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Master’s Degree in Computer Science

Offered By: The University of Texas at Austin via edX

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Computer Science Courses Artificial Intelligence Courses Machine Learning Courses Reinforcement Learning Courses Linear Algebra Courses Algorithms Courses

Course Description

Overview

Texas is consistently listed as a top-ten university for computer science by U.S. News. The University has now made it possible to combine that top-tier reputation with the flexibility of online study through the new Master of Science in Computer Science Online. The program’s rigorous curriculum is based on UT’s on-campus degree, ensuring that you will receive the elite quality of instruction that defines a UT education.

You will be able take classes in a flexible format that gives you the ability to pursue your educational goals in the manner most consistent with your career goals. The Master’s degree you receive at the end of your studies will be indistinguishable from its on-campus counterpart (will not say online) at only a fraction of the on-campus program costs.

Our graduates will enjoy access to world-class professors, a professional network of talented peers from across the globe, and a degree that will enable you to pursue career opportunities from one of the most in-demand fields in the modern economy.


Syllabus

The curriculum incorporates foundational coursework that provides a broad understanding of the field and elective coursework on subject matter that is in high demand within industry that will allow students to tailor their studies to their own interests.

This is a 30-hour program with 9 hours of required courses and 21 hours of electives. Elective courses are opportunities to specialize in areas such as advanced systems design, machine learning and artificial intelligence.

Required Courses:
One class is required from each of the following course categories:

  • Applications: Machine Learning, Reinforcement Learning: Theory and Practice, Linear Algebra
    • Systems: Advanced Operating Systems, Parallel Systems
    • Theory: Algorithms: Techniques and Theory

Elective Courses:

  • Optimization, Deep Learning, Online Learning and Optimization

Note: Any course can be counted towards Elective hours once the required course requirements are met.


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