Program Overview

Artificial Intelligence and Decision Making (Course 6-4)

The Department of Electrical Engineering and Computer Science offers a Bachelor of Science in Artificial Intelligence and Decision Making. This program is designed to provide students with a comprehensive education in artificial intelligence, decision making, and related fields.

General Institute Requirements (GIRs)

The General Institute Requirements include a Communication Requirement that is integrated into both the HASS Requirement and the requirements of each major. The GIRs for the Bachelor of Science in Artificial Intelligence and Decision Making are as follows:

• Science Requirement: 6 subjects
• Humanities, Arts, and Social Sciences (HASS) Requirement: 8 subjects, with at least two designated as communication-intensive (CI-H) to fulfill the Communication Requirement
• Restricted Electives in Science and Technology (REST) Requirement: 2 subjects, satisfied by 6.1200[J] and 18.C06[J] in the Departmental Program
• Laboratory Requirement: 1 subject, satisfied by 6.1010 in the Departmental Program
• Total GIR Subjects Required for SB Degree: 17
• Physical Education Requirement: swimming requirement, plus four physical education courses for eight points

Departmental Program

The Departmental Program for the Bachelor of Science in Artificial Intelligence and Decision Making requires students to choose at least two subjects in the major that are designated as communication-intensive (CI-M) to fulfill the Communication Requirement. The program consists of the following components:

• Fundamentals: 12 units, chosen from the following subjects:
  • 6.1000: Introduction to Programming and Computer Science
  • 6.100A & 6.100B: Introduction to Computer Science Programming in Python and Introduction to Computational Thinking and Data Science
  • 6.100A & 16.C20[J]: Introduction to Computer Science Programming in Python and Introduction to Computational Science and Engineering
  • 6.1010: Fundamentals of Programming
  • 6.1200[J]: Mathematics for Computer Science
  • 6.1210: Introduction to Algorithms
  • 18.C06[J]: Linear Algebra and Optimization
  • 18.06: Linear Algebra
• Centers: 5 subjects, including one from each area:
  • Data-centric:
    • 6.3720: Introduction to Statistical Data Analysis
    • 6.3900: Introduction to Machine Learning
    • 6.C01 & C011: Modeling with Machine Learning: from Algorithms to Applications and Modeling with Machine Learning for Computer Science
  • Model-centric:
    • 6.3000: Signal Processing
    • 6.3100: Dynamical System Modeling and Control Design
    • 6.4110: Representation, Inference, and Reasoning in AI 1
    • 6.4420[J]: Computational Design and Fabrication
    • 6.4400: Computer Graphics 2
  • Decision-centric:
    • 6.3100: Dynamical System Modeling and Control Design
    • 6.4110: Representation, Inference, and Reasoning in AI 1
    • 6.C571[J]: Optimization Methods 3
  • Computation-centric:
    • 6.1220[J]: Design and Analysis of Algorithms
    • 6.1400[J]: Computability and Complexity Theory
    • 6.4400: Computer Graphics 2
    • 6.C571[J]: Optimization Methods 3
  • Human-centric:
    • 6.3260[J]: Networks
    • 6.3950: AI, Decision Making, and Society
    • 6.4120[J]: Computational Cognitive Science
    • 6.4590[J]: Foundations of Information Policy
    • 6.C35[J]: Interactive Data Visualization and Society
• Communication-intensive in the Major: 1 subject, chosen from the following Application CI-M subjects:
  • 6.4200[J]: Robotics: Science and Systems (CI-M)
  • 6.4210: Robotic Manipulation (CI-M)
  • 6.8611: Quantitative Methods for Natural Language Processing (CI-M)
• Electives: 2 subjects, including one that satisfies a degree requirement in Course 6 or Course 18, and one from the list of AI+D Advanced Undergraduate Subjects
• Social and Ethical Responsibilities of Computing (SERC): 1 subject, chosen from the list of SERC-qualified subjects

AI+D Advanced Undergraduate Subjects

The following subjects are available as electives for the Bachelor of Science in Artificial Intelligence and Decision Making:

• 6.3020[J]: Fundamentals of Music Processing
• 6.3730[J]: Statistics, Computation and Applications
• 6.4210: Robotic Manipulation
• 6.4300: Introduction to Computer Vision
• 6.5151: Large-scale Symbolic Systems
• 6.5831: Database Systems
• 6.5931: Hardware Architecture for Deep Learning
• 6.7411: Principles of Digital Communication
• 6.8371: Digital and Computational Photography
• 6.8611: Quantitative Methods for Natural Language Processing
• 6.8701[J]: Computational Biology: Genomes, Networks, Evolution
• 6.8711[J]: Computational Systems Biology: Deep Learning in the Life Sciences
• 6.8801[J]: Biomedical Signal and Image Processing
• 18.404: Theory of Computation

Social and Ethical Responsibilities of Computing (SERC) Subjects

The following subjects are available to fulfill the Social and Ethical Responsibilities of Computing (SERC) requirement:

• 6.3900: Introduction to Machine Learning
• 6.3950: AI, Decision Making, and Society
• 6.4300: Introduction to Computer Vision
• 6.4590[J]: Foundations of Information Policy
• 6.8611: Quantitative Methods for Natural Language Processing
• 6.C01: Modeling with Machine Learning: from Algorithms to Applications
• 6.C40[J]: Ethics of Computing