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

Machine Intelligence Track - Prior to Fall 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.

Required Courses

All track requirements, regardless of department, must be completed with a grade of C or higher.

The track has four required courses that provide general background

Course Title
CS 37300 Data Mining and Machine Learning
CS 38100 Introduction to the Analysis of Algorithms

CS 47100


CS 47300

Artifical 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


Machine Intelligence Track Pre-requisite Flowchart (PDF)



The track has two electives, chosen from the list below.

Course Title
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 48300 Introduction To The Theory Of Computation
CS 47300 Web Information Search & Management


  • Three credits of a relevant EPICS or independent study project may be used as one elective with track committee approval.
  • Neither CS 471 or CS 473 may be double counted toward the required & elective courses.
Last Updated: Jun 23, 2023 8:29 AM

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