CBSE Class 10 Artificial Intelligence (Code 417) Syllabus (2024-25) – Full Breakdown

The CBSE Class 10 Artificial Intelligence Syllabus (Code 417) introduces students to the exciting world of AI, a skill subject under CBSE’s vocational curriculum. Designed for the 2024-25 session, it combines theoretical concepts (50 marks) and practical applications (50 marks), totaling 100 marks. Below is the complete syllabus, structured into Part A (Employability Skills) and Part B (Subject-Specific Skills), with units, topics, and marks distribution as per CBSE’s official guidelines.

Part A: Employability Skills (10 Marks)

This section is common across skill subjects and focuses on foundational skills, assessed in the theory exam for 10 marks.

1. Unit 1: Communication Skills – II (2 Marks)
   
   • Types of communication (verbal, non-verbal, written).
   • Effective communication techniques.
   • Overcoming communication barriers.
2. Unit 2: Self-Management Skills – II (2 Marks)
   
   • Stress and time management.
   • Goal setting and self-motivation.
   • Personal responsibility and discipline.
3. Unit 3: Information and Communication Technology Skills – II (2 Marks)
   
   • Operating systems basics (e.g., Windows, Linux).
   • File management and keyboard shortcuts.
   • Safe internet practices.
4. Unit 4: Entrepreneurial Skills – II (2 Marks)
   
   • Traits of an entrepreneur.
   • Identifying business opportunities.
   • Risk management basics.
5. Unit 5: Green Skills – II (2 Marks)
   
   • Sustainable development principles.
   • Role of technology in environmental conservation.
   • Energy-saving practices.

Part B: Subject-Specific Skills (40 Marks)

This section covers AI-specific concepts, assessed in a 40-mark theory paper, with some topics requiring practical understanding.

1. Unit 1: Introduction to Artificial Intelligence (AI) (10 Marks)
   
   • Topics:
     
     • What is AI? Definitions and examples.
     • Difference between AI, Machine Learning (ML), and Deep Learning (DL).
     • Applications of AI in daily life (e.g., virtual assistants, recommendation systems).
     • Ethical concerns (AI bias, privacy).
   • Skills: Understanding AI’s role and impact.
2. Unit 2: AI Project Cycle (10 Marks)
   
   • Topics:
     
     • Problem Scoping: Defining goals and 4Ws (Who, What, Where, Why).
     • Data Acquisition: Collecting and preparing data.
     • Data Exploration: Visualizing data (charts, graphs).
     • Modelling: Building AI models.
     • Evaluation: Testing model accuracy.
   • Skills: Applying a structured approach to AI projects.
3. Unit 3: Neural Networks (5 Marks)
   
   • Topics:
     
     • Basics of human neurons vs. artificial neurons.
     • Concept of neural networks in AI.
     • Simple applications (e.g., image recognition).
   • Skills: Grasping foundational AI algorithms.
4. Unit 4: Introduction to Python (15 Marks)
   
   • Topics:
     
     • Python basics: Variables, data types, loops, conditions.
     • Libraries for AI (e.g., NumPy, Pandas, Matplotlib).
     • Simple coding exercises (e.g., data manipulation, plotting).
   • Skills: Coding for AI applications (assessed practically too).

Practical Assessment (50 Marks)

The practical component evaluates hands-on skills, conducted internally by schools and submitted to CBSE. Total: 50 marks.

• Practical Work (30 Marks):
  
  • Coding in Python (e.g., data analysis, simple AI models).
  • AI project simulation (e.g., problem scoping to evaluation).
  • Use of tools like Jupyter Notebook or Python IDEs.
• Viva Voce (10 Marks):
  
  • Questions on Python code, AI concepts, and project work.
• Project/Portfolio (10 Marks):
  
  • Small AI project (e.g., chatbot, data visualization) or portfolio of practical tasks.

Marks Distribution Summary

Exam Pattern Highlights

• Theory Paper: 50 marks, 2 hours, includes MCQs (20%), short-answer, and long-answer questions.
• Practical: 50 marks, school-assessed, focuses on Python and AI project skills.
• Weightage: Units 1, 2, and 4 carry higher marks due to foundational and practical importance.