PART A – Employability Skills (Class 9 Artificial Intelligence – Code 417)
| Unit No. | Unit Name | Hours | Marks | Key Topics | Suggested Activities |
|---|---|---|---|---|---|
| 1 | Communication Skills – I | 10 | 2 | – Meaning & Importance of Communication – Types: Verbal, Non-verbal, Written, Visual – Communication Cycle – Barriers & Solutions | – Role Play – Group Discussions – Body Language Practice – Listening Drill |
| 2 | Self-Management Skills – I | 10 | 2 | – Self-Awareness – SWOT Analysis – SMART Goals – Time Management – Self-Confidence | – Goal-Setting Journal – Time Table Planner – Personal SWOT Activity |
| 3 | ICT Skills – I | 10 | 2 | – Introduction to ICT – Computer Basics – MS Word, Excel, PowerPoint (Basics) – Internet and Email Safety | – Create Document in Word – Email Practice – Excel Budget Sheet |
| 4 | Entrepreneurial Skills – I | 15 | 2 | – Who is an Entrepreneur? – Characteristics – Role in Society – Myths vs Reality | – Interview a Local Entrepreneur – Make a Business Idea Poster |
| 5 | Green Skills – I | 5 | 2 | – Green Economy – Sustainable Development – Eco-friendly Practices | – Cleanliness Drive – Poster on Sustainability – Green Diary |
PART B – Subject-Specific Skills (40 Marks)
| Unit No. | Unit Name | Hours | Marks | Key Topics | Suggested Activities / Practicals |
|---|---|---|---|---|---|
| 1 | Introduction to AI & Ethics | 55 | 10 | – What is AI? – Domains: NLP, CV, Data – AI vs Traditional Programming – AI Project Cycle (Problem, Data, Model, Evaluate) – Ethics: Bias, Access, etc. | – Semantris (NLP) – Quick Draw (CV) – Rock-Paper-Scissors Game – Moral Machine Activity |
| 2 | Data Literacy | 50 | 10 | – Importance of Data – Cybersecurity Basics – Data Types – Interpretation & Visualization | – Collect & Explore Data – Create Visuals (Tableau, Datawrapper) – Dashboard creation |
| 3 | Maths in AI – Statistics & Probability | 25 | 10 | – Mean, Median, Mode, SD – Data Types & Graphs – Probability (Theory & Experiment) | – Dice Game – Number Patterns – Mini Survey & Data Analysis |
| 4 | Introduction to Generative AI | 20 | 5 | – What is Generative AI? – Applications (Image, Text, Music) – Deepfakes, Ethics | – GAN Paint – Text Gen Tool – Real vs AI Image Game |
| 5 | Introduction to Python Programming | 10 | 5 | – Syntax, print(), input()– Variables, Operators – If-else, Loops – Lists | – Programs: Grade Checker, Sum of Numbers, List Average, etc. |
PART C – Practical Work (35 Marks)
| Component | Marks | Details |
|---|---|---|
| Python Practical File | 15 | – At least 15 programs – Cover: I/O, Conditions, Loops, Lists |
| Python Practical Exam | 15 | – Live coding test (basic logic-based problems) |
| Viva Voce | 5 | – Based on: Python concepts, AI games, project work, basic theory |
Sample Programs to Include in Practical File:
| Program Name | Concept Covered |
|---|---|
| Sum of two numbers | Input & Arithmetic |
| Even/Odd Number | If-Else Condition |
| Grade Calculator | Nested If |
| Factorial using loop | While Loop |
| Find largest among 3 numbers | Conditions + Logical Ops |
| Reverse a List | List & Loops |
| Average of numbers in list | Lists + Loops |
| Voting eligibility checker | Input + Conditionals |
PART D – Project Work / Portfolio / Field Visit (15 Marks)
| Project Option | Details |
|---|---|
| AI Model/Project Work | – Follow AI Project Cycle: Problem → Data → Model → Evaluate – Tools: Teachable Machine, Scratch, ML for Kids |
| Example Projects: | – Emotion Detector – Smart Bin Classifier – Object Counter using CV |
| AI for Sustainable Development Goals | – Choose any SDG (e.g. Education, Clean Water) – Create solution via AI concept – Poster, Report, or Working Model |
| Field Visit / Virtual Tour | – Visit AI-powered organization or take online tour (e.g., Google AI, Amazon) – Report with AI usage, challenges, impact |
| Portfolio (if project not done) | – Compilation of worksheets, activities, AI ethics, data charts – Posters: “AI for Good”, “Ethical AI”, “Smart Home Design” |
Portfolio Sample Inclusions:
| Activity | Description |
|---|---|
| Smart Home Plan | Draw or design AI-powered smart home layout |
| Data Collection Exercise | Gather and organize sample dataset |
| Quick Draw Log | Summary of attempts, accuracy rate |
| Ethics Worksheet | Dilemmas + decisions taken in AI scenarios |
| AI Poster | Creative poster showing “AI for Social Good” |
The practical activities like Quick Draw and Semantris are such a smart way to introduce students to AI concepts in a fun, hands-on way. This kind of early exposure can really spark curiosity and reduce the intimidation factor around tech-heavy subjects.
The focus on both AI technical skills and employability skills like communication and self-management is spot-on for preparing students for the future. It’s great to see practical activities woven into the curriculum, as it will help them connect what they’re learning to real-world applications.
Really appreciate how the syllabus breakdown includes hands-on activities like using Semantris for NLP and building dashboards with Tableau. It’s great to see practical exposure being integrated so early—it helps students actually experience how AI tools work instead of just reading about them.
This breakdown of the AI syllabus is super helpful—especially the balance between technical concepts like NLP and Computer Vision with practical, hands-on activities like Semantris and the Rock-Paper-Scissors game. I also appreciate how the ethics and data literacy sections are given real weight, which is so important at this stage of learning AI.