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CBSE Class 10 AI Syllabus: Code 417

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

Component Marks
Part A: Theory 10
Part B: Theory 40
Practical Work 30
Viva Voce 10
Project/Portfolio 10
Total 100

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.

 

VIST MORE LINKS

CBSE Class 10 IT Syllabus (Code 402)

 

CBSE Class 10 ITC MCQs

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