AWS Machine Learning Foundations

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What Will You Learn?

Learn the basics of Machine Learning and how to create and assess models. Acquire sought-after skills for businesses tackling AI challenges. Dive into advanced areas like computer vision, reinforcement learning, and generative AI. Get hands-on experience with AWS AI Devices like AWS DeepLens, DeepRacer, and DeepComposer. Master the process of preparing, building, training, and deploying top-notch ML models using Amazon SageMaker. Also, pick up best practices for object-oriented programming.

About This Course

Provider: Udacity
Format: Online
Duration: 11 hours to complete [Approx]
Target Audience: Beginners
Learning Objectives: After completing this free course, you'll gain a solid understanding of Machine Learning concepts and practical applications.
Course Prerequisites: NA
Assessment and Certification: NA
Instructor: AWS
Key Topics: Machine Learning, Machine Learning with AWS, OOP, Data Science, AI fluency, AWS deepracer, AWS deepcomposer
Topic Covered: 
  1. - What is Machine Learning?
  2. - Components of Machine Learning
  3. - Build a Dataset
  4. - Model Training
  5. - Model Evaluation
  6. - Model Inference
  7. - Machine Learning with AWS
  8. - AWS Account Requirements
  9. - Reinforcement Learning and Its Applications
  10. - Reinforcement Learning with AWS DeepRacer
  11. - Introduction to Generative AI
  12. - GANs with AWS DeepComposer
  13. - AR-CNN with AWS DeepComposer
  14. - Writing Modular Code
  15. - Docstrings
  16. - Model Versioning
  17. - Testing
  18. - Testing and Data Science
  19. - Unit Tests
  20. - Procedural vs. object-oriented programming
  21. - Class, object, method, and attribute
  22. - OOP syntax
  23. - Inheritance
  24. - Inheritance probability distribution
  25. - Organizing into modules
  26. - Advanced OOP topics
  27. - Making a package
  28. - Virtual environments
  29. - Putting code on PyPi

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