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ARTIFICIAL INTELLIGENCE (SUBJECT CODE 417)
CLASS – IX
Total Marks: 100 (Theory-50 + Practical-50)
OBJECTIVES OF THE COURSE:
The objective of this module/curriculum - which combines both Inspire and Acquire modules is to develop a readiness for understanding
and appreciating Artificial Intelligence and its application in our lives. This module/curriculum focuses on:
1. Helping learners understand the world of Artificial Intelligence and its applications through games, activities and multi-sensorial
learning to become AI-Ready.
2. Introducing the learners to three domains of AI in an age-appropriate manner.
3. Allowing the learners to construct the meaning of AI through interactive participation and engaging hands-on activities.
4. Revisiting AI domains, project cycle and Ethics
5. Introducing the learners to the importance of Math for AI, data literacy and generative AI
6. Introducing the learners to programming skills - Basic python coding language.
LEARNING OUTCOMES:
Learners will be able to:
1. Identify and appreciate Artificial Intelligence and describe its applications in daily life.
2. Relate, apply and reflect on the Human-Machine Interactions to identify and interact with the three domains of AI: Data, Computer
Vision and Natural Language Processing and Undergo assessment for analysing their progress towards acquired AI-Readiness skills.
3. Imagine, examine and reflect on the skills required for futuristic job opportunities.
4. Unleash their imagination towards smart homes and build an interactive story around it.
5. Understand the impact of Artificial Intelligence on Sustainable Development Goals to develop responsible citizenship.
6. Research and develop awareness of skills required for jobs of the future.
7. Gain awareness about AI bias and AI access and describe the potential ethical considerations of AI.
8. Develop effective communication and collaborative work skills.
9. Get familiar and motivated towards Artificial Intelligence and Identify the AI Project Cycle framework.
10. Learn problem scoping and ways to set goals for an AI project and understand the iterative nature of problem scoping in the AI
project cycle.
11. Brainstorm on the ethical issues involved around the problem selected.
12. Foresee the kind of data required and the kind of analysis to be done, identify data requirements and find reliable sources to
obtain relevant data.
13. Use various types of graphs to visualize acquired data.
14. Understand types of modelling.
15. Understand the importance of Math for AI.
16. Learn the concept of data literacy and generative AI
17. Acquire introductory Python programming skills in a very user-friendly format.
SKILLS TO BE DEVELOPED
AI
Applying Concepts in READINESS Developing Life Skills
Learning Technical Skills CONCEPTS Through Concept Building
TECHNICAL LIFE
SKILLS FOR AI SKILLS FROM
AI
Fostering Life Skills in
Applying Technical Skills
(vi)

