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Section G · College-Preparatory Elective UC Honors · +1.0 GPA

Artificial Intelligence & Machine Learning Honors

UC A-G approved Artificial Intelligence & Machine Learning Honors 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 Elective1 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

Artificial Intelligence & Machine Learning Honors: study order

G · Electives (Honors, ½ year)· One-semester honors course · 2025–26Reference

Six fast-paced units covering classical ML through neural networks, tracking the canonical Andrew Ng + 3Blue1Brown + StatQuest sequence.

Overview

Khan Academy

Also see(2 more picks)

Specialist

Also see(3 more picks)

Specialist
1.1.3 Supervised Learning by Andrew Ng

Computer Science Engineering

Specialist
A Gentle Introduction to Machine Learning

StatQuest with Josh Starmer

Free-Response / Exam

Free-Response / Exam
All Machine Learning algorithms explained in 17 min

Infinite Codes

Also see(1 more pick)

Free-Response / Exam
All Machine Learning Models Clearly Explained!

AI For Beginners

Practice on Khan Academy

Khan Academy

Also see(2 more picks)

Khan Academy
Linear Regression in 3 Minutes

3-Minute Data Science

Khan Academy
Linear Regression, Clearly Explained!!!

StatQuest with Josh Starmer

Free-Response / Exam

Also see(1 more pick)

Free-Response / Exam
How To... Perform Simple Linear Regression by Hand

Eugene O'Loughlin

Practice on Khan Academy

Curated for Artificial Intelligence & Machine Learning Honors. 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.

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