Class10_Facilitator_Handbook

Page 1: Title and Introduction

• Title: Artificial Intelligence Innovation Curriculum

• Support: Curated with support from Intel® https://www.intel.com

• Class Level: Class 10

• Document Type: Facilitator Handbook

Page 2: Overview

• Subject: Artificial Intelligence Curriculum for Class 10

• Support: Curated with Intel®

Page 3: Acknowledgements

• Patrons:

  • Sh. Ramesh Pokhriyal 'Nishank' (Minister of Human Resource Development, Government of India)

  • Sh. Dhotre Sanjay Shamrao (Minister of State for Human Resource Development, Government of India)

• Advisory, Editorial, and Creative Inputs:

  • Ms. Anita Karwal (IAS, Chairperson, Central Board of Secondary Education)

  • Ms. Shweta Khurana (Director, Intel India)

• Guidance and Support:

  • Sh. Anurag Tripathi (Secretary, CBSE)

  • Dr. Joseph Emmanuel (Director, CBSE)

  • Dr. Biswajit Saha (Director, Skill Education & Training, CBSE)

• Education Value Adder, Curator, and Coordinator:

  • Sh. Ravinder Pal Singh (Joint Secretary, Department of Skill Education, CBSE)

• **Content Curation Team: **

  • Ms. Sharon E. Kumar, Mr. Bhavik Khurana, Mr. Akshay Chawla, Mr. Shivam Agrawal (Intel AI For Youth Coaches)

• Feedback by Contributors:

  • Feedback from various educators across institutions in Delhi and Bengaluru

• Special Thanks: Principals and other educators who supported the initiative

Page 4: (No notable content)

Page 5: About the Book

• Recognition of AI: Seen as crucial for future global digital economy

• Significance of Skills-Based Education: Emphasis on project-related work

• AI Strategy Inventory: Importance of making India 'AI Ready'

• Curricular Introduction: AI introduced in Class IX (2019-2020), Class X extended from (2020-2021)

• Skill Subjects Offering: Offered as the sixth additional subject

• Collaboration with Intel: Development of Facilitator Handbook for training

Page 6: Table of Contents

• Sections Include:

  • Introduction to AI: Foundational Concepts

  • What is Intelligence?

  • Decision Making

  • Understanding AI

  • Applications of AI

  • Basics of AI

  • AI Ethics

  • AI Project Cycle

  • Data Sciences

  • Computer Vision

  • Natural Language Processing

  • AI Evaluation Methods

Page 7: Further Table of Contents (Continued)

• Specific Topics Covered:

  • Advanced Python Concepts

  • Recap Sections for Clear Understanding

  • Hands-on applications like Jupyter Notebook and Python programming

Page 8: Function of AI in Society

• Importance of AI in Everyday Life:

  • Smart Devices

  • Impact across sectors from Navigation to Entertainment

Page 9: What is Intelligence?

• Definition of Intelligence: Ability to perceive, infer and apply knowledge

• Characteristics of Intelligence: Interaction, reasoning, learning, and adaptation

Page 10: Technological Advancement

• Smart Devices Evolution:

  • Example of smartphones and their multifaceted functionalities

Page 11: Multiple Intelligences

• Areas of Intelligence Identified:

  • Interaction, Reasoning, Learning

Page 12: Decision Making Process

• Importance of Decision Making: Involves knowledge and experience

• Scenario Examples: To elucidate decision-making processes

Page 13 & 14: Decision-Making Scenarios

• Presented Scenarios: Challenges faced during decision making

Page 15: Characteristics of AI

• Key Traits of AI: Mimicking human decision-making and learning:

  • Collecting, understanding, analyzing data

Page 16: Everyday AI Applications

• Examples of AI Applications:

  • Voice Assistants, Gaming Enhancement, Health Monitoring

Page 17: Distinction between AI and Automation

• Criteria for AIClassification: Discussing capabilities versus automation limitations

Page 18: Various Definitions of AI

• Current Theories and Definitions: By different organizations

Page 19: KWLH Chart for AI Learnings

• Reflective Learning Tool: What learners know, want to know, have learned, and how they learned about AI

Page 20: Definition and Field of AI

• Broad Definition of AI: Intelligence, technology, and field of study involving machine tasks

Page 21: Differences among AI, ML, and DL

• Definitions: Relationships between AI, ML, and DL discussed

Page 22: Overview of AI Domains

• Classification of Major AI Domains: Data Sciences, Vision, Natural Language Processing

Page 23: Introduction to AI Ethics

• Ethical Concerns in AI Implementation: Highlight the significance of ethics in technology

Page 24-28: Ethical Scenarios & Data Privacy

• Scenarios Discussing Morality: Dilemmas presented arising from AI applications

Page 29-119: Various AI Project Cycle Stages

• Detailed Overview: Identification and exploration of AI project cycle for successful implementation

• Examples from Each Phase: Demonstrates how AI is developed and assessed

Final Overview

• AI Potential: AI’s capability to shape societal structures and implications in multiple domains

• Future Implications and Ethical Considerations: Crucial for development in AI-powered initiatives.