⭐ Program Features
🎥 Flip Learning for Deeper Understanding
Instructional videos embedded throughout the course allow students to revisit key concepts at their own pace. This supports differentiated learning, promotes mastery, and improves long-term retention.
🧭 Cross-Disciplinary Integration
Projects are designed to connect with science, social studies, and arts, helping students apply AI and data skills across subjects and build well-rounded academic thinking.
🗂️ Student Portfolios for Showcase & Assessment
Each learner builds a personal portfolio of code projects, intelligent applications, and data dashboards—ideal for school exhibitions, competitions, and future academic use.
🧠 Ethics, Impact & Career Exploration
The program encourages thoughtful reflection on AI ethics, bias, privacy, and career pathways in AI, data science, and software development—helping students make informed, future-oriented choices.
🏅 Industry Readiness & Certification Pathways
Students develop foundational knowledge in Python, AI, and Data Science that prepares them for further learning and certification pathways with platforms like Google, Apple, Microsoft, and AWS.
📚 UC A–G Compliant Curriculum
The course is designed to meet the academic rigor required for the University of California’s A–G requirements, qualifying it as a recognized CTE elective. This ensures students earn credits aligned with college admission standards while developing 21st-century tech skills.
⭐ Hi-Lights
Future-Ready Learning
A comprehensive learning journey that blends foundational Python programming with real-world applications in Artificial Intelligence and Data Science. Students build future-ready skills through interactive coding, intelligent systems design, and data-driven projects.
Curriculum Alignment
Aligned with ISTE – USA, UNESCO’s K–12 AI Curriculum, and US K–12 AI Education Guidelines, the program ensures students receive a globally benchmarked education that promotes digital fluency and innovation.
Expertly Curated
Structured by experienced educators and technologists, the course progresses from basic programming concepts to advanced AI and data science skills. Each module is designed to build logical thinking, technical expertise, and creative problem-solving through project-based learning.
AI & Data Science Lab Learning Sessions
Students gain practical experience through guided lab sessions involving face detection, emotion recognition, chatbots, NLP pipelines, machine learning workflows, and data analysis using Python, OpenCV, NumPy, pandas, SQL, and Tableau.
Flip Learning
Embedded instructional videos enhance understanding of key concepts, enabling students to explore topics in greater depth at their own pace. This supports differentiated learning and improves long-term retention.
Assessment Tools
Each lesson includes multiple-choice questions to reinforce understanding and check comprehension. Every module concludes with a comprehensive assessment and a capstone project that applies learned skills in real-world scenarios.
Real-World Applications
The course emphasizes age-appropriate, project-based learning. Students build functional programs such as calculators, games, chatbots, emotion detectors, and data dashboards—each designed to demonstrate how Python, AI, and data science can be applied to solve real-world problems.
