Program Overview

Introduction to the 6-4 Program: Artificial Intelligence and Decision Making

The 6-4 program in Artificial Intelligence and Decision Making is designed to teach students techniques for the analysis and synthesis of systems that interact with an external world via perception, communication, and action, and that learn, make decisions, and adapt in a changing environment. This major integrates disciplines typically taught in different departments, including electrical engineering, computer science, statistics, operations research, and brain and cognitive sciences.

Program Requirements

To complete the 6-4 program, students must fulfill the following requirements:

• One programming skills subject:
  • 6.1000 Introduction to Programming and Computer Science
  • 6.100A 6.0001 Introduction to Computer Science Programming in Python
• Three math subjects:
  • 6.1200 6.042 Mathematics for Computer Science
  • One of 18.C06, 18.06 Linear Algebra
  • One of 6.370 6.041 Introduction to Probability, 6.380 6.008 Introduction to Inference, 18.05 Introduction to Probability and Statistics
• Two foundation subjects:
  • 6.101 6.009 Fundamentals of Programming
  • 6.121 6.006 Introduction to Algorithms
• Five Center subjects:
  • 6.122 6.046 Design and Analysis of Algorithms
  • 6.140 6.045 Computability and Complexity Theory
  • 6.300 6.003 Signal Processing
  • 6.310 6.302 Dynamical System Modeling and Control Design
  • 6.326 6.207 Networks
  • 6.372 6.401 Introduction to Statistical Data Analysis | 6.390 6.036 Introduction to Machine Learning
  • 6.395 6.404 AI, Decision Making, and Society
  • 6.411 6.038 Representation, Inference, and Reasoning in AI
  • 6.412 6.804 Computational Cognitive Science
  • 6.440 6.837 Computer Graphics
  • 6.459 6.805 Foundations of Information Policy | 6.720 16.215
  • 6.7920 Reinforcement Learning: Foundations and Methods
  • 6.C01 Modeling with Machine Learning: from Algorithms to Applications&6.C011 Modeling with Machine Learning for Computer Science
  • 6.C01 Modeling with Machine Learning: from Algorithms to Applications&6.C511 Modeling with Machine Learning for Computer Science
  • 6.C35 Interactive Data Visualization and Society
  • 6.C571 Optimization Methods | 6.S044 AI and Rationality
  • 6.S061 Humane User Experience Design
  • 9.660 Computational Cognitive Science
• Four elective subjects:
  • One from Application CIMCI-M for 6-4 students list
  • AI+D_AUS
  • Two from the EECS All subjects of at least 12 units that satisfy departmental undergraduate requirements in 6-1, 6-2, 6-3, 6-4, or 6-5 list or a Math (course 18) requirement

Additional Constraints

• At least of your completed subjects must be from the CIM2 EECS CI-M subjects list
• At least of your completed subjects must be from the AI+D_SERC Social and Ethical Responsibilities of Computing list
• At least of your completed subjects must be from the Data-centric 6-4 Data-centric subjects list
• At least of your completed subjects must be from the Model-centric 6-4 Model-centric subjects list
• At least of your completed subjects must be from the Decision-centric 6-4 Decision-centric subjects list
• At least of your completed subjects must be from the Computation-centric 6-4 Computation-centric subjects list
• At least of your completed subjects must be from the Human-centric 6-4 Human-centric subjects list

Notes

• If you choose a Math requirement as an elective, it must not have essentially similar content to the other subjects satisfying your 6-4 degree requirements.

Program Overview

The 6-4 program in Artificial Intelligence and Decision Making is a comprehensive undergraduate program that prepares students for careers in AI, decision-making, and related fields. The program is designed to provide students with a strong foundation in programming, mathematics, and computer science, as well as specialized knowledge in AI and decision-making. Students can declare the 6-4 major starting in Fall 2022.