INET 4062: Data Science II: Advanced

4 Credits

This course is a follow-up to INET 4061: Data Science Fundamentals. It covers the tools required to apply and implement data science techniques such as mathematical programming libraries, cloud resources, and big data databases. It also gives an overview of advanced data science methodologies such as deep learning, reinforcement learning, recommendation systems, and linear programming. Previously offered as INET 4710. prereq: Basic programming knowledge (Java, Python, R). Linear algebra and calculus strongly recommended (e.g. MATH 2243 and 2263). INET 4061 strongly recommended.

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B+ Average (3.367)Most Common: A- (50%)

This total also includes data from semesters with unknown instructors.

10 students
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