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Overview
What you will study
- The Foundations of Data and Models - Regression Analytics course offered by Massachusetts Institute of Technology (MIT) starts with mostly simple linear algebra and computational methods, and introduces some more difficult mathematical concepts towards the end.
- This method also, by design, fits in with our approach of morning lectures and afternoon practice on personal computers.
- The combined teaching system provides opportunities for much hands-on learning and participants leave the course with practical knowledge of the basic algorithms.
The learning objectives of the course are:
- Examining how to fit data to models
- Defining linear least squares, non-linear least squares, singular value decomposition, sensitivity analysis, experiment design, and parameter error estimation
- Appreciating grid search, random search, simulated annealing, genetic algorithms, neural networks, and large inverse systems
- Investigating principles leading to rapid application of methods
- Evaluating the results of pre-programmed computer exercises
Programme Structure
The program focuses on:
- Philosophy of Data and Models
- Statistics
- Straight Line Data Analysis
- Least Squares
- Levenberg-Marquardt and Ridge Regression Algorithms
- Damped Least Squares Comparison
- Stochastic Inverse
- Singular Value Decomposition
- Random and Grid-Search Methods
- Simulated Annealing and Genetic Algorithms
- Neural Networks
- Parameter Error Estimates
- Large Inverse Problems
- Experimental Design
Key information
Duration
- Full-time
- 5 days
Start dates & application deadlines
We did our best, but couldn't find the next application deadline and start date information online.
More details
- Start dates to be determined
Language
English
Credits
3 alternative credits
Delivered
On Campus
Campus Location
- Boston, United States
Disciplines
Data Science & Big Data View 472 other Short Courses in Data Science & Big Data in United StatesWhat students do after studying Computer Science & IT
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Academic requirements
We are not aware of any specific GRE, GMAT or GPA grading score requirements for this programme.
English requirements
We are not aware of any English requirements for this programme.
Other requirements
General requirements
- This course is ideal for anyone who fits data to models.
- Familiarity with computing and statistics is desirable.
- A fair background in linear algebra is highly recommended.
Technological requirements
- Laptops for which you have administrative privileges are required for this course.
- PCs are recommended.
- Tablets will not be sufficient for the computing activities performed in this course.
Tuition Fees
Tuition fees are shown in and the most likely applicable fee is shown based on your nationality.
-
International Applies to you
Applies to youNon-residents4500 USD / full≈ 4500 USD / full - Out-of-State4500 USD / full≈ 4500 USD / full
-
Domestic
Applies to youIn-State4500 USD / full≈ 4500 USD / full
Living costs
Boston
United States
1560 - 3239 USD / month
The living costs include the total expenses per month, covering accommodation, public transportation, utilities (electricity, internet), books and groceries.
Funding
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