Undergraduate | Artificial Intelligence (AI) Program

Undergraduate | Artificial Intelligence (AI) Program
Artificial Intelligence
B.S.E. in AI Curriculum
Curriculum
The AI degree provides the mathematical and algorithmic foundations of AI techniques, along with hands-on experience in programming as well as using AI tools and foundation models. Complementing these engineering skills with a broader perspective, students learn about intelligence from a cognitive science perspective, and they develop a sense of the issues (and solutions) required to responsibly develop AI to benefit society.  Finally, students choose a concentration, ranging from machine learning, to vision and language, to data and society, to robotics, to AI and health systems. Interested students can learn more about the courses below by visiting the
Penn Course Catalog
MATH 1400: Calculus, Part I
MATH 1410: Calculus, Part II
CIS 1600: Mathematics of Computer Science
ESE 2030: Linear Algebra with Applications to Engineering and AI
ESE 3010: Probability or STAT 4300
ESE 4020: Statistics for Data Science
Natural science [1 CU, no lab requirement]
CIS 1100: Python Programming
CIS 1200: Programming Languages
CIS 1210: Data Structures
CIS 3200: Algorithms
CIS 2450: Big Data
Students choose at least one course unit from each of the following six categories:
Introduction to AI
ESE 2000: Data, Systems, Decisions
CIS 2210: Introduction of Artificial Intelligence
Or CIS 4210 Artificial Intelligence
Or CIS 5210 Artificial Intelligence
Machine Learning
CIS 4190: Applied Machine Learning
CIS 5200: Machine Learning
Signals & Systems
ESE 2100: Dynamic Systems
ESE 2240: Signal and Information Processing
Optimization & Control
ESE 3040 Optimization
ESE 4210 Control For Autonomous Robots
Vision & Language
CIS 5810: Computer Vision & Computational Photography
CIS 5300: Natural Language Processing
AI Project
(must have AI development, 30% of grade from term project)
ESE 3060: Deep Learning: A Hands-on Introduction
CIS 3500: Software Engineering
ESE 3600: Tiny Machine Learning
ESE 4210: Control for Autonomous Robots
CIS 5810: Computer Vision & Computational Photography
CIS 5300: Natural Language Processing
NETS 2120: Scalable and Cloud Computing
NETS 2130: Crowd Sourcing and Human Computation
In addition to the courses above, students will have an opportunity to take six AI courses selected from the list of approved courses below, along with the 1-year senior design sequence:
Machine Learning Electives
CIS 3333: Mathematics of Machine Learning
ESE 5460: Principles of Deep Learning
ESE 5140: Graph Neural Networks
ESE 4380: Machine Learning for Time-Series Data
ESE 6450: Deep Generative Models
CIS 6200: Advanced Deep Learning
CIS 6250: Computational Learning Theory
ESE 6740: Information Theory
CIS 7000: Trustworthy AI
Optimization, Systems, and Control Electives
ESE 3030: Stochastic Systems Analysis and Simulation
ESE 5000: Linear Systems Theory
ESE 5050: Control Systems
ESE 5060: Linear Optimization
ESE 6050: Modern Convex Optimization
ESE 6060: Combinatorial Optimization
ESE 6190: Model Predictive Control
ESE 6180: Learning for Dynamics and Control
Other AI Electives
MEAM 4600: AI for Science and Engineering: From Data to Discovery
MEAM 5200: Robotics
MEAM 6200: Advanced Robotics
ESE 6500: Learning in Robotics
ESE 6150: F1/10 Autonomous Racing Cars
ESE 6510: Physical Intelligence: Science and Systems
CIS 4120: Human-Computer Interaction
CIS 5800: Machine Perception
CIS 5360: Computational Biology
BE 5210: Brain Computer Interfaces
CIS 4500: Databases
CIS 6500: Advanced Topics Databases
NETS 3120: Theory of Networks
NETS 4120: Algorithmic Game Theory
ESE 4040: Engineering Markets
The above list will evolve as new courses are added to the program.
The six AI elective courses can be structured along AI concentrations depending on the interests of the student. Concentrations are optional and consist of four courses in a specific theme. Only courses used in the AI Elective category may be counted towards a concentration.
Robotics:
ESE 4210: Control for Autonomous Robots
MEAM 5170: Control & Optimization with Applications to Robotics
MEAM 5200: Introduction to Robotics
ESE 6150: F1/10 Autonomous Racing Cars
MEAM 6200: Advanced Robotics
MEAM 6230: Learning & Control for Adaptive & Reactive Robots
MEAM 6240: Distributed Robotics
ESE 6500: Learning in Robotics
Machine Learning:
ESE 4230: Ethical Algorithm Design
ESE 4380: Machine Learning for Time-series Data
ESE 5140: Graph Neural Networks
ESE 5460: Principles of Deep Learning
CIS 6200: Advanced Topics in Machine Learning
CIS 6250: Theory of Machine Learning
Vision & Language:
CIS 4810: Computer Vision & Computational Photography
CIS 5300: Natural Language Processing
CIS 5800: Machine Perception
CIS 6800: Advanced Topics in Machine Perception
CIS 6300: Advanced Topics in Natural Language Processing
ESE 6450: Deep Generative Models
Rather than offering a specific course for senior design, AI majors will embed themselves into the ESE, CIS or other Penn Engineering senior design courses. This will enable AI students to apply their AI skills across many engineering challenges.
Three course units from Engineering, Math, Natural Science or from the list
here
AI Ethics:
Choose at least one of the following
CIS 4230: Ethical Algorithm Design
LAWM 5060: Machine Learning: Technology Law
Cognitive Science Elective:
Choose at least one of the following
COGS 1001: Intro to Cognitive science
LING 0500: Introduction to Formal Linguistics
LING 2500: Introduction to Syntax
LING 3810: Semantics I
PSYC 1210: Introduction to Brain and Behavior
PSYC 1340: Perception
PSYC 1230: Cognitive Neuroscience
PSYC 1310: Language and Thought
PSYC 2737: Judgment and Decisions
PHIL 1710: Introduction to Logic
PHIL 2640: Introduction to Philosophy of Mind
PHIL 4721: Logic and Computability 1
PHIL 4840: Philosophy of Psychology
SS/H Electives:
Five course units, including a writing course. Three of these courses must be Social Science or Humanities courses, and 2 can be Social Science, Humanities, or Technology in Business & Society courses.
Free Elective:
One course unit from free electives.
Frequently Asked Questions
The application for prospective Penn students interested in the Artificial Intelligence Bachelor of Science in Engineering (AI BSE) program for a Fall 2025 start date will open in early August 2024.
For further details regarding the University of Pennsylvania’s admissions procedures, kindly refer to
Yes! Incoming first-year Engineering undergraduate students will be eligible to change their major to Artificial Intelligence. Beginning on August 26, incoming students can start the process by accessing the
Declare/Update Field of Study form
Current Penn Engineering students, including current first- and second-year M&T students are eligible to apply for transferring to the AI major.
These students will need to follow a two-step process:
Submit a 4-year academic plan to
buchkat@seas.upenn.edu
Submit the
Declare/Update Field of Study form
All other students should follow the procedure outlined “
Transfer Into Penn Engineering
” page in the Penn Engineering Undergraduate Student Handbook.
BSE in AI students are permitted to pursue dual-majors within Penn Engineering, with the exception of CSCI, NETS and SSE.
Eligible BSE in AI students are permitted to pursue dual-degree programs or second majors in the College of Arts and Sciences, including the VIPER program. To determine eligibility, please contact
buchkat@seas.upenn.edu
Note that students seeking to declare the AI major must be able to graduate within 8 semesters in total (or 10 semesters for M&T students), otherwise the major change will not be approved.
No, Penn Engineering does not offer undergraduate online programs. The AI program is designed as a residential undergraduate bachelor’s program, emphasizing in-person instruction. For information regarding Penn Engineering’s online graduate degrees at the master’s level, please visit
For details on prerequisites and recommendations when applying to Penn Engineering, please visit the
Office of Admissions
page.
Strong preparation in fundamental subjects, particularly Mathematics, is vital for any Penn Engineering degree program.
Tuition and financial aid policies are university-wide and not specific to individual programs. For more information, please visit
This website will provide the most up-to-date program information. Kindly continue to check back regularly for updates, and be sure to follow Penn Engineering AI on social media.
Yes! Incoming first-year Engineering and M&T undergraduate students will be eligible to change their major to Artificial Intelligence. Beginning on August 26, incoming students can start the process by accessing the
Declare/Update Field of Study form