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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, May 13, 2008 (week 20)
Language: English(UK)
Price: 1400 EUR
Last day to register:
2008-04-22
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
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).
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/2203
|
Försöksplanering, grundkurs
Start date: Tuesday, May 20, 2008 (week 21)
Language: Swedish
Price: 13500 SEK
Last day to register:
2008-04-29
Försöksplanering, grundkurs
Försöksplanering blir ett allt viktigare konkurrensmedel i takt med att kraven på kostnadseffektivitet och kortare ledtider ökar. Det gäller att träffa rätt så fort som möjligt. En strukturering av den experimentella verksamheten går också hand i hand med en allt större fokusering på nya kvalitetsrutiner.
Vi kommer under kursen att behandla ett antal problem ur multivariat synvinkel, där flera variabler påverkar resultatet. Ett av kursens huvudmoment är att också analysera och optimera flera resultatvariabler.
Kursen består av föreläsningar och praktiska övningar i programvaran MODDE utifrån Umetrics material. Du kommer även att ges möjlighet att diskutera egna frågeställningar och öva med egna problemställningar.
Du kommer att kunna tillämpa kunskaperna vid bl a:
| • |
Utveckling av nya produkter och processer |
| • |
Förbättring av existerande produkter och processer |
| • |
Utvärdering av leverantörer |
| • |
Robusthetsdesigner |
| • |
Samtidig optimering av ett flertal resultatparametrar |
Vem bör delta?
Kursen vänder sig till dig som är tekniker eller naturvetare och arbetar med forskning, utveckling, produktion eller kvalitetskontroll.
Kursprogram
Lunch mellan 12:00 - 13:00 |
| Dag ett |
| 09:00 |
Introduktion.
Hur och när skall försöksplanering användas? Problemformulering, val av mål, faktorer, responser, typ av modell samt design.
Faktorförsök. Analys av fullständiga faktorförsök I, inspektion av mätdata, regressionsanalys och modelltolkning.
Övningar, diskussion av övningsresultat. |
| 17:00 |
Föreläsningar och övningar avslutas. |
| Dag två |
| 09:00 |
Analys av fullständiga faktorförsök II, felsökning, t.ex. kurvatur och avvikande experiment.
Sållningsdesigner, vilka faktorer har störst betydelse och hur skall de varieras.
Optimeringsdesigner, hur hittar vi optimum eller en kompromiss. Vad man gör efter sållning, optimering eller modifiering av designen.
Övningar, diskussion av övningsresultat. |
| 17:00 |
Föreläsningar och övningar avslutas. |
| Dag tre |
| 09:00 |
Robusthetsdesigner. Verifiera att metoden eller processen är robust.
Övningar och diskussion av egna eller Umetrics exempel. Genomgång av kursdeltagarnas egna problem och uppsättande av försöksplaner.
Sammanfattning av kursen. |
| 15:00 |
Kursen avslutas. |
Pris och villkor
Kursavgiften inkluderar kursmaterial samt lunch och kaffe (ev. moms tillkommer). Betalning sker via faktura och motses innan kursstart. Anmälan till kursen är bindande. Vid avbokning senare än 14 dagar före kursstart uttages full kurskostnad. Det står företaget fritt att efter meddelande till Umetrics sända annan kursdeltagare.
Anmälan kan göras genom att trycka på knappen "Begin registration" i ramen för detta fönster, eller genom att kontakta Umetrics Academy.
Direct link to this course: http://www.umetrics.com/default.asp/pagename/Courselist/c/2/link/2185
|
Multivariate Data Analysis, General
Start date: Tuesday, May 20, 2008 (week 21)
Language: English(UK)
Price: 1400 EUR
Last day to register:
2008-04-29
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
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).
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/2194
|
Design of Experiments, General
Start date: Tuesday, May 20, 2008 (week 21)
Language: English(UK)
Price: 1095 GBP
Last day to register:
2008-04-29
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 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. 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/2210
|
Design of Experiments, general
Start date: Monday, May 26, 2008 (week 22)
Language: English
Price: $1,795 US (for additional fee computer will be provided)
Last day to register:
2008-05-05
Design of Experiments, General
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
Course fee includes coffee, lunch and course documentation. For an additional fee of $230 US, computer will be provided during 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/10070
|
Multivariate Data Analysis for PAT
Start date: Tuesday, June 03, 2008 (week 23)
Language: English(UK)
Price: 1145 GBP
Last day to register:
2008-05-13
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 the Carrigaline Court Hotel & Leisure Centre, where B&B accommodation is available at a special delegate rate of €93. 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/2213
|
Design of Experiments, General
Start date: Tuesday, June 03, 2008 (week 23)
Language: English(UK)
Price: 1400 EUR
Last day to register:
2008-05-13
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
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).
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/2208
|
Design of Experiments, General
Start date: Tuesday, June 10, 2008 (week 24)
Language: English(UK)
Price: 1400 EUR
Last day to register:
2008-05-20
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
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).
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/2196
|
Progettazione di Esperimenti
Start date: Wednesday, June 18, 2008 (week 25)
Language: Italian
Price: 1250 EUR
Last day to register:
2008-05-28
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/2234
|
Multivariate Data Analysis, General
Start date: Monday, June 23, 2008 (week 26)
Language: English
Price: $1,795 US (for additional fee computer will be provided)
Last day to register:
2008-06-02
|
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Overview
Course schedule