AI and Machine Learning Courses for Jacobs School Undergraduates

The Jacobs School of Engineering is pleased to provide this course guide to Artificial Intelligence (AI) and Machine Learning (ML) courses for undergraduate engineering majors.

AI and ML tools and techniques are increasingly essential in today’s engineering research and industry settings. The use of AI and ML concepts, modeling, techniques and tools is driven by a need to understand large data streams in order to guide decisions, predict outcomes, and make recommendations. AI and ML skills are critical to realizing the promise of precision medicine, drug discovery, materials design, autonomous transportation, and environmental management and smart grids to name just a few. More and more employers are looking for engineering graduates who understand how to use AI and Machine Learning skills for engineering applications.

Our goal is to give every engineering major the opportunity to acquire AI and ML concepts, models, techniques and tools as well as to work on a project. We encourage students to consult with their departmental academic advisor on how to incorporate these technical electives into course plans. Full course descriptions and prerequisites are available in the UC San Diego catalog.


Getting Started

Students will be more successful in AI/ML courses if they already have an introduction to Python. Here are two options to consider:

DSC 10. Principles of Data Science (4)

This introductory course includes programming techniques in Python that cover data processing, modeling, and analysis.

EdEx CoursePython for DataScience

This free course has been designed by UC San Diego computer science and engineering professors. This course will help you learn Python tools, including Pandas, Git and Matplotlib, to manipulate, analyze, and visualize complex datasets.


AI/ML Courses for Engineering Majors

Bioengineering

BENG 100: Statistical Reasoning for Bioengineering Applications

Computer Science and Engineering

CSE 150A: Introduction to Artificial Intelligence: Probabilistic Reasoning and Decision Making
CSE 150B: Introduction to Artificial Intelligence: Search and Reasoning
CSE 151A: Introduction to Machine Learning

Electrical and Computer Engineering

ECE 175A: Elements of Machine Intelligence: Pattern Recognition and Machine Learning
ECE 175B: Elements of Machine Intelligence: Probabilistic Reasoning and Graphical Models

Mechanical and Aerospace Engineering

MAE 146: Introduction to Machine Learning Algorithms (under development)
MAE 145: Introduction to Robotic Planning and Estimation

NanoEngineering

NANO 181: Data Science in Materials Science (under development)

Structural Engineering

SE 132: Machine Learning for Structural Engineering (under development)


Advanced Courses

CSE 151B: Deep Learning
CSE 156: Statistical Natural Language Processing
CSE 158: Web Mining and Recommender Systems
ECE 176: Introduction to Deep Learning and Applications