Data Science Honors

This honors-level course introduces students to the core concepts and tools of data science, including programming for data analysis, data collection and management, data visualization, and foundational statistics. Students will explore exploratory and predictive analytics, as well as introductory machine learning techniques, while applying these skills to real-world datasets. Through hands-on projects and coding exercises, students will develop practical analytical and computational skills essential for modern data-driven problem solving. The course culminates in a capstone project that integrates the key elements of the curriculum.

Credits 5 (one semester)
UC A–G Area G — College-Preparatory Elective (on UCOP A–G list)
Level & GPA Weight Honors (weighted)
Recommended Grades G10–12
Prerequisites Introductory AI/tech course recommended; and 1 semester of Python or R Programming
Textbook Instructor-provided readings, datasets, and references (no fixed text)

Major Units & Topics

  • Introduction to Data Science & the data lifecycle
  • Python for Data Science (notebooks, libraries, workflows)
  • Data Collection, Management & Ethics
  • Data Cleaning & Preparation
  • Data Visualization (telling stories with charts)
  • Introductory Statistics for Data Science
  • Exploratory Data Analysis (EDA)
  • Introduction to Machine Learning
  • Real-World Applications & Capstone

Practical Work

  • Notebook labs for cleaning, visualization, and modeling
  • Applied mini-projects using real datasets
  • Capstone project demonstrating end-to-end data workflow

Technology & Platforms

  • Python (Jupyter/Colab) or R (RStudio) environment
  • Versioned notebooks; reproducible workflows and documentation
  • Curated public datasets and instructor-provided data

Delivery Options & Tuition (5-credit course)

Model What’s Included Live Hours Tuition
Mini-One-on-One Targeted coaching on EDA/ML, code reviews, and project pacing 12 hours $1,428
One-on-One Fully personalized instruction and capstone mentorship 24 hours $2,856

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, projects, and studying for quizzes/tests/exams.
  • Communication: Q&A and periodic progress updates via email (all models).
  • Weekly load depends on 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 chosen model and pacing.)

Grading & Course Policies

Category Weight
Classwork 10%
Tests/Quizzes 20%
Homework 20%
Project 20%
Final Test 20%
Capstone Project 10%
  • 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 via emails

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.