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Artificial Intelligence (AI) – Foundations
AI Fundamentals, Python, Data & Responsible AI
Target Audience – High School Students (Grades 9–12) and Beginners with little or no prior experience in Artificial Intelligence, Python, or Data Science.
Program Pathway – Foundation
Total Duration – 72 Hours
Delivery – Cohort-Based + Instructor-Led + Hands-On Labs
Program Goal
This beginner-friendly program introduces students to the fundamentals of Artificial Intelligence through simple explanations, Python programming, data concepts, responsible AI, and hands-on projects.
Hands-On Learning
Students learn through instructor-led lessons, guided coding exercises, practical labs, mini-projects, assessments, and a final AI project.
What Students Build
● Python programming skills
● Data analysis fundamentals
● Understanding of AI and machine learning
● Responsible AI awareness
● A beginner-level AI project
● A foundation for the AI Practitioner pathway
Recommended Lab Requirements
Each student should ideally have:
● Windows / MAC Laptop or desktop computer
● 4 GB RAM minimum; 8 GB RAM recommended
● At least 5–10 GB of free storage
Next Step
After successfully completing AI Foundations, students can progress to AI Practitioner, where they begin exploring Machine Learning, Data Science, Computer Vision, AI Model Development, and Applied AI projects.
| Program Structure | ||
| Module | Topic | Hours |
| Module 1 | Introduction to Artificial Intelligence | 12 |
| Module 2 | Python Programming for AI | 18 |
| Module 3 | Data Fundamentals for A | 14 |
| Module 4 | AI Ethics & Responsible AI | 10 |
| Module 5 | AI Foundation Project | 18 |
| Total | 72 Hours | |
Curriculum
- 5 Sections
- 0 Lessons
- 72 Hours
Expand all sectionsCollapse all sections
- Module 1 – Introduction to Artificial Intelligence0 Items✅ Topics :- Understanding AI • AI & ML Fundamentals Types of AI • AI Applications • How AI Systems Work • Introduction to Generative AI
- Module 2 – Python Programming for AI0 Items✅ Topics :- Python Basics • Variables & Data Types • Input & Output • Operators • Conditions • Loops • Lists & Dictionaries •Functions • Python Libraries • Python for AI
- Module 3 – Data Fundamentals for AI0 Items✅ Topics :- Understanding Data • Data Types • Structured & Unstructured Data • Datasets • Data Collection • Data Cleaning • Basic Data Analysis • Data Visualization
- Module 4 – AI Ethics & Responsible AI0 Items✅ Topics :- AI Ethics • Bias & Fairness • Privacy • Responsible AI • AI Safety • Reliability • Generative AI Limitations • Real-World Case Studies
- Module 5 – AI Foundation Project0 Items✅ Topics :- Project Ideation • Problem Definition • Data & Solution Planning • Python-Based Development • Testing & Evaluation • Responsible AI Review • Documentation • Final Presentation Final Project: Build and present a beginner-friendly AI solution.
Yes. Students can access the learning materials online and study from anywhere.
