Course Overview
Module 1: Introduction To Artificial Intelligence (AI)
- 1.1 What is Artificial Intelligence? Preview
- 1.2 A Brief History of AI Preview
- 1.3 Demystifying AI: Myths vs. Reality Preview
- 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 Preview
- 2.3 AI Technologies in Action: Simplified Examples Preview
- 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 Preview
- 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
Optional Module: AI Agents for Everyone
- 1. Understanding AI Agents
- 2. Case Studies
- 3. Hands-On Practice with AI Agents
Tools you will explore
- Runway ML
- SciPy
- AIVA
- Grammarly
