This introductory course on AI/ML will teach you the fundamentals of these rapidly evolving fields, including their definitions, key components, differences, types, applications, and ethical implications. You will also learn how to analyze real-world use cases and applications of AI/ML.
Skills Gained
- Define AI and ML and explain their key components and differences
- Identify and discuss the types and applications of AI/ML
- Summarize the basic concepts of machine learning
- Analyze real-world use cases and applications of AI/ML
- Evaluate the ethical implications of AI and develop strategies for building trust in AI systems
Outline
Introduction
- Course Objectives and Overview
- Brief History of AI and ML
Fundamental Concepts of Artificial Intelligence (AI)
- Definition and Components of AI
- Rule-based systems
- Learning systems
- Types of AI
- Narrow AI vs. General AI
- Reactive, Limited Memory, Theory of Mind, Self-aware AI
- AI vs Human Intelligence: Key Differences
Introduction to Machine Learning (ML)
- What is ML and Why it Matters
- Relationship between AI and ML
- Types of Machine Learning
- Supervised Learning
- Unsupervised Learning
- Reinforcement Learning
- Deep Learning
- Basic Concepts in ML
- Training data
- Model
- Prediction
Real-world Use Cases and Applications of AI/ML
- Everyday AI Applications
- Smart Assistants (e.g., Siri, Alexa)
- Recommendations (e.g., Netflix, Amazon)
- Healthcare
- Diagnosis and Imaging
- Personalized Medicine
- Transportation
- Autonomous Vehicles
- Route Optimization
- Finance
- Fraud Detection
- Robo-advisors
- Entertainment
- Music and Movie Creation
- Game AI
- Agriculture, Environment, and More
Trustworthy AI and Ethics
- Importance of Trust in AI
- Principles for Trustworthy AI
- Transparency
- Fairness
- Security
- Accountability
- Real-world Issues and Controversies
- Bias in AI
- Job Displacement
- Surveillance and Privacy
- Strategies for Building Trust in AI Systems
- Data Quality and Integrity
- Clear Communication with Users
- Inclusive Design and Testing
- Role of Regulation and Governance
- Group Activity: Discussing Ethical Scenarios
Preparing for an AI-Driven Future
- Understanding AI’s Potential Impact on Society
- Building AI Awareness in Various Fields
- Embracing Continuous Learning and Adaptation
- Interactive Discussion: How to Stay Updated and Involved
Conclusion and Recap
- Key Takeaways
- Further Resources and Learning Pathways