National AI Foundations Program
in Internship ProgramWhat you will learn?
Module 1: Introduction to Artificial Intelligence
Module 2: AI Around Us
Module 3: Basics of Data & Machine Learning
Module 4: Intro to Python for AI
Module 5: Introduction to Generative AI
Module 6: AI Ethics & Responsible AI
Module 7: No-Code AI Projects
Module 8: Capstone Project
About this course
Empowering the Future: AI Foundations Program
The world is evolving at an unprecedented pace from digital financial systems to intelligent agricultural solutions. To ensure that the students are prepared to lead in this era of transformation, the AI Foundations Program (AIFP) has been introduced under the visionary AI Pragya Mission.
AIFP is not merely a technology course it is a strategic initiative to future ready the next generation. The program bridges the gap between traditional classroom learning and the rapidly advancing AI driven ecosystem, equipping students with the awareness, mindset, and foundational skills required for the 21st century digital economy.
What the Program Delivers
- Demystifying Artificial Intelligence
- Practical Exposure to Emerging Tools
- Critical and Analytical Thinking
- Responsible and Ethical Innovation
Our Vision
"To enable students across India to transition from mere users of technology into knowledgeable, ethical, and forward thinking innovators who actively contribute to shaping the future digital ecosystem."
FAQ
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1. What is AI?
2. History of AI
3. Types of AI (Narrow, General, Super AI)
4. AI vs ML vs Deep Learning
5. AI in India
Indian Case Studies:
1. ISRO satellite image AI
2. UIDAI identity verification
3. Tata Consultancy Services AI services
1. Healthcare AI
2. Agriculture AI
3. Smart Cities
4. Education AI
5. Fintech AI
Indian Examples:
1. Niramai (AI in breast cancer detection)
2. CropIn (AI in farming)
3. UPI fraud detection AI
1. What is Data?
2. Types of Data
3. Supervised vs Unsupervised Learning
4. Classification vs Regression
5. Training & Testing
Hands-on:
1. Use Google Teachable Machine
2. Simple dataset classification
Mini Lab:
1. Predict exam score from study hours
2. Image recognition activity
1. What is Python?
2. Variables
3. Lists
4. Loops
5. Functions
6. Basic Libraries (NumPy, Pandas overview)
Practical:
1. Install Python
2. Simple ML with Scikit-Learn (demo)
Outcome:
Students run their first ML model.
1. What is Generative AI?
2. How LLMs work (simplified)
3. Prompt Engineering basics
4. AI content creation
Tools:
1. Chat-based AI
2. AI image tools
3. AI code assistants
1. Bias in AI
2. Data privacy
3. AI misuse
4. Deepfakes
5. AI laws in India
6. Responsible innovation
Indian Context:
1. Digital India mission
2. Data Protection Act overview
1. Chatbot for school website
2. AI attendance predictor
3. Crop disease identifier (concept)
4. Fake news classifier (concept)
Tools:
1. Teachable Machine
2. Scratch AI
3. Low-code ML tools
Project Themes:
1. AI for Agriculture
2. AI for Women Safety
3. AI for Local Business
4. AI for Traffic
5. AI for Education
Deliverables:
1. Problem Statement
2. Dataset Description
3. AI Approach
4. Demo
5. Presentation
