CBSE · Class 12 · Artificial Intelligence · Syllabus
CBSE Class 12 Artificial Intelligence Syllabus, Units & Marks
Studying this subject? See the CBSE Class 12 Artificial Intelligence course, or read the units below first.
What is the CBSE Class 12 Artificial Intelligence syllabus?
CBSE Class 12 Artificial Intelligence is organised into 10 units. The full unit list, the topics inside each one and the exam pattern are below, taken from the syllabus we teach to.
CBSE Class 12 Artificial Intelligence unit list
| Unit | Topic |
|---|---|
| Unit 1 | Part A, Employability Skills |
| Unit 2 | Unit 1: Python Programming - II (evaluated in practicals) |
| Unit 3 | Unit 2: Data Science Methodology - An Analytic Approach to Capstone Project |
| Unit 4 | Unit 3: Making Machines See |
| Unit 5 | Unit 4: AI with Orange Data Mining Tool (evaluated in practicals) |
| Unit 6 | Unit 5: Introduction to Big Data and Data Analytics |
| Unit 7 | Unit 6: Understanding Neural Networks |
| Unit 8 | Unit 7: Generative AI |
| Unit 9 | Unit 8: Data Storytelling |
| Unit 10 | Part C, Practical Work / Project Work |
| Total | 10 units |
What each unit covers
Part A, Employability Skills
- Communication Skills-IV
- Self-Management Skills-IV
- ICT Skills-IV
- Entrepreneurial Skills-IV
- Green Skills-IV
Unit 1: Python Programming - II (evaluated in practicals)
- Recap of NumPy library
- Recap of Pandas library
- Importing and exporting data between CSV files and DataFrames
- Handling missing values
- Linear Regression algorithm (advanced learners)
Unit 2: Data Science Methodology - An Analytic Approach to Capstone Project
- Introduction to Data Science Methodology
- Steps for Data Science Methodology
- Model Validation Techniques
- Model Performance - Evaluation Metrics (MSE, RMSE, Precision, Recall, F1 score, Accuracy, confusion matrix)
Unit 3: Making Machines See
- How machines see
- Working of computer vision
- Computer Vision process
- Applications of computer vision
- Challenges of computer vision
- The future of computer vision
- Working with OpenCV - load, display, resize images (advanced learners)
Unit 4: AI with Orange Data Mining Tool (evaluated in practicals)
- What is Data Mining?
- Introduction to the Orange Data Mining tool
- Beneficiaries of Orange data mining
- Getting started with Orange
- Components of Orange
- Default Widget Catalogue
- Key AI domains with Orange - data science, computer vision, NLP
Unit 5: Introduction to Big Data and Data Analytics
- Introduction to Big Data
- Types of Big Data
- Advantages and disadvantages of Big Data
- Characteristics of Big Data
- Big Data Analytics
- Working on Big Data Analytics
- Mining Data Streams
- Future of Big Data Analytics
Unit 6: Understanding Neural Networks
- Parts of a neural network
- Components of a neural network
- Working of a neural network
- Types of neural networks
- Future of neural networks and societal impact
- Hands-on with TensorFlow and Keras (advanced learners)
Unit 7: Generative AI
- Introduction to Generative AI
- Working of Generative AI
- Generative and Discriminative models
- Applications of Generative AI
- LLM - Large Language Models
- Future of Generative AI
- Ethical and social implications of Generative AI
- Using the Gemini API to build a chatbot (advanced learners)
Unit 8: Data Storytelling
- Introduction to storytelling
- Elements of a story
- Introduction to data storytelling
- Why is data storytelling powerful?
- Essential elements of data storytelling
- Narrative structure of a data story (Freytag's Pyramid)
- Types of data and visualizations for different data
- Steps to create a story through data
- Ethics in data storytelling
Part C, Practical Work / Project Work
- Capstone Project (SDG-aligned, group of 3-5 students)
- Project Documentation
- 3-minute Capstone Project video
- Practical File - min 6 Python programs, 3 Orange Data Mining programs, 1 Data Story
- Lab Test (Python and Orange Data Mining)
- Viva Voce
Exam pattern
Total 100 marks: Theory 50 + Practical 50. Theory includes Employability Skills (Part A) and Subject-Specific Skills theory (Part B, 50 marks). Practical (Part C, 50 marks): Capstone Project 15 + Project Documentation 6 + Video 4 (= 25), Practical File 10, Lab Test on Python and Orange Data Mining 10, Viva Voce 5.
Practical and project work
Practical File with a minimum of 6 Python programs, 3 Orange Data Mining programs and 1 complete Data Story; a group Capstone Project (3-5 students) aligned to a UN Sustainable Development Goal, with written documentation and an exactly 3-minute project video; plus a lab test on Python and Orange Data Mining and a viva voce. Projects may be built using Python or no-code/low-code tools like Orange.
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Frequently asked questions
How many units are there in CBSE Class 12 Artificial Intelligence?+
CBSE Class 12 Artificial Intelligence is organised into 10 units.
What is the exam pattern for CBSE Class 12 Artificial Intelligence?+
Total 100 marks: Theory 50 + Practical 50. Theory includes Employability Skills (Part A) and Subject-Specific Skills theory (Part B, 50 marks). Practical (Part C, 50 marks): Capstone Project 15 + Project Documentation 6 + Video 4 (= 25), Practical File 10, Lab Test on Python and
Is there a practical exam in CBSE Class 12 Artificial Intelligence?+
Practical File with a minimum of 6 Python programs, 3 Orange Data Mining programs and 1 complete Data Story; a group Capstone Project (3-5 students) aligned to a UN Sustainable Development Goal, with written documentation and an exactly 3-minute project video; plus a lab test on