Course Overview
The AI+ Everyone course offers a comprehensive journey through the landscape of artificial intelligence, covering fundamental principles, technological advancements, real-world applications, project workflows, ethical considerations, generative AI, and preparation for an AI-driven future. Participants gain insights into diverse AI technologies and their practical implications across industries, alongside discussions on ethics and societal impact. The course culminates with practical guidance for starting with AI, providing resources for further exploration. Overall, participants are equipped with a holistic understanding of AI, empowering them to navigate its opportunities and challenges in today's rapidly evolving technological landscape.
Prerequisites
- Understand the basics of digital technologies and how they affect life
- Awareness of ethical principles and societal impact of technology
- Curiosity and openness to learning about new concepts and technologies
Course Objectives
- AI Project Workflow Management
- Students will learn to manage AI project workflows from data collection and preprocessing to model building, evaluation, and deployment.
- Ethical Decision-making in AI
- Students will critically examine AI technology and applications' ethical considerations. This includes identifying ethical issues, apply ethical frameworks, and make informed, societally beneficial judgments.
- Creativity and Innovation with Generative AI
- Students will examine how generative AI promotes creativity and innovation. This involves deep learning-based generative models to generate new ideas, designs, and content.
- Critical thinking and problem-solving
- Students will improve their critical thinking and problem-solving skills, evaluate approaches, and create innovative solutions, encouraging innovation and adaptability in AI problem-solving.
Outline: AI+ Everyone (AIEV)
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