Course Catalog
Section G · College-Preparatory ElectiveUC Honors · +1.0 GPA
Introduction to Artificial Intelligence Honors: Informatics
UC A-G approved Introduction to Artificial Intelligence Honors: Informatics course delivered fully online through immersive VR and AI-enhanced instruction.
1/2 Year Online · Remote / Hybrid / In-Person Mathematics - Computer Science Grades 9, 10, 11, 12 5 credits
Section GUC A‑G Requirement
College-Preparatory Elective — 1 year required
Must be chosen from additional courses in categories A–F (beyond the minimum requirements) OR from other UC-approved college-preparatory electives, including computer science, business, statistics, and interdisciplinary STEM courses.
UC Honors Designation
AP and IB electives earn 1 extra weighted GPA point. Some G electives (Statistics, Computer Science) satisfy UC quantitative reasoning requirements.
Why This Matters for College Admission
G electives are where students develop depth and signal academic passion. AI, cybersecurity, data science, and entrepreneurship courses are highly competitive differentiators for tech-oriented admissions profiles.
What You'll Learn
Develop computational thinking skills: decomposition, abstraction, and algorithms
Write, debug, and document code in industry-relevant programming languages
Understand data structures, sorting algorithms, and complexity analysis
Apply mathematics (discrete math, statistics, or calculus) to computing problems
Build working software projects with version control and collaborative workflows
Explore career pathways in software engineering, data science, and AI/ML
Course Structure
Unit 1Weeks 1–4
Foundations & Context
- Core vocabulary and concepts
- Skill baseline assessment
Unit 2Weeks 5–9
Core Content
- Primary content delivery
- Applied practice activities
Unit 3Weeks 10–14
Application & Synthesis
- Real-world application
- Final project or exam prep
Curated syllabus · 6 units · 60 videos
Introduction to Artificial Intelligence Honors: Informatics: study order
Six units covering the Russell-Norvig sequence: search, adversarial games, knowledge representation, probabilistic reasoning, basic ML, and modern AI. Spine: UC Berkeley CS188 + Stanford CS221.
Overview
Khan Academy
Also see(2 more picks)
Specialist
Specialist
Search 1 - Dynamic Programming, Uniform Cost Search | Stanford CS221: AI (Autumn 2019)Stanford Online
Also see(3 more picks)
Free-Response / Exam
Also see(1 more pick)
Overview
Khan Academy
Also see(2 more picks)
Specialist
Specialist
JavaScript Tic Tac Toe Project Tutorial - Unbeatable AI w/ Minimax AlgorithmfreeCodeCamp.org
Also see(3 more picks)
Specialist
Game Playing 1 - Minimax, Alpha-beta Pruning | Stanford CS221: AI (Autumn 2019)Stanford Online
Free-Response / Exam
Free-Response / Exam
Python Checkers AI Tutorial Part 1 - The Minimax Algorithm ExplainedTech With Tim
Also see(1 more pick)
Free-Response / Exam
C++/Game Tutorial 40: AI for Tic-Tac-Toe with Minimax AlgorithmMakingGamesWithBen
Curated for Introduction to Artificial Intelligence Honors: Informatics. Videos open in YouTube's privacy-enhanced (nocookie) embed; cookies are blocked until you click.
Prerequisites & Requirements
Open to qualifying students in grades 9, 10, 11, 12; no prerequisites required
All students complete a placement conversation with our admissions team before enrollment is confirmed. Questions? Contact admissions.