Elements of AI - Building AI
"Building AI" offers a flexible online learning experience suitable for anyone interested in understanding the practical applications of artificial intelligence. Covering topics like machine learning and neural networks, the course accommodates learners at various skill levels, from introductory multiple-choice exercises to advanced Python programming. Through real-life examples, participants gain insight into how AI methods are utilized across different fields. Students can craft and present their AI ideas to the community upon completion.
Chapters
Chapter 1 - Getting Started With AI
- Why AI matters
- Optimization
- Hill climbing
Chapter 2 - Deailing With Uncertainty
- Probaility fundamentals
- The Bayes Rule
- Native Bayers classifier
Chapter 3 - Machine Learning
- Linear regression
- The neasest neighbor method
- Working with text
- Overfitting
Chapter 4 - Neural Networks
- Logicistic regression
- From logistic regression to neural networks
- Deep learning
Chapter 5 - Conclusion
• Summary
• Your AI idea
• AI idea gallery