Track 1
Introduction to Computer Science
An introductory course designed for high school students with no prior programming experience. Using Python, students will explore the power of computing through creative problem-solving and hands-on program design. The curriculum emphasizes technical communication alongside core engineering principles.
Key Learning Outcomes:
★ Functional Decomposition: Breaking complex tasks into manageable
subtasks.
★ Data Structures: Mastering common types including integers, booleans,
strings, and lists.
★ Control Structures: Implementing logic through conditionals and loops.
★ Professional Skills: Developing technical writing and presentation abilities.
Track 2
Introduction to AI
(Description awaiting)
Track 3
Gen AI
This course introduces the foundations and modern techniques of Generative AI. It is adapted from existing UCLA CS courses, including CS146 (Machine Learning) and CS162 (Natural Language Processing), and extends beyond them to cover emerging topics in generative modeling.
The course provides an introduction to a wide range of generative AI tasks, including language generation, mathematical reasoning, and multimodal generation, and discusses foundational algorithms and methods such as neural networks, representation learning, and large language models. Students will learn the machine learning principles that enable generative systems to learn from large-scale data and produce coherent, structured outputs.
Class lectures will discuss general concepts as well as present abstract algorithms and implementations. Homework assignments will cover both theoretical foundations and practical applications, allowing students to build and experiment with generative models.
Track 4
Internet of Things: Connectivity & Sensing
This 3-week course is designed to give students a hands-on introduction on Internet of Things (IoT) technologies focusing on connectivity and sensing aspects. Lectures will be held each weekday morning by instructors.
Afternoons consist of lab work with teaching assistants, providing students the opportunity to reinforce lecture concepts through coding exercises and small-scale experiments with both hardware and software.
The course culminates in the final week with a capstone project, where students will design, build, and analyze a fully functional IoT system that leverages both hardware and software skills learned throughout the program.
