Computer Science Courses & Certificates

Technology is evolving faster than ever—and so should your skills. Our newly reimagined computer science area of study can equip you with the tools to thrive in today’s data-driven, AI-powered world.

Whether you're launching a new career or leveling up your current one, our programs are designed to meet the demands of the modern tech landscape. Learn from industry experts through hands-on, project-based courses that blend theory with real-world application.

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Build the future. One line of code at a time.

Explore our key focus areas:

Software Development & Programming
Master the languages, frameworks, and tools that power today’s most in-demand applications—from web and mobile to enterprise systems.

Machine Learning & Artificial Intelligence
Dive into the world of intelligent systems. Learn how to build, train, and deploy models that drive innovation across industries.

Data Analytics & Infrastructure
Gain the skills to collect, manage, and analyze data at scale. From pipelines to predictive analytics, turn raw data into actionable insights.

Cybersecurity, Cloud, and Emerging Tech
Stay ahead of the curve with courses in cybersecurity, cloud computing, blockchain, and more.

Why Choose UCLA Extension?

Flexible online and hybrid formats
Taught by working professionals in the field
Career-focused certificates and specializations
Open enrollment—no formal application required

Computer Science

Courses

Exploratory Data Analysis and Visualization

Learn the iterative process of exploratory data analysis (EDA), data analysis techniques, data exploration, and visualization. Course tools include R for data analysis and Tableau for data visualization.

Foundations of Generative AI

This course introduces generative AI through theory and hands-on practice, covering model evolution, practical techniques, and ethical frameworks to build, refine, and evaluate systems in real-world contexts.

Full Stack Web Development

Fundamentals of AI in Finance

This course covers AI fundamentals in finance, Python basics, financial libraries (Numpy, Pandas, etc.), and SQL. It includes machine learning concepts, supervised/unsupervised learning, reinforcement learning, and algorithmic trading, concluding with a real-world case study application.

Fundamentals of Artificial Intelligence

Intro to AI problem-solving and knowledge representation using Lisp. Covers search strategies, planning, logic structures, and applications in NLP, expert systems, and vision. Includes lectures, labs, and programming assignments.