AI+ Everyone (AIEV) – Outline

Detailed Course Outline

Module 1: Introduction to Artificial Intelligence (AI)

• 1.1 What is Artificial Intelligence?
• 1.2 A Brief History of AI
• 1.3 Demystifying AI: Myths vs. Reality
• 1.4 The Significance of AI in Everyday Life

Module 2: AI Technologies

• 2.1 Machine Learning: Basics and Beyond
• 2.2 Deep Learning and Neural Networks
• 2.3 AI Technologies in Action: Simplified Examples
• 2.4 Interactive Workshop: Exploring AI

Module 3: AI in Action: Applications and Case Studies

• 3.1 Introduction to AI Applications
• 3.2 Case Study 1: Smart Speakers
• 3.3 Case Study 2: Self-Driving Cars
• 3.4 Case Study 3: Healthcare Applications

Module 4: The Workflow of AI Projects

• 4.1 Introduction to AI Project Workflow
• 4.2 Problem Definition and Data Preparation
• 4.3 Model Selection, Training, and Validation
• 4.4 Deployment and Integration
• 4.5 Evaluation and Iteration

Module 5: Ethics and Social Implications of AI

• 5.1 Introduction to AI Ethics and Social Implications
• 5.2 Bias and Fairness in AI
• 5.3 Privacy and Security in the Age of AI
• 5.4 Responsible AI Development
• 5.5 AI and Society: Looking Ahead

Module 6: Generative AI and Creativity

• 6.1 Introduction to Generative AI
• 6.2 Applications of Generative AI in Creativity
• 6.3 Ethical Considerations in Generative AI
• 6.4 Exploring the Future of Creativity with AI

Module 7: Preparing for An AI-Driven Future

• 7.1 The Future Landscape of AI
• 7.2 AI and the Transformation of Work
• 7.3 Lifelong Learning in an AI World
• 7.4 Staying Relevant in an AI-Driven World
• 7.5 Interactive Discussion: Preparing for the Future with AI

Module 8: Starting with AI: First Steps and Resources

• 8.1 Introduction to Starting with AI
• 8.2 Choosing AI Projects
• 8.3 Forming AI Teams
• 8.4 Resources for Learning and Development in AI