Machine Intelligence Track - Prior to Fall 2019

Objectives

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 or CS 47300	Artifical Intelligence or Web Information Search & Management
STAT 41600 or MA 41600 or STAT 51200	Probability or Probability or 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)

 

Electives

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

Notes:

• 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.