each participant will be able to:
| • |
Understand the theory behind modeling of multivariate data |
| • |
Use SIMCA-P+ to model and interpret multivariate data |
Who should participate?
The course is intended for researchers, scientists and engineers from all sectors of industry and academia. No prior knowledge of statistics is assumed.
Course schedule
Lunch daily between 12:00 - 13:00 |
| Day one |
| 08:30 |
Introduction & Need for Multivariate Data Analysis
Principal components analysis
- The Method
- Example
- Diagnostics
- Usage
Introduction to SIMCA-P +
Analyzing Data in SIMCA-P+
- Importing Data and Quick Info
- Preparing the Model: the Workset
Computer exercises followed by discussions |
| 17:00 |
End of lectures and exercises |
| Day two |
| 08:30 |
PCA Model
Prepare the workset
- Fit and Review the Model
- Interpret the scores and loadings plots
- Diagnostics and contribution plots
- Update model
- Predictions
- PCA Examples
Labs
Introduction to PCR and PLS
PLS
- The Method
- Small Example
Computer exercises followed by discussions |
| 17:00 |
End of lectures and exercises. |
| Day three |
| 8:30 |
Plots and Diagnostics
- Example (Enviro)
- Analyzing PLS data
- Fit and Review Fit
- Interpret the scores and loadings
- Diagnostics and contribution plots
- Understand the relationship
- Update the model
- Predictions
- Examples
Conclusion
Labs |
| 17:00 |
End of course |
Cost and conditions
Course fee includes coffee, lunch, and course documentation. Course registration is binding. Cancellations received within two weeks of the course start date will forfeit the entire course fee. If the customer cancels prior to 14 days of the course, 20% of the class fee will be applied to cover processing costs. The balance of class fees already paid to Umetrics may be credited towards a future course. The registering company may substitute its participant(s) provided that Umetrics is notified.
Umetrics holds courses based on a sufficient number of registrants. Therefore, Umetrics reserves the right to cancel the course 14 days prior to the course start date if the number of registrants is too low. Full refund will be made to these registrants. Alternately a 10% refund will be made to any registrant(s) enrolling in the next available course.
Early bird registration: if you book at least 2 months prior to course date the price DISCOUNT is 15%. Also if you are more than three participants from one company booking the same course date you will receive a 10% DISCOUNT/person.
To register, please use the button "Begin registration" in this window frame, or send an email to Umetrics Academy.
Direct link to this course: http://www.umetrics.com/default.asp/pagename/Courselist/c/2/link/10082
|
Design of Experiments, General
Start date: Tuesday, September 22, 2009 (week 39)
Language: Swedish
Price: 12000 SEK
Last day to register:
2009-09-01
Design of Experiments
Design of experiments is a rational and cost-effective approach to practical experimentation that allows the effect of variables to be assessed using a minimum of resources. Discover how to optimise your company's experiments, products and processes for increased throughput and enhanced profitability.
The course splits between lectures and hands-on analysis of real data using Umetrics' state-of-the-art software package MODDE.
After completing the course, participants will know how to:
| • |
Create efficient designs to match the experimental objectives. |
| • |
Analyse experimental data using sound statistical principles. |
| • |
Improve and optimise products and processes. |
| • |
Report results in a simple graphical format. |
| • |
Design, measure, analyse, interpret, and optimize. |
| • |
Construct predictive models and apply them in practice |
Who should participate?
The course is intended for researchers, scientists and engineers from all sectors of industry and academia. No prior knowledge of statistics is assumed.
Course schedule
Lunch daily between 12:00 - 13:00 |
| Day one |
| 09:00 |
Course start.
How and when should design of experiments be used? Problem formulation, selection of goals, factors, responses, type of model and design.
Full factorials, the basis of other designs. Analysis of full factorial designs I, evaluation of raw data, regression analysis and model interpretation.
Computer exercises followed by discussions. |
| 17:00 |
End of lectures and exercises. |
| Day two |
| 09:00 |
Analysis of full factorials II. Fault detection.
Screening designs, which factors dominate and what are their optimal ranges.
What to do after screening, optimization or modification of the design. Optimization designs, how do we find an optimum or a compromise?
Computer exercises followed by discussions. |
| 17:00 |
End of lectures and exercises. |
| Day three |
| 09:00 |
Robustness testing, verification that the method or process is robust within given specifications.
Exercises using participants' or Umetrics' examples.
Discussion of participants' own data including creation of new designs.
Course summary. |
| 15:00 |
End of course. |
Cost and conditions
Early bird registration: if you book at least 2 months prior to course date the price DISCOUNT is 17%. Also if you are more than three participants from one company booking the same course date you will receive an 8% DISCOUNT/person.
Course fee (+VAT) includes coffee, lunch and course documentation. An invoice will be sent and payment is required within 30 days of the invoice date. Course application is binding. Cancellations registered later than two weeks before the course start will not be refunded. Provided that Umetrics AB is notified, the registering company may substitute its participant(s).
If the customer cancels prior to 14 days of the course, 10% of the class fee will be applied to cover processing costs. The balance of class fees already paid to Umetrics may be credited towards a future course. The registering company may substitute its participant(s) provided that Umetrics is notified.
Umetrics holds courses based on a sufficient number of registrants. Therefore, Umetrics reserves the right to cancel the course 14 days prior to the course start date if the number of registrants is too low. Full refund will be made to these registrants. Alternately a 10% refund will be made to any registrant(s) enrolling in the next available course.
To register, please use the button "Begin registration" in this window frame, or send an email to Umetrics Academy.
Direct link to this course: http://www.umetrics.com/default.asp/pagename/Courselist/c/2/link/2367
|
Advanced Design of Experiments for Mixtures
Start date: Wednesday, September 23, 2009 (week 39)
Language: English(UK)
Price: 1000 EUR
Last day to register:
2009-09-02
Advanced Design of Experiments, Mixture Design
This two-day advanced course is dedicated to designs and methodologies that handle the special experimental situations where blends are under investigation. This special situation involves more difficulties compare with classical problems due to the factors constrains and relationships. However, it is often encountered in many different fields as pharmaceutical, food, painting or alloy. The course illustrates the designs and the methodologies that support the experimenter who deals with mixture problems.
The course will include both tutorial lectures and practical exercises in software MODDE using well-established material from Umetrics AB. Additionally, course participants will be given the opportunity to work with their own data and to discuss analytical matters with the tutors.
After completing the course, participants will:
| • |
Be able to attack problems with new and refreshed skills in analysis
|
| • |
Have a deeper theoretical understanding of experimental design
|
| • |
Have discussed and exercised new areas of applications |
Who should participate?
The course is intended for those who have attended Umetrics Academy's design of experiments basic course, or have equivalent training or experience.
Course schedule
Lunch daily between 12:30 - 13:30 |
| Day one |
| 09:00 |
Course start.
A review of the important topics in the basic course. The experimental domain. The mathematical limitations and possibilities vs design selection. Diagnostics of data. Evaluation of results.
Demonstration of new important functionalities in MODDE. Exercises.
Discussion of company specific problems. |
| 17:00 |
End of lectures and exercises.
|
| Day two |
| 09:00 |
A working strategy for mixture design.
Overview of mixture region.
Overview of mixture deisgn protocols.
Introduction to D-optimal design
Introduction to PLS.
Computer exercises and discussions. Computer exercises and discussions. |
| 17:00 |
End of course. |
Cost and conditions Course fee (+VAT) includes coffee, lunch and course documentation. An invoice will be sent and payment is required within 30 days of the invoice date. Course application is binding. Cancellations registered later than 2 weeks before the course start will not be refunded. Provided that Umetrics AB is notified, the registering company may substitute its participant(s) freely, if desired. The course will be held at S-IN Soluzioni Informatiche, via Ferrari 14, 36100 Vicenza. To register, please use the button "Begin registration" in this window frame, or send an email to Soluzioni Informatiche (S.IN), training@s-in.it.
Direct link to this course: http://www.umetrics.com/default.asp/pagename/Courselist/c/2/link/2353
|
Multivariate Data Analysis, General
Start date: Tuesday, September 29, 2009 (week 40)
Language: Swedish
Price: 12000 SEK
Last day to register:
2009-09-08
Multivariate Analysis, General
Using the latest multivariate techniques, participants will learn how to interpret complex data quickly and confidently. Discover the secrets of overviewing data tables and also learn how to build robust predictive models that turn data into decisions.
The course is composed of lectures, demonstrations and computer exercises in software SIMCA-P+, based on real-life datasets.
After completing the course, participants will know how to:
| • |
Apply PCA (Principal Component Analysis) to detect outliers, trends, patterns and to classify groups within complex data |
| • |
Relate multiple responses to multiple inputs using PLS (Partial Least Squares) modelling |
| • |
Interpret models to gain scientific insights |
| • |
Learn how to construct predictive models and apply them in practice. Use multivariate calibration to predict and improve quality |
| • |
Classification of raw materials and ingredients |
| • |
Analysing a multivariate problem. |
Who should participate?
The course is intended for researchers, scientists and engineers from all sectors of industry and academia. No prior knowledge of statistics is assumed.
Course schedule
Lunch daily between 12:00 - 13:00 |
| Day one |
| 9:00 |
Introduction and presentation of the need for multivariate data analysis. Introduction to three kinds of problem: overview, classification, and quantification and prediction.
Principal Component Analysis (PCA) for over-views of data tables: variable scaling, geometrical interpretation, and model evaluation.
PCA examples: quality control of manufacturing, process control (SPC) and environmental monitoring.
Computer exercises followed by discussions. |
| 17:00 |
End of lectures and exercises. |
| Day two |
| 9:00 |
Partial Least Squares (PLS): prediction of responses Y from control parameters X.
Variable scaling, geometrical interpretation, algebraic solution and model evaluation.
Model diagnoses and validation of a PLS model.
PLS examples: process and quality control.
Computer exercises followed by discussions. |
| 17:00 |
End of lectures and exercises. |
| Day three |
| 9:00 |
Multivariate calibration: prediction of chemical contents from spectroscopic data. Multivariate classification; two types of classification techniques will be discussed; SIMCA classification and PLS-DA (discriminant analysis). Exercises and discussion of participants’ own data. Course summary. |
| 15:00 |
End of course. |
Cost and conditions
Early bird registration: if you book at least 2 months prior to course date the price DISCOUNT is 17%. Also if you are more than three participants from one company booking the same course date you will receive an 8% DISCOUNT/person.
Course fee (+VAT) includes coffee, lunch and course documentation. An invoice will be sent and payment is required within 30 days of the invoice date. Course application is binding. Cancellations registered later than two weeks before the course start will not be refunded. Provided that Umetrics AB is notified, the registering company may substitute its participant(s).
If the customer cancels prior to 14 days of the course, 10% of the class fee will be applied to cover processing costs. The balance of class fees already paid to Umetrics may be credited towards a future course. The registering company may substitute its participant(s) provided that Umetrics is notified.
Umetrics holds courses based on a sufficient number of registrants. Therefore, Umetrics reserves the right to cancel the course 14 days prior to the course start date if the number of registrants is too low. Full refund will be made to these registrants. Alternately a 10% refund will be made to any registrant(s) enrolling in the next available course.
To register, please use the button "Begin registration" in this window frame, or send an email to Umetrics Academy.
Direct link to this course: http://www.umetrics.com/default.asp/pagename/Courselist/c/2/link/2370
|
Design of Experiments, General
Start date: Tuesday, September 29, 2009 (week 40)
Language: English(UK)
Price: 1200 EUR
Last day to register:
2009-09-08
Design of Experiments
Design of experiments is a rational and cost-effective approach to practical experimentation that allows the effect of variables to be assessed using a minimum of resources. Discover how to optimise your company's experiments, products and processes for increased throughput and enhanced profitability.
The course splits between lectures and hands-on analysis of real data using Umetrics' state-of-the-art software package MODDE.
After completing the course, participants will know how to:
| • |
Create efficient designs to match the experimental objectives. |
| • |
Analyse experimental data using sound statistical principles. |
| • |
Improve and optimise products and processes. |
| • |
Report results in a simple graphical format. |
| • |
Design, measure, analyse, interpret, and optimize. |
| • |
Construct predictive models and apply them in practice |
Who should participate?
The course is intended for researchers, scientists and engineers from all sectors of industry and academia. No prior knowledge of statistics is assumed.
Course schedule
Lunch daily between 12:00 - 13:00 |
| Day one |
| 09:00 |
Course start.
How and when should design of experiments be used? Problem formulation, selection of goals, factors, responses, type of model and design.
Full factorials, the basis of other designs. Analysis of full factorial designs I, evaluation of raw data, regression analysis and model interpretation.
Computer exercises followed by discussions. |
| 17:00 |
End of lectures and exercises. |
| Day two |
| 09:00 |
Analysis of full factorials II. Fault detection.
Screening designs, which factors dominate and what are their optimal ranges.
What to do after screening, optimization or modification of the design. Optimization designs, how do we find an optimum or a compromise?
Computer exercises followed by discussions. |
| 17:00 |
End of lectures and exercises. |
| Day three |
| 09:00 |
Robustness testing, verification that the method or process is robust within given specifications.
Exercises using participants' or Umetrics' examples.
Discussion of participants' own data including creation of new designs.
Course summary. |
| 15:00 |
End of course. |
Cost and conditions
Early bird registration: if you book at least 2 months prior to course date the price DISCOUNT is 17%. Also if you are more than three participants from one company booking the same course date you will receive an 8% DISCOUNT/person.
Course fee (+ VAT) includes coffee, lunch and course documentation. An invoice will be sent and payment is required within 30 days of the invoice date. Course application is binding. OBSERVE THAT OWN LAPTOPS IS REQUIERED FOR EXCERCISES. PROGRAM INSTALLATION INSTRUCTIONS WILL BE SENT OUT WITH THE FINAL COURSE INFORMATION. Cancellations registered later than two weeks before the course start will not be refunded. Provided that Umetrics AB is notified, the registering company may substitute its participant(s). If the customer cancels prior to 14 days of the course, 10% of the class fee will be applied to cover processing costs. The balance of class fees already paid to Umetrics may be credited towards a future course. The registering company may substitute its participant(s) provided that Umetrics is notified.
Umetrics holds courses based on a sufficient number of registrants. Therefore, Umetrics reserves the right to cancel the course 14 days prior to the course start date if the number of registrants is too low. Full refund will be made to these registrants. Alternately a 10% refund will be made to any registrant(s) enrolling in the next available course.
To register, please use the button "Begin registration" in this window frame, or send an email to Umetrics Academy.
Direct link to this course: http://www.umetrics.com/default.asp/pagename/Courselist/c/2/link/2380
|
Multivariate Data Analysis for Batch
Start date: Tuesday, October 06, 2009 (week 41)
Language: English
Price: $1,795 US
Last day to register:
2009-09-15
Multivariate Analysis for Batch Applications
Multivariate data analysis with projection methods is ideal for batch modeling, with the characteristic 3-way tables brought about by the batch maturity vector. Discover how to use the latest multivariate techniques to model batch processes and to interpret the models. You will see how models are applied to monitor batch evolution and predict batch quality before completion.
The course consists of lectures, examples and hands-on computer exercises in software SIMCA-P+, using real-life datasets.
After completing the course, participants will know how to:
| • |
Understand the specific nature of batch data |
| • |
Be able to model batch data and interpret models in SIMCA-P+ |
| • |
Be able to use models for prediction of batch quality |
| • |
Understand the concept of hierarchical modeling of batch data |
Who should participate?
The course is intended for researchers, scientists and engineers involved in research and development, production and manufacturing. Prior knowledge of Multivariate Data Analysis is preferable, but a review of the basic methodology will be given on the first day.
Course schedule
Lunch daily between 12:00 - 13:00 |
| Day one |
| 09:00 |
Course start.
Review of MVA modeling, PCA, PLS MSPC objectives.
Objective of Batch modeling.
BMSPC, soft sensors.
Nature of batch data.
3-way decomposition vs unfolding with 2-way table analysis. Computer exercises followed by discussions. |
| 17:00 |
End of lectures and exercises. |
| Day two |
| 09:00 |
Hierarchical approach to modeling batch data.
What does quality of batch depend on?
Modeling batch data. Observation level. Batch level. Batch-specific issues. Representative training set.
Different phases. Scaling and centering of phases.
Run-to-run control. Time vs Maturity.
Smoothing maturity. Alignments of batches.
Demo using SIMCA-Batch On-Line.
Computer Exercises. |
| 17:00 |
End of lectures and exercises. |
| Day three |
| 09:00 |
Modeling batches in SIMCA-P+.
Import, specifying batch/phase identifiers.
Merging and deleting phases.
Local centering and filtering.
Conditional delete. Diagnostics and interpreting plots.
Control charts and transformations.
Prediction set and prediction control charts.
Creating batch level with different options.
Partial models and predicting the completed batch.
Model validation.
Conclusions. Course summary. |
| 15:00 |
End of course. |
Cost and conditions
Course fee includes coffee, lunch, and course documentation. Course registration is binding. Cancellations received within two weeks of the course start date will forfeit the entire course fee. If the customer cancels prior to 14 days of the course, 20% of the class fee will be applied to cover processing costs. The balance of class fees already paid to Umetrics may be credited towards a future course. The registering company may substitute its participant(s) provided that Umetrics is notified.
Umetrics holds courses based on a sufficient number of registrants. Therefore, Umetrics reserves the right to cancel the course 14 days prior to the course start date if the number of registrants is too low. Full refund will be made to these registrants. Alternately a 10% refund will be made to any registrant(s) enrolling in the next available course.
Early bird registration: if you book at least 2 months prior to course date the price DISCOUNT is 15%. Also if you are more than three participants from one company booking the same course date you will receive a 10% DISCOUNT/person.
To register, please use the button "Begin registration" in this window frame, or send an email to Umetrics Academy.
Direct link to this course: http://www.umetrics.com/default.asp/pagename/Courselist/c/2/link/10085
|
Design of Experiments, General
Start date: Tuesday, October 06, 2009 (week 41)
Language: English(UK)
Price: 1095 GBP
Last day to register:
2009-09-15
Design of Experiments
Design of experiments is a rational and cost-effective approach to practical experimentation that allows the effect of variables to be assessed using a minimum of resources. Discover how to optimize your company's experiments, products and processes for increased throughput and enhanced profitability.
The course splits between lectures and hands-on analysis of real data using Umetrics' state-of-the-art software package MODDE.
After completing the course, participants will know how to:
| • |
Create efficient designs to match the experimental objectives. |
| • |
Analyse experimental data using sound statistical principles. |
| • |
Improve and optimize products and processes. |
| • |
Report results in a simple graphical format. |
| • |
Design, measure, analyse, interpret, and optimise. |
| • |
Construct predictive models and apply them in practice |
Who should participate?
The course is intended for researchers, scientists and engineers from all sectors of industry and academia. No prior knowledge of statistics is assumed.
Course schedule
Lunch daily between 12:00 - 13:00 |
| Day one |
| 09:00 |
Course start.
How and when should design of experiments be used? Problem formulation, selection of goals, factors, responses, type of model and design.
Full factorials, the basis of other designs. Analysis of full factorial designs I, evaluation of raw data, regression analysis and model interpretation.
Computer exercises followed by discussions. |
| 17:30 |
End of lectures and exercises. |
| Day two |
| 09:00 |
Analysis of full factorials II. Fault detection.
Screening designs, which factors dominate and what are their optimal ranges.
What to do after screening, optimization or modification of the design. Optimization designs, how do we find an optimum or a compromise?
Computer exercises followed by discussions. |
| 17:30 |
End of lectures and exercises. |
| Day three |
| 09:00 |
Robustness testing, verification that the method or process is robust within given specifications.
Exercises using participants' or Umetrics' examples.
Discussion of participants' own data including creation of new designs.
Course summary. |
| 16:00 |
End of course. |
Cost and conditions
The course fee (+VAT) includes lunch each day and the course dinner on Tuesday evening. The course will be held at our offices in Winkfield Ascot. B&B accommodation is available at the nearby Harte & Garter hotel in Windsor at preferential rates. Umetrics will organise accommodation at the hotel but delegates are responsible for settling their own bills. Cancellations received later than two weeks before the course starts will be charged at the full rate. Providing that Umetrics is notified, the registering company may substitute participants.
To register, please use the button "Begin registration" in this window frame, or send an email to Umetrics Academy.
Direct link to this course: http://www.umetrics.com/default.asp/pagename/Courselist/c/2/link/2344
|
Multivariate Data Analysis for Omics
Start date: Tuesday, October 13, 2009 (week 42)
Language: English(UK)
Price: 995 EUR
Last day to register:
2009-09-22
Multivariate Analysis for "Omics"
Multivariate data analysis is essential in the process of extracting information from the complex data sets involved in “omics” studies. Discover how to build valid and predictive models based on data from genomic, proteomic and metabolomic studies, with the latest multivariate techniques. The focus on this course is how to use state-of art multivariate tools to extract putative biomarkers in a statistically significant way.
The course is composed of lectures, demonstrations and computer exercises using SIMCA-P+12 software on real-life datasets. Examples from plant biology and medicine will be used to highlight the usefulness of the applied strategies.
After completing the course, participants will know how to:
| • |
Insights on chemometrics strategies for ”omics” studies |
| • |
Apply PCA to detect outliers, trends and patterns in "omics" data |
| • |
An awareness of sources of variability and the effect on modeling and interpretation |
| • |
Understanding of how to use OPLS in classification |
| • |
Understanding on how to compare multiple treatments |
| • |
Understanding on how to apply multivariate tools for putative biomarker identification |
| • |
Validate models for robustness and predictability |
Who should participate?
The course is intended for researchers involved in “omics” studies with little or no knowledge in multivariate data analysis. The examples presented in the lectures are focused on MS- and NMR-based metabolomics, for consistency. The exercises include genomics, proteomics and metabolomics data sets so participants from different field can choose from their own interest. Practice on own data is also welcome and appreciated.
Course schedule
Lunch daily between 12:00 - 13:00 |
| Day one |
| 09:00 |
Introduction to multivariate data analysis
Principal component analysis, PCA
Apply PCA to detect outliers, trends and patterns in metabolomic data
Interpret models to gain scientific insights
Exercises in SIMCA-P+ |
| 17:00 |
End of lectures and exercises and course dinner |
| Day two |
| 09:00 |
From PCA to Orthogonal projections to latent structures, OPLS
Putative biomarkers identification using OPLS
How to compare multiple treatments
Validate models for robustness and predictability
Exercises in SIMCA-P+ and discussions
Course summary |
| 17:00 |
End of course |
Cost and conditions
Early bird registration: if you book at least 2 months prior to course date the price DISCOUNT is 17%. Also if you are more than three participants from one company booking the same course date you will receive an 8% DISCOUNT/person.
Course fee (+VAT) includes coffee, lunch and course documentation. An invoice will be sent and payment is required within 30 days of the invoice date. Course application is binding. Cancellations registered later than two weeks before the course start will not be refunded. Provided that Umetrics AB is notified, the registering company may substitute its participant(s).
If the customer cancels prior to 14 days of the course, 10% of the class fee will be applied to cover processing costs. The balance of class fees already paid to Umetrics may be credited towards a future course. The registering company may substitute its participant(s) provided that Umetrics is notified.
Umetrics holds courses based on a sufficient number of registrants. Therefore, Umetrics reserves the right to cancel the course 14 days prior to the course start date if the number of registrants is too low. Full refund will be made to these registrants. Alternately a 10% refund will be made to any registrant(s) enrolling in the next available course.
To register, please use the button "Begin registration" in this window frame, or send an email to Umetrics Academy.
Direct link to this course: http://www.umetrics.com/default.asp/pagename/Courselist/c/2/link/2377
|
Design of Experiments, General
Start date: Tuesday, October 13, 2009 (week 42)
Language: English(UK)
Price: 1200 EUR
Last day to register:
2009-09-22
Design of Experiments
Design of experiments is a rational and cost-effective approach to practical experimentation that allows the effect of variables to be assessed using a minimum of resources. Discover how to optimise your company's experiments, products and processes for increased throughput and enhanced profitability.
The course splits between lectures and hands-on analysis of real data using Umetrics' state-of-the-art software package MODDE.
After completing the course, participants will know how to:
| • |
Create efficient designs to match the experimental objectives. |
| • |
Analyse experimental data using sound statistical principles. |
| • |
Improve and optimise products and processes. |
| • |
Report results in a simple graphical format. |
| • |
Design, measure, analyse, interpret, and optimize. |
| • |
Construct predictive models and apply them in practice |
Who should participate?
The course is intended for researchers, scientists and engineers from all sectors of industry and academia. No prior knowledge of statistics is assumed.
Course schedule
Lunch daily between 12:00 - 13:00 |
| Day one |
| 09:00 |
Course start.
How and when should design of experiments be used? Problem formulation, selection of goals, factors, responses, type of model and design.
Full factorials, the basis of other designs. Analysis of full factorial designs I, evaluation of raw data, regression analysis and model interpretation.
Computer exercises followed by discussions. |
| 17:00 |
End of lectures and exercises. |
| Day two |
| 09:00 |
Analysis of full factorials II. Fault detection.
Screening designs, which factors dominate and what are their optimal ranges.
What to do after screening, optimization or modification of the design. Optimization designs, how do we find an optimum or a compromise?
Computer exercises followed by discussions. |
| 17:00 |
End of lectures and exercises. |
| Day three |
| 09:00 |
Robustness testing, verification that the method or process is robust within given specifications.
Exercises using participants' or Umetrics' examples.
Discussion of participants' own data including creation of new designs.
Course summary. |
| 15:00 |
End of course. |
Cost and conditions
Early bird registration: if you book at least 2 months prior to course date the price DISCOUNT is 17%. Also if you are more than three participants from one company booking the same course date you will receive an 8% DISCOUNT/person.
Course fee (+VAT) includes coffee, lunch and course documentation. An invoice will be sent and payment is required within 30 days of the invoice date. Course application is binding. Cancellations registered later than two weeks before the course start will not be refunded. Provided that Umetrics AB is notified, the registering company may substitute its participant(s).
If the customer cancels prior to 14 days of the course, 10% of the class fee will be applied to cover processing costs. The balance of class fees already paid to Umetrics may be credited towards a future course. The registering company may substitute its participant(s) provided that Umetrics is notified.
Umetrics holds courses based on a sufficient number of registrants. Therefore, Umetrics reserves the right to cancel the course 14 days prior to the course start date if the number of registrants is too low. Full refund will be made to these registrants. Alternately a 10% refund will be made to any registrant(s) enrolling in the next available course.
To register, please use the button "Begin registration" in this window frame, or send an email to Umetrics Academy.
Direct link to this course: http://www.umetrics.com/default.asp/pagename/Courselist/c/2/link/2385
|
Analisi Multivariata di Dati
Start date: Wednesday, October 14, 2009 (week 42)
Language: Italian
Price: 1200 EUR
Last day to register:
2009-09-23
Analisi Multivariata di Dati
Le moderne matrici di dati sono spesso costituite da numerose variabili che “nascondono” nelle loro combinazioni le informazioni più interessanti. Mediante l’applicazione delle metodologie di analisi multivariata, è possibile interpretare velocemente e correttamente complesse matrici di dati, scoprire relazioni nascoste tra le variabili, costruire modelli interpretativi con valore predittivo e, quindi, convertire dati in decisioni. Il corso comprende lezioni teoriche ed esercitazioni guidate al computer basate su set di dati reali che hanno lo scopo di presentare i principi base dell’Analisi Multivariata e di consentire ai partecipanti di acquistare familiarità con l’interpretazione dei dati e con l’uso del software.
Obiettivi del corso
Alla fine del corso i partecipanti saranno in grado di:
| • |
Applicare PCA (Analisi delle Componenti Principali) al fine di individuare outliers, suddividere i dati in classi, identificare l’eventuale struttura presente nella matrice dati; |
| • |
Mettere in relazione le variabili con risposte multiple mediante PLS (Partial Least Squares); |
| • |
Interpretare i modelli ed estrarre conoscenza dai dati; |
| • |
Modellare un processo e usare la calibrazione multivariata al fine di migliorarne la qualità; |
| • |
Caratterizzare materie prime; |
| • |
Generare e applicare modelli predittivi. |
A chi è rivolto
Il corso è rivolto a ricercatori, ingegneri e tecnici del settore ricerca e sviluppo oppure del settore della produzione. Non sono richieste particolari conoscenze in campo statistico.
Programma
Il pranzo è previsto tra le ore 12:30 e le 13:30 |
| Primo giorno |
| 09:00 |
Inizio delle lezioni.
Introduzione e presentazione di tre tipologie di problemi: “overview” dei dati, classificazione, e predizione.
Analisi delle Componenti Principali (PCA) e prima analisi della matrice di dati: scalatura delle variabili, interpretazione geometrica, e valutazione del modello.
PCA, esempi applicativi: controllo della qualità di un manufatto, controllo di un processo (SPC), monitoraggio ambientale. Esercizi e discussione. |
| 17:00 |
Conclusione. |
| Secondo giorno |
| 09:00 |
“Partial Least Squares” (PLS): predizione delle risposte Y sulla base dei parametri X.
Scalatura delle variabili, interpretazione geometrica, soluzione algebrica e valutazione del modello.
Caratterizzazione multivariata: quantificazione di effetti qualitativi o di effetti discreti.
Esempi di applicazione di PLS.
Esercizi e discussione. |
| 17:00 |
Conclusione. |
| Terzo giorno |
| 09:00 |
Calibrazione multivariata: predizione della composizione chimica sulla base di dati spettroscopici.
Esempio: determinazione della qualità dello zucchero da misure di fluorescenza.
Analisi di dati di processo. Esempi di controllo multivariato di processo (SPC) e di ottimizzazione di processo.
Esercizi basati su dati dei partecipanti. |
| 15:00 |
Conclusione del corso. |
Iscrizione
Iscrizione Il costo dell’iscrizione (+IVA) include coffee break, tre pranzi e materiale didattico. Si richiede il pagamento tramite fattura a 30 giorni che verrà emessa successivamente alla chiusura delle iscrizioni. L’iscrizione è vincolante: non è previsto il rimborso dell’iscrizione qualora la rinuncia sia notificata due settimane prima dell’inizio del corso. La società dell’iscritto può sostituire il/i partecipanti in qualsiasi momento previa notifica a S-IN. Il corso si svolgerà presso S-IN Soluzioni Informatiche, via Ferrari 14, 36100 Vicenza. Per ulteriori informazioni scrivere a training@s-in.it oppure a academy@umetrics.com. Per registrarsi, utilizzare il tasto "Begin registration" di questa finestra o scrivere a Soluzioni Informatiche (S.IN).
Direct link to this course: http://www.umetrics.com/default.asp/pagename/Courselist/c/2/link/2352
|
Multivariate Data Analysis, General
Start date: Tuesday, October 20, 2009 (week 43)
Language: English(UK)
Price: 1200 EUR
Last day to register:
2009-09-29
Multivariate Analysis, Basic
Using the latest multivariate techniques, participants will learn how to interpret complex data quickly and confidently. Discover the secrets of overviewing data tables and also learn how to build robust predictive models that turn data into decisions.
The course is composed of lectures, demonstrations and computer exercises in software SIMCA-P+, based on real-life datasets.
After completing the course, participants will know how to:
| • |
Apply PCA (Principal Component Analysis) to detect outliers, trends, patterns and to classify groups within complex data |
| • |
Relate multiple responses to multiple inputs using PLS (Partial Least Squares) modelling |
| • |
Interpret models to gain scientific insights |
| • |
Learn how to construct predictive models and apply them in practice. Use multivariate calibration to predict and improve quality |
| • |
Classification of raw materials and ingredients |
| • |
Analysing a multivariate problem. |
Who should participate?
The course is intended for researchers, scientists and engineers from all sectors of industry and academia. No prior knowledge of statistics is assumed.
Course schedule
Lunch daily between 12:00 - 13:00 |
| Day one |
| 9:00 |
Introduction and presentation of the need for multivariate data analysis. Introduction to three kinds of problem: overview, classification, and quantification and prediction.
Principal Component Analysis (PCA) for over-views of data tables: variable scaling, geometrical interpretation, and model evaluation.
PCA examples: quality control of manufacturing, process control (SPC) and environmental monitoring.
Computer exercises followed by discussions. |
| 17:00 |
End of lectures and exercises. |
| Day two |
| 9:00 |
Partial Least Squares (PLS): prediction of responses Y from control parameters X.
Variable scaling, geometrical interpretation, algebraic solution and model evaluation.
Model diagnoses and validation of a PLS model.
PLS examples: process and quality control.
Computer exercises followed by discussions. |
| 17:00 |
End of lectures and exercises. |
| Day three |
| 9:00 |
Multivariate calibration: prediction of chemical contents from spectroscopic data. Multivariate classification; two types of classification techniques will be discussed; SIMCA classification and PLS-DA (discriminant analysis). Exercises and discussion of participants’ own data. Course summary. |
| 15:00 |
End of course. |
Cost and conditions
Early bird registration: if you book at least 2 months prior to course date the price DISCOUNT is 17%. Also if you are more than three participants from one company booking the same course date you will receive an 8% DISCOUNT/person.
Course fee (+ VAT) includes coffee, lunch and course documentation. An invoice will be sent and payment is required within 30 days of the invoice date. Course application is binding. OBSERVE THAT OWN LAPTOPS IS REQUIERED FOR EXCERCISES. PROGRAM INSTALLATION INSTRUCTIONS WILL BE SENT OUT WITH THE FINAL COURSE INFORMATION. Cancellations registered later than two weeks before the course start will not be refunded. Provided that Umetrics AB is notified, the registering company may substitute its participant(s). If the customer cancels prior to 14 days of the course, 10% of the class fee will be applied to cover processing costs. The balance of class fees already paid to Umetrics may be credited towards a future course. The registering company may substitute its participant(s) provided that Umetrics is notified.
Umetrics holds courses based on a sufficient number of registrants. Therefore, Umetrics reserves the right to cancel the course 14 days prior to the course start date if the number of registrants is too low. Full refund will be made to these registrants. Alternately a 10% refund will be made to any registrant(s) enrolling in the next available course.
To register, please use the button "Begin registration" in this window frame, or send an email to Umetrics Academy.
Direct link to this course: http://www.umetrics.com/default.asp/pagename/Courselist/c/2/link/2381
|
Design of Experiments, General
Start date: Tuesday, October 20, 2009 (week 43)
Language: English(UK)
Price: 1200 EUR
Last day to register:
2009-09-29
Design of Experiments
Design of experiments is a rational and cost-effective approach to practical experimentation that allows the effect of variables to be assessed using a minimum of resources. Discover how to optimise your company's experiments, products and processes for increased throughput and enhanced profitability.
The course splits between lectures and hands-on analysis of real data using Umetrics' state-of-the-art software package MODDE.
After completing the course, participants will know how to:
| • |
Create efficient designs to match the experimental objectives. |
| • |
Analyse experimental data using sound statistical principles. |
| • |
Improve and optimise products and processes. |
| • |
Report results in a simple graphical format. |
| • |
Design, measure, analyse, interpret, and optimize. |
| • |
Construct predictive models and apply them in practice |
Who should participate?
The course is intended for researchers, scientists and engineers from all sectors of industry and academia. No prior knowledge of statistics is assumed.
Course schedule
Lunch daily between 12:00 - 13:00 |
| Day one |
| 09:00 |
Course start.
How and when should design of experiments be used? Problem formulation, selection of goals, factors, responses, type of model and design.
Full factorials, the basis of other designs. Analysis of full factorial designs I, evaluation of raw data, regression analysis and model interpretation.
Computer exercises followed by discussions. |
| 17:00 |
End of lectures and exercises. |
| Day two |
| 09:00 |
Analysis of full factorials II. Fault detection.
Screening designs, which factors dominate and what are their optimal ranges.
What to do after screening, optimization or modification of the design. Optimization designs, how do we find an optimum or a compromise?
Computer exercises followed by discussions. |
| 17:00 |
End of lectures and exercises. |
| Day three |
| 09:00 |
Robustness testing, verification that the method or process is robust within given specifications.
Exercises using participants' or Umetrics' examples.
Discussion of participants' own data including creation of new designs.
Course summary. |
| 15:00 |
End of course. |
Cost and conditions
Early bird registration: if you book at least 2 months prior to course date the price DISCOUNT is 17%. Also if you are more than three participants from one company booking the same course date you will receive an 8% DISCOUNT/person.
Course fee (+ VAT) includes coffee, lunch and course documentation. An invoice will be sent and payment is required within 30 days of the invoice date. Course application is binding. OBSERVE THAT OWN LAPTOPS IS REQUIERED FOR EXCERCISES. PROGRAM INSTALLATION INSTRUCTIONS WILL BE SENT OUT WITH THE FINAL COURSE INFORMATION. Cancellations registered later than two weeks before the course start will not be refunded. Provided that Umetrics AB is notified, the registering company may substitute its participant(s). If the customer cancels prior to 14 days of the course, 10% of the class fee will be applied to cover processing costs. The balance of class fees already paid to Umetrics may be credited towards a future course. The registering company may substitute its participant(s) provided that Umetrics is notified.
Umetrics holds courses based on a sufficient number of registrants. Therefore, Umetrics reserves the right to cancel the course 14 days prior to the course start date if the number of registrants is too low. Full refund will be made to these registrants. Alternately a 10% refund will be made to any registrant(s) enrolling in the next available course.
To register, please use the button "Begin registration" in this window frame, or send an email to Umetrics Academy.
Direct link to this course: http://www.umetrics.com/default.asp/pagename/Courselist/c/2/link/2384
|
Multivariate Data Analysis, General
Start date: Tuesday, October 27, 2009 (week 44)
Language: English(UK)
Price: 1200 EUR
Last day to register:
2009-10-06
Multivariate Analysis, General
Using the latest multivariate techniques, participants will learn how to interpret complex data quickly and confidently. Discover the secrets of overviewing data tables and also learn how to build robust predictive models that turn data into decisions.
The course is composed of lectures, demonstrations and computer exercises in software SIMCA-P+, based on real-life datasets.
After completing the course, participants will know how to:
| • |
Apply PCA (Principal Component Analysis) to detect outliers, trends, patterns and to classify groups within complex data |
| • |
Relate multiple responses to multiple inputs using PLS (Partial Least Squares) modelling |
| • |
Interpret models to gain scientific insights |
| • |
Learn how to construct predictive models and apply them in practice. Use multivariate calibration to predict and improve quality |
| • |
Classification of raw materials and ingredients |
| • |
Analysing a multivariate problem. |
Who should participate?
The course is intended for researchers, scientists and engineers from all sectors of industry and academia. No prior knowledge of statistics is assumed.
Course schedule
Lunch daily between 12:00 - 13:00 |
| Day one |
| 9:00 |
Introduction and presentation of the need for multivariate data analysis. Introduction to three kinds of problem: overview, classification, and quantification and prediction.
Principal Component Analysis (PCA) for over-views of data tables: variable scaling, geometrical interpretation, and model evaluation.
PCA examples: quality control of manufacturing, process control (SPC) and environmental monitoring.
Computer exercises followed by discussions. |
| 17:00 |
End of lectures and exercises. |
| Day two |
| 9:00 |
Partial Least Squares (PLS): prediction of responses Y from control parameters X.
Variable scaling, geometrical interpretation, algebraic solution and model evaluation.
Model diagnoses and validation of a PLS model.
PLS examples: process and quality control.
Computer exercises followed by discussions. |
| 17:00 |
End of lectures and exercises. |
| Day three |
| 9:00 |
Multivariate calibration: prediction of chemical contents from spectroscopic data. Multivariate classification; two types of classification techniques will be discussed; SIMCA classification and PLS-DA (discriminant analysis). Exercises and discussion of participants’ own data. Course summary. |
| 15:00 |
End of course. |
Cost and conditions
Early bird registration: if you book at least 2 months prior to course date the price DISCOUNT is 17%. Also if you are more than three participants from one company booking the same course date you will receive an 8% DISCOUNT/person.
Course fee (+VAT) includes coffee, lunch and course documentation. An invoice will be sent and payment is required within 30 days of the invoice date. Course application is binding. Cancellations registered later than two weeks before the course start will not be refunded. Provided that Umetrics AB is notified, the registering company may substitute its participant(s).
If the customer cancels prior to 14 days of the course, 10% of the class fee will be applied to cover processing costs. The balance of class fees already paid to Umetrics may be credited towards a future course. The registering company may substitute its participant(s) provided that Umetrics is notified.
Umetrics holds courses based on a sufficient number of registrants. Therefore, Umetrics reserves the right to cancel the course 14 days prior to the course start date if the number of registrants is too low. Full refund will be made to these registrants. Alternately a 10% refund will be made to any registrant(s) enrolling in the next available course.
To register, please use the button "Begin registration" in this window frame, or send an email to Umetrics Academy.
Direct link to this course: http://www.umetrics.com/default.asp/pagename/Courselist/c/2/link/2378
|
Progettazione di Esperimenti
Start date: Wednesday, October 28, 2009 (week 44)
Language: Italian
Price: 1200 EUR
Last day to register:
2009-10-07
Progettazione di Esperimenti
Lo studio di un sistema richiede la variazione di un certo numero di variabili controllate (o indipendenti) al fine di indurre le modifiche desiderate in determinate risposte (variabili dipendenti). Il “Design of Experiments” (Progettazione di Esperimenti) è una metodologia statistica che permette di identificare le condizioni sperimentali più opportune con il minor numero possibile di test e di fornire risposte concrete in tempi brevi a problemi di ottimizzazione di un processo/prodotto, di riduzione dei costi o di sottoprodotti indesiderati, di miglioramento dell’efficienza.
Umetrics fornisce il software MODDE per la sezione di esercitazioni prevista durante il corso.
Alla fine del corso i partecipanti saranno in grado di
| • |
generare un disegno sperimentale che risponda a specifiche esigenze; |
| • |
analizzare i dati mediante appropriati strumenti statistici; |
| • |
migliorare prodotti e ottimizzare processi; |
| • |
interpretare i risultati tramite grafici semplici e altamente informativi. |
A chi è rivolto
Il corso è rivolto a ricercatori, ingegneri e tecnici di qualsiasi settore industriale o accademico. Applicazioni tipiche della metodologia riguardano lo sviluppo di un nuovo prodotto, l’ottimizzazione di un processo e il controllo qualità. Non sono richieste particolari conoscenze in campo statistico.
Programma
Il pranzo è previsto tra le ore 12:30 e le 13:30 |
| Primo giorno |
| 09:00 |
Inizio delle lezioni. Quando e come applicare la Progettazione di Esperimenti. Formulazione del problema, selezione degli obiettivi, dei fattori, delle risposte; tipi di modelli e di “experimental design” disponibili. Il “Full Factorial Design” come base di altri modelli. “Full Factorial Design” parte I: valutazione dei dati grezzi, equazione di regressione e interpretazione del modello.
Esercizi e discussione. |
| 17:00 |
Conclusione. |
| Secondo giorno |
| 09:00 |
“Full Factorial Design” parte II. Valutazione degli errori; “Screening”: quali sono i fattori più importanti e quali i loro intervalli ottimali. Cosa fare dopo lo “Screening”: ottimizzazione o modifica del disegno sperimentale? Ottimizzazione: quali condizioni sperimentali corrispondono all’ottimo o al miglior compromesso?
Esercizi e discussione. |
| 17:00 |
Conclusione. |
| Terzo giorno |
| 09:00 |
Test di “robustezza” del modello: come verificare se il metodo è stabile entro gli intervalli di variazione stabiliti.
Esercizi basati su dati dei partecipanti.
|
| 15:00 |
Conclusione del corso. |
Iscrizione
il costo dell’iscrizione (+IVA) include coffee break, tre pranzi e materiale didattico. Si richiede il pagamento tramite fattura a 30 giorni che verrà emessa successivamente alla chiusura delle iscrizioni. L’iscrizione è vincolante: non è previsto il rimborso dell’iscrizione qualora la rinuncia sia notificata due settimane prima dell’inizio del corso. La società dell’iscritto può sostituire il/i partecipanti in qualsiasi momento previa notifica a S-IN. Il corso si svolgerà presso S-IN Soluzioni Informatiche, via Ferrari 14, 36100 Vicenza. Per ulteriori informazioni scrivere a training@s-in.it oppure a academy@umetrics.com. Per registrarsi, utilizzare il tasto "Begin registration" di questa finestra, o scrivere a Soluzioni Informatiche (S.IN).
Direct link to this course: http://www.umetrics.com/default.asp/pagename/Courselist/c/2/link/2350
|
Multivariate Data Analysis for Omics
Start date: Tuesday, November 10, 2009 (week 46)
Language: English(UK)
Price: 995 EUR
Last day to register:
2009-10-20
Multivariate Analysis for "Omics"
Multivariate data analysis is essential in the process of extracting information from the complex data sets involved in “omics” studies. Discover how to build valid and predictive models based on data from genomic, proteomic and metabolomic studies, with the latest multivariate techniques. The focus on this course is how to use state-of art multivariate tools to extract putative biomarkers in a statistically significant way.
The course is composed of lectures, demonstrations and computer exercises using SIMCA-P+12 software on real-life datasets. Examples from plant biology and medicine will be used to highlight the usefulness of the applied strategies.
After completing the course, participants will know how to:
| • |
Insights on chemometrics strategies for ”omics” studies |
| • |
Apply PCA to detect outliers, trends and patterns in "omics" data |
| • |
An awareness of sources of variability and the effect on modeling and interpretation |
| • |
Understanding of how to use OPLS in classification |
| • |
Understanding on how to compare multiple treatments |
| • |
Understanding on how to apply multivariate tools for putative biomarker identification |
| • |
Validate models for robustness and predictability |
Who should participate?
The course is intended for researchers involved in “omics” studies with little or no knowledge in multivariate data analysis. The examples presented in the lectures are focused on MS- and NMR-based metabolomics, for consistency. The exercises include genomics, proteomics and metabolomics data sets so participants from different field can choose from their own interest. Practice on own data is also welcome and appreciated.
Course schedule
Lunch daily between 12:00 - 13:00 |
| Day one |
| 09:00 |
Introduction to multivariate data analysis
Principal component analysis, PCA
Apply PCA to detect outliers, trends and patterns in metabolomic data
Interpret models to gain scientific insights
Exercises in SIMCA-P+ |
| 17:00 |
End of lectures and exercises and course dinner |
| Day two |
| 09:00 |
From PCA to Orthogonal projections to latent structures, OPLS
Putative biomarkers identification using OPLS
How to compare multiple treatments
Validate models for robustness and predictability
Exercises in SIMCA-P+ and discussions
Course summary |
| 17:00 |
End of course |
Cost and conditions
Early bird registration: if you book at least 2 months prior to course date the price DISCOUNT is 17%. Also if you are more than three participants from one company booking the same course date you will receive an 8% DISCOUNT/person.
Course fee (+VAT) includes coffee, lunch and course documentation. An invoice will be sent and payment is required within 30 days of the invoice date. Course application is binding. Cancellations registered later than two weeks before the course start will not be refunded. Provided that Umetrics AB is notified, the registering company may substitute its participant(s).
If the customer cancels prior to 14 days of the course, 10% of the class fee will be applied to cover processing costs. The balance of class fees already paid to Umetrics may be credited towards a future course. The registering company may substitute its participant(s) provided that Umetrics is notified.
Umetrics holds courses based on a sufficient number of registrants. Therefore, Umetrics reserves the right to cancel the course 14 days prior to the course start date if the number of registrants is too low. Full refund will be made to these registrants. Alternately a 10% refund will be made to any registrant(s) enrolling in the next available course.
To register, please use the button "Begin registration" in this window frame, or send an email to Umetrics Academy.
Direct link to this course: http://www.umetrics.com/default.asp/pagename/Courselist/c/2/link/2345
|
Design of Experiments, General
Start date: Tuesday, November 10, 2009 (week 46)
Language: English(UK)
Price: 1200 EUR
Last day to register:
2009-10-20
Design of Experiments
Design of experiments is a rational and cost-effective approach to practical experimentation that allows the effect of variables to be assessed using a minimum of resources. Discover how to optimise your company's experiments, products and processes for increased throughput and enhanced profitability.
The course splits between lectures and hands-on analysis of real data using Umetrics' state-of-the-art software package MODDE.
After completing the course, participants will know how to:
| • |
Create efficient designs to match the experimental objectives. |
| • |
Analyse experimental data using sound statistical principles. |
| • |
Improve and optimise products and processes. |
| • |
Report results in a simple graphical format. |
| • |
Design, measure, analyse, interpret, and optimize. |
| • |
Construct predictive models and apply them in practice |
Who should participate?
The course is intended for researchers, scientists and engineers from all sectors of industry and academia. No prior knowledge of statistics is assumed.
Course schedule
Lunch daily between 12:00 - 13:00 |
| Day one |
| 09:00 |
Course start.
How and when should design of experiments be used? Problem formulation, selection of goals, factors, responses, type of model and design.
Full factorials, the basis of other designs. Analysis of full factorial designs I, evaluation of raw data, regression analysis and model interpretation.
Computer exercises followed by discussions. |
| 17:00 |
End of lectures and exercises. |
| Day two |
| 09:00 |
Analysis of full factorials II. Fault detection.
Screening designs, which factors dominate and what are their optimal ranges.
What to do after screening, optimization or modification of the design. Optimization designs, how do we find an optimum or a compromise?
Computer exercises followed by discussions. |
| 17:00 |
End of lectures and exercises. |
| Day three |
| 09:00 |
Robustness testing, verification that the method or process is robust within given specifications.
Exercises using participants' or Umetrics' examples.
Discussion of participants' own data including creation of new designs.
Course summary. |
| 15:00 |
End of course. |
Cost and conditions
Early bird registration: if you book at least 2 months prior to course date the price DISCOUNT is 17%. Also if you are more than three participants from one company booking the same course date you will receive an 8% DISCOUNT/person.
Course fee (+VAT) includes coffee, lunch and course documentation. An invoice will be sent and payment is required within 30 days of the invoice date. Course application is binding. Cancellations registered later than two weeks before the course start will not be refunded. Provided that Umetrics AB is notified, the registering company may substitute its participant(s).
If the customer cancels prior to 14 days of the course, 10% of the class fee will be applied to cover processing costs. The balance of class fees already paid to Umetrics may be credited towards a future course. The registering company may substitute its participant(s) provided that Umetrics is notified.
Umetrics holds courses based on a sufficient number of registrants. Therefore, Umetrics reserves the right to cancel the course 14 days prior to the course start date if the number of registrants is too low. Full refund will be made to these registrants. Alternately a 10% refund will be made to any registrant(s) enrolling in the next available course.
To register, please use the button "Begin registration" in this window frame, or send an email to Umetrics Academy.
Direct link to this course: http://www.umetrics.com/default.asp/pagename/Courselist/c/2/link/2383
|
Design of Experiments, General
Start date: Tuesday, November 10, 2009 (week 46)
Language: Swedish
Price: 12000 SEK
Last day to register:
2009-10-20
Design of Experiments
Design of experiments is a rational and cost-effective approach to practical experimentation that allows the effect of variables to be assessed using a minimum of resources. Discover how to optimise your company's experiments, products and processes for increased throughput and enhanced profitability.
The course splits between lectures and hands-on analysis of real data using Umetrics' state-of-the-art software package MODDE.
After completing the course, participants will know how to:
| • |
Create efficient designs to match the experimental objectives. |
| • |
Analyse experimental data using sound statistical principles. |
| • |
Improve and optimise products and processes. |
| • |
Report results in a simple graphical format. |
| • |
Design, measure, analyse, interpret, and optimize. |
| • |
Construct predictive models and apply them in practice |
Who should participate?
The course is intended for researchers, scientists and engineers from all sectors of industry and academia. No prior knowledge of statistics is assumed.
Course schedule
Lunch daily between 12:00 - 13:00 |
| Day one |
| 09:00 |
Course start.
How and when should design of experiments be used? Problem formulation, selection of goals, factors, responses, type of model and design.
Full factorials, the basis of other designs. Analysis of full factorial designs I, evaluation of raw data, regression analysis and model interpretation.
Computer exercises followed by discussions. |
| 17:00 |
End of lectures and exercises. |
| Day two |
| 09:00 |
Analysis of full factorials II. Fault detection.
Screening designs, which factors dominate and what are their optimal ranges.
What to do after screening, optimization or modification of the design. Optimization designs, how do we find an optimum or a compromise?
Computer exercises followed by discussions. |
| 17:00 |
End of lectures and exercises. |
| Day three |
| 09:00 |
Robustness testing, verification that the method or process is robust within given specifications.
Exercises using participants' or Umetrics' examples.
Discussion of participants' own data including creation of new designs.
Course summary. |
| 15:00 |
End of course. |
Cost and conditions
Early bird registration: if you book at least 2 months prior to course date the price DISCOUNT is 17%. Also if you are more than three participants from one company booking the same course date you will receive an 8% DISCOUNT/person.
Course fee (+VAT) includes coffee, lunch and course documentation. An invoice will be sent and payment is required within 30 days of the invoice date. Course application is binding. Cancellations registered later than two weeks before the course start will not be refunded. Provided that Umetrics AB is notified, the registering company may substitute its participant(s).
If the customer cancels prior to 14 days of the course, 10% of the class fee will be applied to cover processing costs. The balance of class fees already paid to Umetrics may be credited towards a future course. The registering company may substitute its participant(s) provided that Umetrics is notified.
Umetrics holds courses based on a sufficient number of registrants. Therefore, Umetrics reserves the right to cancel the course 14 days prior to the course start date if the number of registrants is too low. Full refund will be made to these registrants. Alternately a 10% refund will be made to any registrant(s) enrolling in the next available course.
To register, please use the button "Begin registration" in this window frame, or send an email to Umetrics Academy.
Direct link to this course: http://www.umetrics.com/default.asp/pagename/Courselist/c/2/link/2371
|
Process Analytical Technology
Start date: Wednesday, November 11, 2009 (week 46)
Language: English
Price: $1,795 US
Last day to register:
2009-10-21
Multivariate Analysis for PAT
This course introduces PAT (Process Analytical Technologies) as it applies in the pharmaceutical and biotech industries, and the objectives of PAT. This three-day course is dedicated to the multivariate methods and applications essential for development of process understanding and execution of PAT projects. The course covers PAT in both Process R&D and Manufacturing with the emphasis on chemometrics, analytical and IT aspects, and is illustrated by real life examples.
The topics covered include analysis of raw material variation, MV calibration, batch analysis and design of experiments. Applications include MV calibration, end point detection, multivariate monitoring (real-time MSPC) of batch processes, identification of critical process parameters, prediction of quality and a methodology for modeling complete production trains. There is also discussion of data infrastructure requirements that enable these types of analysis.
Chemometrics tools essential to PAT, i.e., PCA, PLS, Multivariate Calibration, Classification, Batch Modeling and Design of Experiments (DoE) are worked through and organized into the four levels of PAT.
The topics of data integration and IT, and the required infrastructure are addressed as well as Regulatory aspects.
After completing the course, each participant will be able to:
| • |
Identify critical process parameters |
| • |
Evaluate manufacturing performance for quality investigations |
| • |
Understand the technology required to accomplish PAT objectives |
| • |
Quantify the influence of raw material and process variation on product quality |
Who should participate?
The course is intended for researchers, scientists and engineers from all sectors of industry and academia. No prior knowledge of statistics is assumed.
Course schedule
Lunch daily between 12:00 - 13:00 |
| Day one |
| 08:30 |
Introduction and presentation of three kinds of problems: overview, classification, and quantification and prediction. Principal Component Analysis (PCA) for overview of data tables: variable scaling, geometrical interpretation, and model evaluation. PCA examples: quality control of manufacturing, process control (SPC) and environmental monitoring.
Computer exercises followed by discussion. |
| 17:00 |
End of lectures and exercises |
| Day two |
| 08:30 |
Partial Least Squares (PLS): prediction of responses Y from inputs X e.g. spectra, process variables etc.
Variable scaling, geometrical interpretation, algebraic solution and model evaluation.
Multivariate characterisation: quantification of qualitative differences (batches of raw material, chemicals, suppliers). Multivariate calibration: prediction of chemical contents from spectroscopic data.
PLS examples: NIR calibration of API concentration in tablets, mixing of two powders.
Computer exercises followed by discussion. |
| 17:00 |
End of lectures and exercises. |
| Day three |
| 8:30 |
Multivariate batch modelling.
Computer exercises on API manufacture and reaction monitoring. Multivariate process modelling.
Computer exercises and analysis of student data.
Course summary. |
| 17:00 |
End of course |
Cost and conditions
Course fee includes coffee, lunch, and course documentation. Course registration is binding. Cancellations received within two weeks of the course start date will forfeit the entire course fee. If the customer cancels prior to 14 days of the course, 20% of the class fee will be applied to cover processing costs. The balance of class fees already paid to Umetrics may be credited towards a future course. The registering company may substitute its participant(s) provided that Umetrics is notified.
Umetrics holds courses based on a sufficient number of registrants. Therefore, Umetrics reserves the right to cancel the course 14 days prior to the course start date if the number of registrants is too low. Full refund will be made to these registrants. Alternately a 10% refund will be made to any registrant(s) enrolling in the next available course.
Early bird registration: if you book at least 2 months prior to course date the price DISCOUNT is 15%. Also if you are more than three participants from one company booking the same course date you will receive a 10% DISCOUNT/person.
To register, please use the button "Begin registration" in this window frame, or send an email to Umetrics Academy.
Direct link to this course: http://www.umetrics.com/default.asp/pagename/Courselist/c/2/link/10083
|
Multivariate Data Analysis, General
Start date: Tuesday, November 17, 2009 (week 47)
Language: Swedish
Price: 12000 SEK
Last day to register:
2009-10-27
Multivariate Analysis, General
Using the latest multivariate techniques, participants will learn how to interpret complex data quickly and confidently. Discover the secrets of overviewing data tables and also learn how to build robust predictive models that turn data into decisions.
The course is composed of lectures, demonstrations and computer exercises in software SIMCA-P+, based on real-life datasets.
After completing the course, participants will know how to:
| • |
Apply PCA (Principal Component Analysis) to detect outliers, trends, patterns and to classify groups within complex data |
| • |
Relate multiple responses to multiple inputs using PLS (Partial Least Squares) modelling |
| • |
Interpret models to gain scientific insights |
| • |
Learn how to construct predictive models and apply them in practice. Use multivariate calibration to predict and improve quality |
| • |
Classification of raw materials and ingredients |
| • |
Analysing a multivariate problem. |
Who should participate?
The course is intended for researchers, scientists and engineers from all sectors of industry and academia. No prior knowledge of statistics is assumed.
Course schedule
Lunch daily between 12:00 - 13:00 |
| Day one |
| 9:00 |
Introduction and presentation of the need for multivariate data analysis. Introduction to three kinds of problem: overview, classification, and quantification and prediction.
Principal Component Analysis (PCA) for over-views of data tables: variable scaling, geometrical interpretation, and model evaluation.
PCA examples: quality control of manufacturing, process control (SPC) and environmental monitoring.
Computer exercises followed by discussions. |
| 17:00 |
End of lectures and exercises. |
| Day two |
| 9:00 |
Partial Least Squares (PLS): prediction of responses Y from control parameters X.
Variable scaling, geometrical interpretation, algebraic solution and model evaluation.
Model diagnoses and validation of a PLS model.
PLS examples: process and quality control.
Computer exercises followed by discussions. |
| 17:00 |
End of lectures and exercises. |
| Day three |
| 9:00 |
Multivariate calibration: prediction of chemical contents from spectroscopic data. Multivariate classification; two types of classification techniques will be discussed; SIMCA classification and PLS-DA (discriminant analysis). Exercises and discussion of participants’ own data. Course summary. |
| 15:00 |
End of course. |
Cost and conditions
Early bird registration: if you book at least 2 months prior to course date the price DISCOUNT is 17%. Also if you are more than three participants from one company booking the same course date you will receive an 8% DISCOUNT/person.
Course fee (+VAT) includes coffee, lunch and course documentation. An invoice will be sent and payment is required within 30 days of the invoice date. Course application is binding. Cancellations registered later than two weeks before the course start will not be refunded. Provided that Umetrics AB is notified, the registering company may substitute its participant(s).
If the customer cancels prior to 14 days of the course, 10% of the class fee will be applied to cover processing costs. The balance of class fees already paid to Umetrics may be credited towards a future course. The registering company may substitute its participant(s) provided that Umetrics is notified.
Umetrics holds courses based on a sufficient number of registrants. Therefore, Umetrics reserves the right to cancel the course 14 days prior to the course start date if the number of registrants is too low. Full refund will be made to these registrants. Alternately a 10% refund will be made to any registrant(s) enrolling in the next available course.
To register, please use the button "Begin registration" in this window frame, or send an email to Umetrics Academy.
Direct link to this course: http://www.umetrics.com/default.asp/pagename/Courselist/c/2/link/2368
|
Design of Experiments, General
Start date: Tuesday, November 17, 2009 (week 47)
Language: English(UK)
Price: 1200 EUR
Last day to register:
2009-10-27
Design of Experiments
Design of experiments is a rational and cost-effective approach to practical experimentation that allows the effect of variables to be assessed using a minimum of resources. Discover how to optimise your company's experiments, products and processes for increased throughput and enhanced profitability.
The course splits between lectures and hands-on analysis of real data using Umetrics' state-of-the-art software package MODDE.
After completing the course, participants will know how to:
| • |
Create efficient designs to match the experimental objectives. |
| • |
Analyse experimental data using sound statistical principles. |
| • |
Improve and optimise products and processes. |
| • |
Report results in a simple graphical format. |
| • |
Design, measure, analyse, interpret, and optimize. |
| • |
Construct predictive models and apply them in practice |
Who should participate?
The course is intended for researchers, scientists and engineers from all sectors of industry and academia. No prior knowledge of statistics is assumed.
Course schedule
Lunch daily between 12:00 - 13:00 |
| Day one |
| 09:00 |
Course start.
How and when should design of experiments be used? Problem formulation, selection of goals, factors, responses, type of model and design.
Full factorials, the basis of other designs. Analysis of full factorial designs I, evaluation of raw data, regression analysis and model interpretation.
Computer exercises followed by discussions. |
| 17:00 |
End of lectures and exercises. |
| Day two |
| 09:00 |
Analysis of full factorials II. Fault detection.
Screening designs, which factors dominate and what are their optimal ranges.
What to do after screening, optimization or modification of the design. Optimization designs, how do we find an optimum or a compromise?
Computer exercises followed by discussions. |
| 17:00 |
End of lectures and exercises. |
| Day three |
| 09:00 |
Robustness testing, verification that the method or process is robust within given specifications.
Exercises using participants' or Umetrics' examples.
Discussion of participants' own data including creation of new designs.
Course summary. |
| 15:00 |
End of course. |
Cost and conditions
Early bird registration: if you book at least 2 months prior to course date the price DISCOUNT is 17%. Also if you are more than three participants from one company booking the same course date you will receive an 8% DISCOUNT/person.
Course fee (+VAT) includes coffee, lunch and course documentation. An invoice will be sent and payment is required within 30 days of the invoice date. Course application is binding. Cancellations registered later than two weeks before the course start will not be refunded. Provided that Umetrics AB is notified, the registering company may substitute its participant(s).
If the customer cancels prior to 14 days of the course, 10% of the class fee will be applied to cover processing costs. The balance of class fees already paid to Umetrics may be credited towards a future course. The registering company may substitute its participant(s) provided that Umetrics is notified.
Umetrics holds courses based on a sufficient number of registrants. Therefore, Umetrics reserves the right to cancel the course 14 days prior to the course start date if the number of registrants is too low. Full refund will be made to these registrants. Alternately a 10% refund will be made to any registrant(s) enrolling in the next available course.
To register, please use the button "Begin registration" in this window frame, or send an email to Umetrics Academy.
Direct link to this course: http://www.umetrics.com/default.asp/pagename/Courselist/c/2/link/2374
|
Design of Experiments, General
Start date: Tuesday, December 01, 2009 (week 49)
Language: English(UK)
Price: 1200 EUR
Last day to register:
2009-11-10
Design of Experiments
Design of experiments is a rational and cost-effective approach to practical experimentation that allows the effect of variables to be assessed using a minimum of resources. Discover how to optimise your company's experiments, products and processes for increased throughput and enhanced profitability.
The course splits between lectures and hands-on analysis of real data using Umetrics' state-of-the-art software package MODDE.
After completing the course, participants will know how to:
| • |
Create efficient designs to match the experimental objectives. |
| • |
Analyse experimental data using sound statistical principles. |
| • |
Improve and optimise products and processes. |
| • |
Report results in a simple graphical format. |
| • |
Design, measure, analyse, interpret, and optimize. |
| • |
Construct predictive models and apply them in practice |
Who should participate?
The course is intended for researchers, scientists and engineers from all sectors of industry and academia. No prior knowledge of statistics is assumed.
Course schedule
Lunch daily between 12:00 - 13:00 |
| Day one |
| 09:00 |
Course start.
How and when should design of experiments be used? Problem formulation, selection of goals, factors, responses, type of model and design.
Full factorials, the basis of other designs. Analysis of full factorial designs I, evaluation of raw data, regression analysis and model interpretation.
Computer exercises followed by discussions. |
| 17:00 |
End of lectures and exercises. |
| Day two |
| 09:00 |
Analysis of full factorials II. Fault detection.
Screening designs, which factors dominate and what are their optimal ranges.
What to do after screening, optimization or modification of the design. Optimization designs, how do we find an optimum or a compromise?
Computer exercises followed by discussions. |
| 17:00 |
End of lectures and exercises. |
| Day three |
| 09:00 |
Robustness testing, verification that the method or process is robust within given specifications.
Exercises using participants' or Umetrics' examples.
Discussion of participants' own data including creation of new designs.
Course summary. |
| 15:00 |
End of course. |
Cost and conditions
Early bird registration: if you book at least 2 months prior to course date the price DISCOUNT is 17%. Also if you are more than three participants from one company booking the same course date you will receive an 8% DISCOUNT/person.
Course fee (+VAT) includes coffee, lunch and course documentation. An invoice will be sent and payment is required within 30 days of the invoice date. Course application is binding. Cancellations registered later than two weeks before the course start will not be refunded. Provided that Umetrics AB is notified, the registering company may substitute its participant(s).
If the customer cancels prior to 14 days of the course, 10% of the class fee will be applied to cover processing costs. The balance of class fees already paid to Umetrics may be credited towards a future course. The registering company may substitute its participant(s) provided that Umetrics is notified.
Umetrics holds courses based on a sufficient number of registrants. Therefore, Umetrics reserves the right to cancel the course 14 days prior to the course start date if the number of registrants is too low. Full refund will be made to these registrants. Alternately a 10% refund will be made to any registrant(s) enrolling in the next available course.
To register, please use the button "Begin registration" in this window frame, or send an email to Umetrics Academy.
Direct link to this course: http://www.umetrics.com/default.asp/pagename/Courselist/c/2/link/2379
|
Design of Experiments, General
Start date: Tuesday, December 01, 2009 (week 49)
Language: English(UK)
Price: 12000 SEK
Last day to register:
2009-11-10
Design of Experiments
Design of experiments is a rational and cost-effective approach to practical experimentation that allows the effect of variables to be assessed using a minimum of resources. Discover how to optimise your company's experiments, products and processes for increased throughput and enhanced profitability.
The course splits between lectures and hands-on analysis of real data using Umetrics' state-of-the-art software package MODDE.
After completing the course, participants will know how to:
| • |
Create efficient designs to match the experimental objectives. |
| • |
Analyse experimental data using sound statistical principles. |
| • |
Improve and optimise products and processes. |
| • |
Report results in a simple graphical format. |
| • |
Design, measure, analyse, interpret, and optimize. |
| • |
Construct predictive models and apply them in practice |
Who should participate?
The course is intended for researchers, scientists and engineers from all sectors of industry and academia. No prior knowledge of statistics is assumed.
Course schedule
Lunch daily between 12:00 - 13:00 |
| Day one |
| 09:00 |
Course start.
How and when should design of experiments be used? Problem formulation, selection of goals, factors, responses, type of model and design.
Full factorials, the basis of other designs. Analysis of full factorial designs I, evaluation of raw data, regression analysis and model interpretation.
Computer exercises followed by discussions. |
| 17:00 |
End of lectures and exercises. |
| Day two |
| 09:00 |
Analysis of full factorials II. Fault detection.
Screening designs, which factors dominate and what are their optimal ranges.
What to do after screening, optimization or modification of the design. Optimization designs, how do we find an optimum or a compromise?
Computer exercises followed by discussions. |
| 17:00 |
End of lectures and exercises. |
| Day three |
| 09:00 |
Robustness testing, verification that the method or process is robust within given specifications.
Exercises using participants' or Umetrics' examples.
Discussion of participants' own data including creation of new designs.
Course summary. |
| 15:00 |
End of course. |
Cost and conditions
Early bird registration: if you book at least 2 months prior to course date the price DISCOUNT is 17%. Also if you are more than three participants from one company booking the same course date you will receive an 8% DISCOUNT/person.
Course fee (+VAT) includes coffee, lunch and course documentation. An invoice will be sent and payment is required within 30 days of the invoice date. Course application is binding. Cancellations registered later than two weeks before the course start will not be refunded. Provided that Umetrics AB is notified, the registering company may substitute its participant(s).
If the customer cancels prior to 14 days of the course, 10% of the class fee will be applied to cover processing costs. The balance of class fees already paid to Umetrics may be credited towards a future course. The registering company may substitute its participant(s) provided that Umetrics is notified.
Umetrics holds courses based on a sufficient number of registrants. Therefore, Umetrics reserves the right to cancel the course 14 days prior to the course start date if the number of registrants is too low. Full refund will be made to these registrants. Alternately a 10% refund will be made to any registrant(s) enrolling in the next available course.
To register, please use the button "Begin registration" in this window frame, or send an email to Umetrics Academy.
Direct link to this course: http://www.umetrics.com/default.asp/pagename/Courselist/c/2/link/2369
|
Multivariate Data Analysis for PAT
Start date: Tuesday, December 01, 2009 (week 49)
Language: English(UK)
Price: 1095 GBP
Last day to register:
2009-11-10
Multivariate Analysis for PAT
Process Analytical Technology (PAT) is a drive within pharmaceutical manufacturing to improve process understanding, process consistency and provide a framework for continuous improvement. This course enables understanding of the central role of multivariate analysis in this process. Delegates will learn how to interpret complex data quickly and confidently, and find out how to build robust predictive models that turn data into decisions.
The course is composed of lectures, demonstrations and computer exercises in software SIMCA-P+, based on real-life datasets.
After completing the course, participants will know how to:
| • |
Apply PCA (Principal Component Analysis) to detect outliers, trends, patterns and to classify groups within complex data |
| • |
Relate multiple responses to multiple inputs using PLS (Partial Least Squares) modelling |
| • |
Interpret models to gain scientific insights |
| • |
Learn how to model processes and use multivariate calibration to improve quality |
| • |
Characterise raw materials and ingredients |
| • |
Construct predictive models and apply them in practice |
Who should participate?
The course is intended for researchers, scientists and engineers in life science industry, or with an interest in PAT. No prior knowledge of statistics is assumed.
Course schedule
Lunch daily between 12:00 - 13:00 |
| Day one |
| 09:00 |
Introduction and presentation of three kinds of problem: overview, classification, and quantification and prediction.
Principal Component Analysis (PCA) for overview of data tables: variable scaling, geometrical interpretation, and model evaluation.
PCA examples: quality control of manufacturing, process control (SPC) and environmental monitoring.
Computer exercises followed by discussions. |
| 17:00 |
End of lectures and exercises. Dinner in Cork.
|
| Day two |
| 09:00 |
Partial Least Squares (PLS): prediction of responses Y from inputs X e.g. spectra, process variables etc.
Variable scaling, geometrical interpretation, algebraic solution and model evaluation.
Multivariate characterisation: quantification of qualitative differences (batches of raw material, chemicals, suppliers).
Multivariate calibration: prediction of chemical contents from spectroscopic data.
PLS examples: NIR calibration of API concentration in tablets, mixing of two powders.
Computer exercises followed by discussion. |
| 17:00 |
End of lectures and exercises. |
| Day three |
| 09:00 |
Multivariate batch modelling. Computer exercises on API manufacture and reaction monitoring. Multivariate process modelling. Computer exercises and analysis of delegates' own data.
Course summary. |
| 16:00 |
End of course. |
Cost and conditions
Course fee is £1145 (+VAT) which includes lunch each day and the course dinner on Tuesday evening. The course will be held at our offices in Winkfield Ascot. B&B accommodation is available at the nearby Harte & Garter hotel in Windsor at preferential rates. Umetrics will organise accommodation at the hotel but delegates are responsible for settling their own bills. Cancellations received later than two weeks before the course starts will be charged at the full rate. Providing that Umetrics is notified, the registering company may substitute participants.
To register, please use the button "Begin registration" in this window frame, or send an email to Umetrics Academy.
Direct link to this course: http://www.umetrics.com/default.asp/pagename/Courselist/c/2/link/2346
|
Multivariate Data Analysis for Omics
Start date: Tuesday, January 19, 2010 (week 3)
Language: English(UK)
Price: 995 EUR
Last day to register:
2009-12-29
Multivariate Analysis for "Omics"
Multivariate data analysis is essential in the process of extracting information from the complex data sets involved in “omics” studies. Discover how to build valid and predictive models based on data from genomic, proteomic and metabolomic studies, with the latest multivariate techniques. The focus on this course is how to use state-of art multivariate tools to extract putative biomarkers in a statistically significant way.
The course is composed of lectures, demonstrations and computer exercises using SIMCA-P+12 software on real-life datasets. Examples from plant biology and medicine will be used to highlight the usefulness of the applied strategies.
After completing the course, participants will know how to:
| • |
Insights on chemometrics strategies for ”omics” studies |
| • |
Apply PCA to detect outliers, trends and patterns in "omics" data |
| • |
An awareness of sources of variability and the effect on modeling and interpretation |
| • |
Understanding of how to use OPLS in classification |
| • |
Understanding on how to compare multiple treatments |
| • |
Understanding on how to apply multivariate tools for putative biomarker identification |
| • |
Validate models for robustness and predictability |
Who should participate?
The course is intended for researchers involved in “omics” studies with little or no knowledge in multivariate data analysis. The examples presented in the lectures are focused on MS- and NMR-based metabolomics, for consistency. The exercises include genomics, proteomics and metabolomics data sets so participants from different field can choose from their own interest. Practice on own data is also welcome and appreciated.
Course schedule
Lunch daily between 12:00 - 13:00 |
| Day one |
| 09:00 |
Introduction to multivariate data analysis
Principal component analysis, PCA
Apply PCA to detect outliers, trends and patterns in metabolomic data
Interpret models to gain scientific insights
Exercises in SIMCA-P+ |
| 17:00 |
End of lectures and exercises and course dinner |
| Day two |
| 09:00 |
From PCA to Orthogonal projections to latent structures, OPLS
Putative biomarkers identification using OPLS
How to compare multiple treatments
Validate models for robustness and predictability
Exercises in SIMCA-P+ and discussions
Course summary |
| 17:00 |
End of course |
Cost and conditions
Early bird registration: if you book at least 2 months prior to course date the price DISCOUNT is 17%. Also if you are more than three participants from one company booking the same course date you will receive an 8% DISCOUNT/person.
Course fee (+VAT) includes coffee, lunch and course documentation. An invoice will be sent and payment is required within 30 days of the invoice date. Course application is binding. Cancellations registered later than two weeks before the course start will not be refunded. Provided that Umetrics AB is notified, the registering company may substitute its participant(s).
If the customer cancels prior to 14 days of the course, 10% of the class fee will be applied to cover processing costs. The balance of class fees already paid to Umetrics may be credited towards a future course. The registering company may substitute its participant(s) provided that Umetrics is notified.
Umetrics holds courses based on a sufficient number of registrants. Therefore, Umetrics reserves the right to cancel the course 14 days prior to the course start date if the number of registrants is too low. Full refund will be made to these registrants. Alternately a 10% refund will be made to any registrant(s) enrolling in the next available course.
To register, please use the button "Begin registration" in this window frame, or send an email to Umetrics Academy.
Direct link to this course: http://www.umetrics.com/default.asp/pagename/Courselist/c/2/link/2375
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| Design of Experiments, General |
Denmark, Copenhagen |
2009-09-01 |
3 |
English(UK) |
| Multivariate Data Analysis, General |
Denmark, Copenhagen |
2009-09-15 |
3 |
English(UK) |
| Design of Experiments, General |
Switzerland, Basel |
2009-09-15 |
3 |
English(UK) |
| Multivariate Data Analysis, General |
United Kingdom, Ascot |
2009-09-15 |
3 |
English(UK) |
| Multivariate Data Analysis, General |
Germany, Frankfurt |
2009-09-15 |
3 |
English(UK) |
| Multivariate Data Analysis, General |
USA, MA, Boston |
2009-09-16 |
3 |
English |
| Design of Experiments, General |
Sweden, Stockholm |
2009-09-22 |
3 |
Swedish |
| Advanced Design of Experiments for Mixtures |
Italy, Vicenza |
2009-09-23 |
2 |
English(UK) |
| Multivariate Data Analysis, General |
Sweden, Gothenburg |
2009-09-29 |
3 |
Swedish |
| Design of Experiments, General |
Netherlands, Amsterdam |
2009-09-29 |
3 |
English(UK) |
| Multivariate Data Analysis for Batch |
USA, CA, San Jose |
2009-10-06 |
3 |
English |
| Design of Experiments, General |
United Kingdom, Ascot |
2009-10-06 |
3 |
English(UK) |
| Multivariate Data Analysis for Omics |
Switzerland, Basel |
2009-10-13 |
2 |
English(UK) |
| Design of Experiments, General |
Germany, Munich |
2009-10-13 |
3 |
English(UK) |
| Analisi Multivariata di Dati |
Italy, Vicenza |
2009-10-14 |
3 |
Italian |
| Multivariate Data Analysis, General |
Netherlands, Amsterdam |
2009-10-20 |
3 |
English(UK) |
| Design of Experiments, General |
Spain, Barcelona |
2009-10-20 |
3 |
English(UK) |
| Multivariate Data Analysis, General |
Switzerland, Basel |
2009-10-27 |
3 |
English(UK) |
| Progettazione di Esperimenti |
Italy, Vicenza |
2009-10-28 |
3 |
Italian |
| Multivariate Data Analysis for Omics |
United Kingdom, Ascot |
2009-11-10 |
2 |
English(UK) |
| Design of Experiments, General |
Germany, Frankfurt |
2009-11-10 |
3 |
English(UK) |
| Design of Experiments, General |
Sweden, Gothenburg |
2009-11-10 |
3 |
Swedish |
| Process Analytical Technology |
USA, NV, Las Vegas |
2009-11-11 |
3 |
English |
| Multivariate Data Analysis, General |
Sweden, Stockholm |
2009-11-17 |
3 |
Swedish |
| Design of Experiments, General |
Denmark, Copenhagen |
2009-11-17 |
3 |
English(UK) |
| Design of Experiments, General |
Switzerland, Basel |
2009-12-01 |
3 |
English(UK) |
| Design of Experiments, General |
Sweden, Stockholm |
2009-12-01 |
3 |
English(UK) |
| Multivariate Data Analysis for PAT |
United Kingdom, Ascot |
2009-12-01 |
3 |
English(UK) |
| Multivariate Data Analysis for Omics |
Denmark, Copenhagen |
2010-01-19 |
2 |
English(UK) |
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Overview
Course schedule