Artificial Intelligence, BSE

The rapid rise of big data, machine learning, and artificial intelligence have resulted in tremendous breakthroughs that are having horizontal impact across many disciplines, in engineering, computing and beyond. The need for cutting edge AI engineers is tremendous, as are the research and innovation opportunities in this rapidly evolving field. Above all there is tremendous potential for having a positive societal impact in numerous applications domains (health, energy, transportation, robotics, computer vision, human machine interfaces, national security) in addition to networks and society.


Artificial Intelligence (ARIN) Major Requirements

37 course units are required.

CIS 1100Introduction to Computer Programming1
CIS 1200Programming Languages and Techniques I1
CIS 1210Programming Languages and Techniques II1
CIS 2450Big Data Analytics1
CIS 3200Introduction to Algorithms1
Math and Natural Science
MATH 1400Calculus, Part I1
MATH 1410Calculus, Part II1
or MATH 1610 Honors Calculus
CIS 1600Mathematical Foundations of Computer Science1
ESE 2030Linear Algebra with Applications to Engineering and AI1
ESE 3010Engineering Probability1
or STAT 4300 Probability
ESE 4020Statistics for Data Science1
or ESE 5420 Statistics for Data Science
Natural Science elective 11
Artificial Intelligence
12 course units, with at least one course unit from each of the following 6 categories. Note that one course cannot satisfy multiple categories, so, e.g., if you take ESE 4210 for Optimization & Control then you must still take another Project course.12
Introduction to AI
Artificial Intelligence
Artificial Intelligence
Artificial Intelligence Lab: Data, Systems, and Decisions
Machine Learning
Applied Machine Learning
Applied Machine Learning
Machine Learning
Signals & Systems
Introduction to Dynamic Systems
Signal and Information Processing
Optimization & Control
Introduction to Optimization
Control For Autonomous Robots
Vision & Language
Natural Language Processing
Natural Language Processing
Computer Vision & Computational Photography
Computer Vision & Computational Photography
AI Project
Software Design/Engineering
Natural Language Processing
Natural Language Processing
Computer Vision & Computational Photography
Computer Vision & Computational Photography
Deep Learning: A Hands-on Introduction
TinyML: Tiny Machine Learning for Embedded Systems
Control For Autonomous Robots
Scalable and Cloud Computing
Crowdsourcing and Human Computation
AI Electives
Remaining course units from any of the six categories above, or any of the following:
Machine Learning Electives
Mathematics of Machine Learning
Advanced Topics in Machine Learning
Theory of Machine Learning
Machine Learning for Time-Series Data
Machine Learning for Time-Series Data
Graph Neural Networks
Principles of Deep Learning
Deep Generative Models
Information Theory
Optimization, Systems, and Control Electives
Stochastic Systems Analysis and Simulation
Linear Systems Theory
Feedback Control Design and Analysis
Introduction to Optimization Theory
Modern Convex Optimization
Combinatorial Optimization
Learning for Dynamics and Control
Model Predictive Control
Other AI Electives
Brain-Computer Interfaces
Introduction to Human Computer Interaction
Introduction to Human Computer Interaction
Database and Information Systems
Database and Information Systems
Fundamentals of Computational Biology
Machine Perception
Advanced Topics in Databases
Introduction to Robotics
Advanced Robotics
Engineering Markets
F1/10 Autonomous Racing Cars
Learning in Robotics
Theory of Networks
Algorithmic Game Theory
Senior Design
CIS 4000Senior Project1
or ESE 4500 Senior Design Project I - EE and SSE
or MEAM 4450 Mechanical Engineering Design Projects
or BE 4950 Senior Design Project
or MSE 4950 Senior Design
or CBE 4000 Introduction to Product and Process Design
CIS 4010Senior Project1
or ESE 4510 Senior Design Project II - EE and SSE
or MEAM 4460 Mechanical Engineering Design Projects
or BE 4960 Senior Design Project
or MSE 4960 Senior Design
or CBE 4590 Product and Process Design Projects
Technical Electives
Three course units from Engineering, Math or Natural Science or listed at 23
General Electives 3
AI Ethics Elective
CIS 4230Ethical Algorithm Design1
or CIS 5230 Ethical Algorithm Design
or LAWM 5060 ML: Technology Law
Cognitive Science Elective
Select one of the following Cognitive Science electives:1
Introduction to Cognitive Science
Introduction to Formal Linguistics
Introduction to Syntax
Semantics I
Introduction to Logic
Introduction to Philosophy of Mind
Logic and Computability 1
Philosophy of Psychology
Introduction to Brain and Behavior
Cognitive Neuroscience
Language and Thought
Judgment and Decisions
Select 3 Social Science or Humanities courses3
Select 2 Social Science or Humanities or Technology in Business & Society courses2
Free Elective
Select 1 course unit of free elective.1
Total Course Units37

The Natural Science elective can be satisfied with appropriate AP credits, e.g., AP Physics. (a list of approved Natural Science course can be found on the SEAS UG Handbook)


May contain at most one CU of 1000-level courses.


Must include a Writing Seminar (a list of approved Writing Seminars can be found in the SEAS Undergraduate Handbook).

The degree and major requirements displayed are intended as a guide for students entering in the Fall of 2024 and later. Students should consult with their academic program regarding final certifications and requirements for graduation.