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Elements of AI - Building AI

Building AI a flexible online course for anyone who wants to learn about the practical methods that make artificial intelligence a reality. You will get a solid introduction to for example machine learning and neural networks, and you will learn where and how AI methods are applied in real life. It is easy to move freely between the three difficulty levels, from multiple choice exercises to programming with Python – depending on whether you know programming or not. As a result of this course, you will be able to craft your own AI idea and present it to the community. Doing the online course is free of charge, but you can purchase the Building AI certificate to reward yourself for the effort.

https://buildingai.elementsofai.com/

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

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