Machine Intelligence Track 2019 - Department of Computer Science - Purdue University Skip to main content

Machine Intelligence Track 2019


The track is designed to prepare students to work in fields related to analysis of data, including areas such as machine learning, artificial intelligence, 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.

All CS core courses, all track requirements, and their pre-requisites, regardless of department, must be completed with a grade of C or better.


Required Courses (4)
Course Title
CS 37300 Data Mining and Machine Learning
CS 38100 Introduction to the Analysis of Algorithms

CS 47100


CS 47300

Artificial Intelligence


Web Information Search & Management

STAT 41600


MA 41600


STAT 51200





Applied Regression Analysis

NOTE: Students considering graduate work or research in this area are encouraged to take STAT/MA 41600 and STAT 41700 

Electives (2)
Course Title
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 & Management
CS 48300 Introduction To The Theory Of Computation

CS 49000-HCI


CS 49000-LDA


CS 49000-IDV

Human-Computer Interactions


Large-Scale Data Analysis


Introduction to Data Visualization

CS 57700 Natural Language Processing
CS 57800 Statistical Machine Learning

Note: Three credits of a relevant EPICS or independent study project may be used as one elective with approval from the track chair.

Note: No course can be counted both for required and elective credit. This is true for all tracks. 

Last Updated: Jun 23, 2023 8:22 AM

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