Python and AI Honors
Course Description
Introductory honors course blending Python programming with core AI concepts. Students learn essential Python, professional coding practices, AI-assisted coding versus traditional coding, and foundational machine learning ideas—then demonstrate skills in a capstone project.
| Credits | 5 (one semester) |
| UC A–G Area | G — College-Preparatory Elective (confirm on UCOP A–G list) |
| Level & GPA Weight | Honors (weighted; confirm UCOP/district policy) |
| Recommended Grades | G9–11 |
| Prerequisites | Foundational Python programming |
| Textbook | Instructor-provided materials |
Major Units & Topics
- Computing & AI fundamentals; responsible use of AI tools
- Python essentials (syntax, types, control flow, functions)
- Working with libraries & APIs; data handling basics
- AI-assisted coding vs. traditional coding; testing & debugging
- Foundations of machine learning; simple models & evaluation
- Capstone: design, build, and present an applied Python/AI project
Practical Work
- Notebook labs for coding, data handling, and model experimentation
- Mini-projects that integrate Python + AI tooling
- Capstone project (proposal → build → demo)
Technology & Platforms
- Python in Jupyter/Colab; versioned notebooks and reproducible workflows
- Intro libraries (e.g., pandas, matplotlib); optional AI assistants
- Starter datasets and instructor-provided references
Delivery Options
| Model | What’s Included | Live Hours |
|---|---|---|
| Mini-One-on-One | Targeted coaching on Python/AI skills, code reviews, project pacing | Typically 11-12 hours |
| One-on-One | Fully personalized instruction and capstone mentorship | Typically 24 hours |
For current tuition, see the pricing section or contact our team.
Time & Workload Expectations
- Total live session hours: ~22 hours (One-on-one); ~12 hours (Mini-one-on-one).
- Pre-study for Mini-one-on-one: plan an additional ~12 hours of structured pre-study (before live sessions).
- Independent work: ~25–30 hours for assignments, reviewing new material, mini-projects, and studying for quizzes/tests/exams.
- Communication: Q&A and periodic progress updates via email (all models).
- Weekly load depends on the course window (start/end dates). Example:
(22 live hours + 38 independent hours) ÷ 12 weeks ≈ 5 hours/week(Adjust the independent-hours figure to match your model and pacing.)
Grading & Course Policies
| Category | Weight |
|---|---|
| Classwork | 10% |
| Tests/Quizzes | 20% |
| Homework | 30% |
| Project | 20% |
| Final Test | 20% |
- Assignments: due next session unless noted; one-session late accepted with reduced credit.
- Class conduct (for synchronous): active participation, focused device use, photos only with permission.
Additional Notes
- Pacing Guide: Personalized plan based on start/end dates and seasonal schedules.
- Accessibility: Reasonable accommodations available; notify counselor/instructor during onboarding.
- Parent Updates: Progress check-ins available upon request (per FERPA/guardian permissions).
Track Eligibility (Academic Track & AI Certification)
- Full-Time (≥5 courses/year): counts toward certifications.
- Dual Enrollment (LCP school of record) (≥3 courses/year): counts toward certifications.
- Dual Enrollment (other school of record) (≥6 LCP courses across high school with counselor-approved plan): counts toward certifications.
- Part-Time à-la-carte: does not count toward certifications.