The Artificial Intelligence: Theory, Methods, and Applications (AITMA) minor offered by the Department of Electrical and Computer Engineering provides students with a rigorous, engineering-focused foundation in AI. The minor integrates AI theory, methods, and applications, giving students a comprehensive understanding of the field. AI theory explains how intelligence can be modeled, AI methods provide the algorithms and techniques that make these models work, and AI applications allow students to implement these algorithms in real-world contexts. Students gain the skills to analyze, design, and apply AI across a wide range of systems and sectors, including embedded devices, robotics, IoT, machine vision, healthcare, finance, retail, manufacturing, agriculture, sustainability, transportation, and cybersecurity.

Requirements 

The minor requires 15 semester hours (s.h.).

  • In addition to the required course, students must complete electives from at least two of the following categories: Theory, Methods, and Applications.
  • Optionally, students may count one elective from the Support category.
  • Students may count one AI-related course that is not an ECE or ENGR course towards the minor.
  • Through choice of electives, students can tailor the minor to align with their academic interests and career goals.

Required core courses (3 sh):

  • ENGR:3110 Intro to AI & Machine Learning in Engr1, P: ENGR:13002, C: MATH:25503

Theory:

  • ECE:5200 (previously ECE:5450) Machine Learning
  • ECE:5225 (previously ECE:5455) Statistical Foundations of Inference and Machine Learning
  • ECE:5240 Deep Learning Theory

Methods:

  • ECE:5215 Applied Machine Learning
  • ECE:5250 Large Language Models
  • ECE:5485 Intelligent Vision and Image Understanding
  • Other: AI methods course from another department, approved by ECE Undergraduate Committee

Applications:

  • ECE:5230 Generative AI Tools: ChatGPT and Beyond
  • ECE:5290 Artificial Intelligence: Experiential Learning
  • ECE:5550 Internet of Things
  • ECE:5830 Software Engineering Project
  • ECE:5845 Modern Databases
  • Other: AI applications course from another department, approved by ECE Undergraduate Committee

Support:

  • ECE:5320 High Performance Computer Architecture
  • ECE:5420 Power Systems and Renewable Energy
  • CS:3980 Topics in Computer Science I: Ethics in Artificial Intelligence
  • AI Ethics course
  • Upper-level Probability course4

Notes

  1. ENGR:3110 may be replaced by a 5000-lvl ECE theory, method, or application course.
  2. Majors that do not require a programming course may count ENGR:1300 Introduction to Engineering Computing towards the minor.

  3. Majors that do not require a matrix algebra course may count one of the following as their support course.

    a. MATH:2550 Engineering Matrix Algebra, 2 s.h. (Students will need one additional sh to earn minor.)

    b. MATH:2700 Introduction to Linear Algebra

  4. Majors that do not require a probability course may count one of the following as their support course.

    a. STAT:2020 Probability & Stats for Engr & Phys Sci

    b. STAT:3120 Probability and Statistics

    c. ECE:3995 Introduction to Probability and Statistics

Other requirements

  • Students must earn a GPA of at least 2.00 in all coursework applied to the minor.
  • No course taken Pass/Nonpass may be used toward the minor.
  • Enrollment in some courses for the minor may require prerequisites that will not count toward the minor.
  • Students must be enrolled as degree-seeking undergraduates at the University of Iowa to pursue the minor.
  • A maximum of 3 s.h. of transfer credit will be accepted toward minor.