Curriculum

B.S. IN ARTIFICIAL INTELLIGENCE

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Degree Requirements

BSAI majors will take courses in math and statistics, computer science, AI, science and engineering, and humanities and arts. There's also room built into the curriculum for academic exploration via electives. We've included information about how the curriculum breaks down below.

You can learn more about how a typical student may complete this degree on our BSAI Roadmap.

 

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BSAI Curriculum

Math and Statistics Core (7 Courses)

  • Math Foundations of Computer Science (15-151)
    If not available, 21-127: Concepts of Mathematics can be substituted.
  • Differential and Integral Calculus (21-120)
  • Integration and Approximation (21-122)
  • Matrices and Linear Transformations (21-241)
  • Calculus in Three Dimensions (21-259)
  • Probability Theory for Computer Scientists (36-218)
  • Modern Regression (36-401)

Computer Science Core (5 Courses plus Freshman Immigration Course)

  • Freshman Immigration Course (07-128)
  • Principles of Imperative Computation (15-122)
  • Principles of Functional Programming (15-150)
  • Parallel and Sequential Data Structures and Algorithms (15-210)
  • Introduction to Computer Systems (15-213)
  • Great Theoretical Ideas in Computer Science (15-251)

Artificial Intelligence Core (3 Courses)

  • Introduction to AI: Representation and Problem Solving (15-281)
  • Introduction to Machine Learning (10-315)
  • Take one of the following courses:
    • Introduction to Natural Language Processing (11-411)
    • Introduction to Computer Vision (16-385)

Humanities and Arts

BSAI students take seven courses in the humanities and arts as part of the SCS General Education requirements. Of the seven Humanities and Arts courses in the curriculum, one must be in cognitive science or cognitive psychology. Examples include:

  • Cognitive Psychology (85-211)
  • Human Information Processing and Artificial Intelligence (85-213)
  • Perception (85-370)
  • Human Memory (85-390)
  • Visual Cognition (85-408)
  • Language and Thought (85-421)

AI Cluster Electives (4 Courses)

Take one course from each of the following areas:

Decision Making and Robotics Cluster

  • Neural Computation (15-386)
  • Autonomous Agents (15-482)
  • Cognitive Robotics (15-494)
  • Planning Techniques for Robotics (16-350)
  • Mobile Robot Programming Laboratory (16-362)
  • Robot Kinematics and Dynamics (16-384)

Machine Learning Cluster

  • Deep Reinforcement Learning and Control (10-403)
  • Machine Learning With Large Datasets (10-405)
  • Deep Learning Systems: Algorithms and Implementation (10-414)
  • Intermediate Deep Learning (10-417)
  • Machine Learning for Structured Data (10-418)
  • Foundations of Learning, Game Theory, and Their Connections (10-422)
  • Generative AI (10-423)
  • Bayesian Methods in Machine Learning (10-424)
  • Introduction to Convex Optimization (10-425)
  • Machine Learning for Text and Graph-based Mining (11-441)
  • Introduction to Deep Learning (11-485)
  • Advanced Methods for Data Analysis (36-402)

Perception and Language Cluster

  • Search Engines (11-442)
  • Speech Processing (11-492)
  • Computational Perception (15-387)
  • Computational Photography (15-463)
  • Vision Sensors (16-421)

Human-AI Interaction Cluster

  • Design of Artificial Intelligence Products (05-317)
  • Human-AI Interaction (05-318)
  • Designing Human-Centered Software (05-391)
  • Human-Robot Interaction (16-467)

Ethics Elective (One Course From the Following)

  • Artificial Intelligence and Humanity (16-161)
  • Ethics and Robotics (16-735)
  • Ethics and Policy Issues in Computing (17-200)
  • AI, Society and Humanity (80-249)

SCS Electives

BSAI students take two electives within the School of Computer Science. Students who take two of the major-intro mini-courses (02-18005-18007-180, or 15-180) during their first year may combine these two mini-courses together to count as one SCS elective.

Science and Engineering

BSAI students take four courses in science and engineering as part of the SCS General Education requirements.