Class 12 Hub
ailogicschool.blogspot.com · CBSE 2025–26
Class XII Artificial Intelligence
Subject Code 843 · Job Role: AI Assistant · All study materials in one place
Theory — 50 Marks
Practical — 50 Marks
Total — 100 Marks
At a glance
8
Subject Specific Units
5
Employability Units
6+
Python Practicals
3+
Orange Programs
843
Subject Code
3 min
Capstone Video Length
Study materials
📚
Chapter Notes
Unit-wise Theory Notes
Complete sub-topics, learning outcomes, and key concepts for all 8 units. Includes marks distribution and employability skills.
🔬
Practical Programs
Lab Manual with Code
All Python programs, Orange Data Mining practicals, and Data Storytelling project with code, explanations, and sample outputs.
❓
MCQ Practice
MCQ Zone — 20 Sec Timer
Interactive quiz with 10 moderate-to-hard questions per set. 20-second timer per question. Instant answer reveal with explanation.
🚀
Capstone Project
Project Guidelines & SDGs
Capstone project rules, SDG alignment guide, documentation format, video requirements, and sample project ideas aligned to CBSE-IBM cookbook.
📖
Data Storytelling
MDMS Data Story
Complete sample data story on the Mid-Day Meal Scheme. Freytag's Pyramid structure, charts, visualizations, and narrative — ready for practical file.
✨
Generative AI
Gemini API Chatbot
Hands-on Generative AI — Gemini API setup, chatbot code, prompt engineering guide, and Canva AI / Animaker exploration steps.
Practical file checklist
Minimum requirements for the Practical File (50 marks)
🐍 Python (min. 6)
- Pandas DataFrame — display, head, tail, missing
- CSV import → statistics → fill missing
- Model evaluation code (metrics)
- Linear Regression (optional)
- Gemini Chatbot (optional)
- TensorFlow C↔F (optional)
🍊 Orange (min. 3)
- Iris dataset — Scatter Plot viz
- Classification with kNN / Decision Tree
- Evaluate model — Confusion Matrix
- Image analytics (optional)
- Word Cloud NLP (optional)
- Big Data analytics (optional)
📖 Data Story (min. 1)
- MDMS impact on dropout rates
- Freytag's Pyramid — all 5 stages
- Charts, graphs, visualizations
- External factor analysis
- Comprehensive narrative
Marks distribution
| Unit | Topic | Theory | Practical |
|---|---|---|---|
| U1 | Python Programming – II | —* | Lab Test |
| U2 | Data Science Methodology | 8 | 12 |
| U3 | Making Machines See | 6 | 12 |
| U4 | AI with Orange Tool | —* | Lab Test |
| U5 | Introduction to Big Data | 6 | 12 |
| U6 | Understanding Neural Networks | 8 | 12 |
| U7 | Generative AI | 7 | 12 |
| U8 | Data Storytelling | 5 | 4 |
| Employability Skills (Part A) | 10 | — | |
| Capstone Project + Practical File + Viva | — | 50 | |
| Grand Total | 50 | 50 | |
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