Computer Science Concentration - Machine Intelligence Track (MI)

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Objectives:

The track is designed to prepare students to work in fields related to management and analysis of data, including areas such as machine learning, information retrieval, and data mining. The track is designed to prepare students to understand, and effectively apply in practice, the principles and techniques of data and knowledge representation, search, as well as learning and reasoning with data.

Required Courses (4 Courses)

Electives (2 Courses)

CS 31400 - Numerical Methods
CS 34800 - Information Systems
CS 35200 - Compilers: Principles And Practice
CS 44800 - Introduction To Relational Database Systems
CS 45600 - Programming Languages
CS 47100 - Introduction to Artificial Intelligence
CS 47300 - Web Information Search And Management
CS 48300 - Introduction To The Theory Of Computation
CS 49000 - Topics In Computer Sciences For Undergraduates
• HCI Human Computer Interactions

• LDA Large-Scale Data Analysis

• IDV Intro to Data Visualization
CS 57700 - Natural Language Processing
CS 57800 - Statistical Machine Learning

Notes

All track requirements, regardless of department, must be completed with a grade of C or higher.
No course can be counted both for required and elective.

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Computer Science Concentration - Machine Intelligence Track (MI)

Required Courses (4 Courses)

Electives (2 Courses)

Notes