Here’s an outline for a Class 7 Artificial Intelligence Curriculum:
Unit 1: Introduction to Artificial Intelligence
- What is AI?
- Definition and overview of Artificial Intelligence
- How AI is different from human intelligence
- Examples of AI in everyday life: Virtual assistants, smart devices, AI in search engines
- The History of AI
- Early concepts and developments in AI
- Key milestones in AI’s journey: Turing Test, development of machine learning, modern AI applications
Unit 2: Applications of AI
- AI in the World Around Us
- AI in healthcare: Disease diagnosis, drug discovery
- AI in transportation: Self-driving cars, traffic management
- AI in entertainment: How AI is used in music, video, and gaming
- AI in Communication and Social Media
- AI in chatbots: How chatbots work and examples from customer service
- AI in social media platforms: How recommendation algorithms work
Unit 3: Introduction to Machine Learning
- What is Machine Learning?
- Basic definition: How machines learn from data without being explicitly programmed
- Key concepts: Training data, testing data, and algorithms
- Types of Machine Learning
- Supervised Learning: Simple examples like teaching a computer to recognize objects
- Unsupervised Learning: Grouping data into clusters (e.g., customer profiles)
- Introduction to reinforcement learning: AI learning from rewards (e.g., how AI wins in games)
Unit 4: Data and Its Role in AI
- What is Data?
- Understanding data: Structured vs. unstructured data
- How data is collected, cleaned, and organized for AI systems
- Visualizing Data
- Basics of data visualization: Charts, graphs, and infographics
- Tools: Using simple tools like Google Sheets to create visual representations of data
Unit 5: Natural Language Processing (NLP)
- Introduction to NLP
- How computers understand human language
- Examples of NLP: Virtual assistants, language translation, text analysis
- Simple NLP Projects
- Using basic tools to create a chatbot or language-based project (no coding required)
Unit 6: AI in Image Recognition
- What is Computer Vision?
- How AI processes and understands images
- Applications of image recognition: Face recognition, object detection, and classification
- Hands-on Activity
- Explore AI tools that can recognize images (e.g., Teachable Machine, AI-based games)
Unit 7: Ethics of AI
- AI and Ethics
- Basic ethical questions surrounding AI: What is fair, transparent, and safe AI?
- How AI can be biased: Understanding the impact of biased data on AI decisions
- AI and Society
- How AI affects jobs, privacy, and security
- Discuss the impact of AI on industries and daily life
Unit 8: Simple AI Projects and Activities
- Create Simple AI Projects
- Build a basic rule-based chatbot or program using AI tools like Scratch or MIT App Inventor
- Use AI platforms to train a simple machine learning model (with teacher guidance)
- Exploring AI in Fun Ways
- Experiment with AI-based games or AI art generators to understand AI decision-making
- Use visual-based AI tools like Google’s AI Experiments to explore fun AI applications
Unit 9: The Future of AI
- AI in the Future
- Trends and developments in AI: AI in space exploration, AI in medicine, smart cities
- The future of AI in education, jobs, and industries
- AI Careers
- Introduction to AI career paths: AI researchers, data scientists, AI engineers
- Key skills for working in AI: Critical thinking, programming, data analysis
This curriculum introduces students to AI through simple, fun, and interactive activities. It emphasizes understanding AI concepts, real-world applications, and ethical considerations, balanced with hands-on projects suited for grade 7 learners.