Artificial Intelligence Minor

This minor requires students to have a background that includes collegiate-level mathematics, probability and statistics, and programming course work.  Pre-requisite course work in the following three categories must be completed in order to pursue the minor.  Within each category, each bullet point provides an option for meeting the pre-requisite.  Students need to complete one pre-requisite option/bullet point (NOT all bullet points) in each category to meet the pre-requisite requirements for the minor.

Mathematics up through differential equations or linear algebra

• MATH 225: Linear Algebra and Linear Differential Equations
• MATH 235: Linear Algebra and Applications
• MATH 245: Mathematics of Physics and Engineering I
• EE 141: Applied Linear Algebra for Engineering and [MATH 226: Calculus III or MATH 229: Calculus III for Engineers and Scientists]

Probability and statistics course or sequence

• EE 364: Probability and Statistics for Engineers and Computer Scientists
• ISE 220: Foundations of Probability Modeling and ISE 225: Foundations of Data Analysis
• CE 119: Statistical Data Analysis in Engineering and CE 408: Risk and Decision Analysis in Civil Engineering

Programming fundamentals

• [CSCI 113: Programming Fundamentals for Computing or ISE 150: Solving Engineering Problems using Python] and CSCI 114: Programming for Applications of Computing
• CSCI 103: Object Oriented Programming and CSCI 104: Data Structures
• [TAC 115: Programming in Python or TAC 116: Accelerated Programming in Python or CE 108: Programming for Civil and Environmental Engineers] and TAC 216: Applied Python and [TAC 265: Software Design with Object-Oriented Programming or CSCI 114: Programming for Applications of Computing]

A grade of C or better is required in all pre-requisite course work; courses with grades of C– or below may be retaken only once and only with the corresponding department’s approval.

Students who do not satisfy the pre-requisite requirements for this minor are encouraged to instead consider pursuing the Artificial Intelligence Applications minor from Viterbi’s Technology and Applied Computing (TAC) program.

This minor requires 20 units of course work (not including pre-requisites). At least 16 units must be unique to the minor (i.e., not used to fulfill major requirements or the requirements of another minor) and at least 16 units must be outside of the student's major department.

Required Courses

• CSCI 170: Discrete Methods in Computer Science (4 units)*
• CSCI 360: Artificial Intelligence: Principles and Foundations (4 units)
• EIS 370: Ethical Issues in Artificial Intelligence (4 units)

• EE 460: Machine Learning for Engineers (4 units) OR
• CSCI 467: Foundations of Machine Learning (4 units)

Elective Course

Choose one of the following courses:

• CSCI 444: Language Models in Natural Language Processing (4 units)
• CSCI 445: Foundations of Robotics (4 units)
• CSCI 461: Artificial Intelligence for Sustainable Development (4 units)
• CSCI 468: Trustworthy Artificial Intelligence (4 units)
• CSCI 469: Computer Vision (4 units)
• EE 451: Parallel and Distributed Computation (4 units)
• EE 456: Reinforcement Learning and Applications (4 units)
• EE 461: Machine Learning with Distributed Computing Systems (4 units)
• ISE 325: Modeling for Predictive Analytics (4 units)
• ISE 470: Human/Computer Interface Design (4 units)
• TAC 459: Applied Natural Language Processing and Generative AI (4 units)

* A grade of C or better is required in CSCI 170; students who earn a grade of C- or below may retake the course only once and only with the approval of the Computer Science Department.

To learn more about the Artificial Intelligence minor or to declare the minor, contact Viterbi Student and Academic Services by email at vaseug@usc.edu or by opening a referral to the minor in Advise USC.