Day 1 — Understand
The World of Machines, Data & AI
Students begin with the fundamentals of how machines and Artificial Intelligence work.
Students Learn
- What is a machine?
- Machines vs humans
- Mechanical, electronic and smart machines
- Data vs information
- Input → Process → Output
- What Artificial Intelligence actually is
- AI around us and AI in India
- Python variables and data types
- Python input and output
if / elif / elsedecisions
By the end of Day 1, students are expected to understand machines, turn data into useful information, identify the IPO cycle, recognise everyday AI systems and write basic Python programs that can ask questions and make decisions.
Day 1 Activities
Robot Says • Machine Sorting • Five Machines Activity • Data Detective • Spot the AI • AI Treasure Hunt • Be the AI Role-Play • AI Quiz Bowl
Students also complete beginner Python challenges involving variables, user input and decision-making.
Day 2 — Explore & Create
AI Explorers, Python & Generative AI
Day 2 takes students deeper into how AI learns and how they can create with it.
Students Learn
- AI vs Machine Learning vs Deep Learning
- How machines learn from data
- Training data, models and predictions
- Supervised, unsupervised and reinforcement learning
- Neural networks
- Python lists
- Python
forloops - Python functions
- Generative AI
- AI for stories, images, music and video
- Prompt engineering
- Responsible AI
- AI mistakes and hallucinations
- Privacy, bias and deepfakes
Students also learn the four-part prompting method:
Role + Task + Context + Format
Day 2 Activities
AI Prediction Game • Co-write a Story • Image Prompt Activity • Thirty-Second Soundtrack • Prompt Battle Arena • Catch the Mistake • AI Meme Challenge • AI Poster Challenge • Level 2 AI Quiz
The workbook encourages students to use AI as a creative assistant while checking facts, protecting privacy and clearly identifying AI-generated work.
Day 3 — Build & Showcase
Day 3 shifts the focus from learning concepts to building something that a real person could use.
Students Explore
- Python Mini Project
- Testing & Debugging
- AI-powered websites and apps
- No-code development
- Robotics & IoT
- Real-world AI applications
- Prototype development
- User testing
- Startup-style project pitch
- AI careers
- AI learning roadmap and portfolio
The day includes a Python quiz game, project development, testing, improvement and a final pitch to judges.
Projects Students Build & Explore
1. Analyse Your Class — Python Mini Project
Students collect ten real numbers such as test scores, heights or screen-time minutes and create functions to calculate the average, find the highest value and count how many values are above average.
Implementation Tools:
Python
Recommended Platform: Replit / browser-based Python environment
2. AI-Themed Quiz Game
Students combine their Python skills into one complete program. Lists store questions and answers, a loop asks each question, a function checks the response and conditions maintain the score.
Students can extend the game with more questions, grades, hints and personalised greetings.
Implementation Tools:
Python
Recommended Platform: Replit
3. AI-Powered Website
Students explore how AI can be added to a website for features such as:
- Chat assistance
- Intelligent search
- Live translation
- Image recognition
- Accessibility support
The workbook asks students to plan a simple interface and clearly identify where AI is being used.
Recommended Implementation Tools:
Framer – website creation
ChatGPT / Gemini – AI-powered content or chat assistance
Canva – graphics and interface elements
4. AI-Powered App Prototype
Students plan an app around one clear job, sketch up to three screens, decide exactly where AI helps and consider what happens if the AI produces a wrong answer.
The workbook specifically introduces the idea of connecting a no-code interface to an existing AI service.
Recommended Implementation Tools:
Glide – no-code app building
MIT App Inventor – visual app development
ChatGPT / Gemini – AI functionality
5. Design Your Robot
Students invent a robot for a real job in their school and design its complete working cycle:
Sensors → Processing → Decision → Actuators
They also identify one action the robot must never perform, bringing safety into the design process.
Recommended Implementation Tools:
Paper / Canva – robot concept and prototype design
micro:bit + MakeCode – optional practical robotics implementation
Teachable Machine – optional AI recognition model
6. AI Meme & Responsible AI Poster
Students create a meme that teaches one true fact about AI and design a school poster explaining how to use AI honestly.
The focus is on clarity, usefulness, design and clearly stating where AI helped.
Recommended Implementation Tools:
Canva – poster and meme design
ChatGPT / Gemini – brainstorming and wording
DALL·E – optional AI-generated illustrations
Creative AI Activities
Students also explore how AI can help create different forms of digital content.
AI Story & Writing
Students co-write a story with AI, alternating between their own sentences and AI-generated sentences.
Implementation Tools:
ChatGPT • Claude • Gemini
AI Image Creation
Students learn to write image prompts using subject, style, framing and mood.
Implementation Tools:
DALL·E • Midjourney
AI Music
Students write prompts describing instruments, tempo, mood and length to create music for project videos or presentations.
Implementation Tools:
Suno • Udio
AI Video
Students explore creating short AI-generated video clips from written scene descriptions.
Implementation Tools:
Runway • Veo
Grand Finale Project — Solve a Real Problem with AI
The main Class 7 project is the AI Champions Cup Grand Finale.
Each team identifies one real problem experienced by a real person, develops a prototype that helps solve it, tests the prototype and finally presents it to judges.
The 7-Step Build Process
1. Find a Problem
Identify a genuine problem.
2. Understand the User
Talk to the person instead of guessing what they need.
3. Design the Solution
Decide exactly where AI can help.
4. Build a Prototype
Create a simple working version.
5. Test It
Let someone outside the team use it.
6. Improve It
Fix what confused the user.
7. Present It
Explain the solution through a four-minute pitch.
Suggested Implementation Tools
Depending on the team’s chosen solution:
Python Project: Python + Replit
AI Chat Solution: ChatGPT / Gemini
Website: Framer
App: Glide / MIT App Inventor
Image Classifier: Teachable Machine
Robot Prototype: micro:bit + MakeCode
Presentation: Canva / Google Slides
AI Images: DALL·E
Music: Suno
Video: Runway
The workbook itself allows students to use tools such as Python, an AI chat tool, paper and a phone camera, depending on their prototype.
Startup-Style Project Pitch
Students present their final project like a young founder and answer questions such as:
What problem are you solving?
Who has the problem?
What is your AI solution?
How does it work?
Why is it useful?
What makes it different?
What could it become in five years?
AI Tools Introduced in the Workbook
The workbook directly introduces several tools for different types of AI creation:
Text, Ideas & Code: ChatGPT • Claude • Gemini
Images: DALL·E • Midjourney
Music: Suno • Udio
Video: Runway • Veo
Machine Learning: Teachable Machine
The workbook also stresses that students should use these tools with teacher guidance where required, protect personal information and clearly label AI-generated work.
Skills Students Develop
Through the three-day programme, students develop:
AI Awareness • Machine Learning Understanding • Python Programming • Data Handling • Prompt Engineering • Generative AI Skills • Logical Thinking • Creative Problem-Solving • Testing & Debugging • Responsible AI Use • Teamwork • Project Development • Presentation Skills
By the end of the workshop, students are expected to be able to write basic Python, understand how machines learn from data, use Generative AI responsibly, develop an AI solution to a real problem and present what they built.
Understand → Explore → Create → Build → Showcase
3 Days. From Learning About AI to Building With AI.
The programme concludes with the Grand Finale Project, Startup Pitch, AI Champions Cup, awards and Certificate of Completion. The certificate records that students have covered machines and data, machine learning, Python, Generative AI, prompt engineering, responsible AI, robotics and project development.
SKK Educational Foundation
AI Learning + Python Programming + Generative AI + Project Execution