AI - UCR

AI is about understanding how machines can learn, reason, and make decisions and what that means for us. You’ll explore the philosophical foundations of artificial intelligence, dive into the logic and mathematics behind algorithms, and study how AI systems plan, optimize, and learn through experience. From ethical questions to real-world applications, this field equips you to think critically about both the potential and the limitations of intelligent systems.

Opening up AI courses

Easily explore the world of AI, as all 100-level courses, and some 200-level courses are open to anyone. For the remainder of the 200-level courses, and the 300-level courses, you need to first take the Introduction to Programming & Computer Science gateway.

Courses in AI

Gateway

Introduction to Programming

Introduces programming and computer science. Covers structured programming, data constructs, testing, debugging and object‑oriented programming with Python, and develops computational problem‑solving skills.

100-level

AI & Philosophy

Explores philosophical foundations and implications of AI. Examines the history of AI, ethical issues like interpretability, bias and alignment, debates about AI consciousness and implications for human nature.

200-level

Logic & Discrete Mathematics

This course is about the mathematics of decision-making. Unlike fields like algebra or calculus, discrete mathematics deals with things you can count – like whole numbers, steps in a process, or connections in a network. It’s the math of logic, patterns, and structure. These are widely applicable concepts, but we will mostly focus on computer science and the construction of algorithms.

200-level

Decision-Making in AI

The course focuses on planning. It introduces various techniques for AI systems to achieve goals by taking actions in a structured sequence, considering both deterministic and non-deterministic environments. The course covers classical algorithms, the challenges of handling uncertainty, and the complexity of partial observability in decision-making. It also explores planning with resources and how AI systems can optimize their behavior to handle real-world constraints and diverse situations.

300-level

Optimization Methods in AI

Considerable part of AI is about computational methods which aim to achieve the best expected outcome for search problems in complex and adversarial environment. Topics of this course include uninformed and informed search in discrete and completely known environments, local and global search methods in unknown and continuous environments, games played in adversarial environments and constraint satisfaction problems.

300-level

Reinforcement Learning

Reinforcement learning explores how agents such as robots or game AIs can learn through trial and error. In this course, we discuss the fundamental theoretical framework for reinforcement learning as well as various classical learning algorithms. We also study some of the most important recent algorithms that involve neural networks. Students implement many of these algorithms and build agents that can solve complex tasks.

Also consider these options:

Data Science & Intelligent Systems

The other fields within the Data Science & Intelligent Systems cluster.

Data Science & Intelligent Systems

Explore Cognitive Science!

To better understand the human mind that inspires intelligent machines.

Cognitive Science

Explore Heritage, Art & Museums!

To discover how technology can preserve the past and enrich cultural experiences.

Heritage, Art & Museums

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The UCR Program Builder is designed to help you easily plan your academic program. Step by step, the tool guides you through selecting courses, building a balanced curriculum, and meeting UCR’s academic requirements.

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The UCR Program Builder is designed to help you easily plan your academic program. Step by step, the tool guides you through selecting courses, building a balanced curriculum, and meeting UCR’s academic requirements.

Try the Program Builder

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Opening up AI courses

Courses in AI

Courses in AI

Introduction to Programming

Introduction to Programming

AI & Philosophy

AI & Philosophy

Logic & Discrete Mathematics

Logic & Discrete Mathematics

Decision-Making in AI

Decision-Making in AI

Optimization Methods in AI

Optimization Methods in AI

Reinforcement Learning

Reinforcement Learning

Also consider these options:

Also consider these options:

Data Science & Intelligent Systems

Data Science & Intelligent Systems

Explore Cognitive Science!

Explore Cognitive Science!

Explore Heritage, Art & Museums!

Explore Heritage, Art & Museums!