FA18
Deterministic Optimization
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This course blends optimization theory and computation and its teachings can be applied to modern data analytics, economics, and engineering. Organized across four modules, it takes learners through basic concepts, models, and algorithms in linear optimization, convex optimization, and integer optimization.The first module of the course is a general overview of key concepts in linear algebra, calculus, and optimization. The second module of the course is on linear optimization, covering modeling techniques with many applications, basic polyhedral theory, simplex method, and duality theory. The third module is on convex conic optimization, which is a significant generalization of linear optimization. The fourth and final module focuses on integer optimization, which augments the previously covered optimization models with the flexibility of integer decision variables.
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Rating | 3.5★ based on 4 ratings |
---|---|
Length | 15 weeks |
Effort | 8 - 10 hours per week |
Starts | Aug 20 (293 weeks ago) |
Cost | $0 |
From | GTx via edX |
Instructor | Shabbir Ahmed |
Download Videos | On all desktop and mobile devices |
Language | English |
Subjects | Data Science |
Tags | Data Analysis & Statistics |
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What people are saying
covered range from non-constrained
The course is an introduction to deterministic optimization, the topics covered range from non-constrained optimization (the most basic one) to basic algorithms for integer programming, central topics like convexity and applications are also included.
peer review assessments allow
The quality of the lectures is very good, and the peer review assessments allow students to have a sort of personalized feedback.
second part working more
I wish it had a second part working more with non-linear models and available tools for nonlinear optimization in Python.
several open source libraries
Mostly Python is used for solving the problems making used of several open source libraries, MATLAB was briefly mentioned but in my opinion Python is better for this field.
central topics like convexity
introductory text says there
The introductory text says there 4 modules, but the syllabus shows that there are 14 modules.
applications are also included
symbolic passing grade
Therefore I was not able to obtain even a symbolic passing grade, despite completing all assignments that were provided to me.
briefly mentioned but
available tools
complete access
This course (run in early 2018) broke the enrollment clause stating "Audit this course for free and have complete access to all the course material, activities, tests, and forums".
computational using
The course assignments are half theoretical and half computational using Python or MATLAB.
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Rating | 3.5★ based on 4 ratings |
---|---|
Length | 15 weeks |
Effort | 8 - 10 hours per week |
Starts | Aug 20 (293 weeks ago) |
Cost | $0 |
From | GTx via edX |
Instructor | Shabbir Ahmed |
Download Videos | On all desktop and mobile devices |
Language | English |
Subjects | Data Science |
Tags | Data Analysis & Statistics |
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