Learn what machine learning is and the steps involved in building and evaluating models. Gain in demand skills needed at businesses working to solve challenges with AI.
Learn the fundamentals of advanced machine learning areas such as computer vision, reinforcement learning, and generative AI. Get hands-on with machine learning using AWS AI Devices (i.e. AWS DeepLens, AWS DeepRacer, and AWS DeepComposer).
Learn how to prepare, build, train, and deploy high-quality machine learning (ML) models quickly with Amazon SageMaker and learn object-oriented programming best practices.
Welcome to the AWS Machine Learning Foundations Course
Meet your instructors,What you will learn,Pre-requisites
Introduction to Machine Learning
Differentiate between supervised and unsupervised learning,Identify problems that can be solved with machine learning,Describe commonly used algorithms including linear regression, logistic regression, and k-means,Describe how model training and testing works,Evaluate the performance of a machine learning model using metrics
Machine Learning with AWS
Identify AWS machine learning offerings and understand how different services are used for different applications,Explain the fundamentals of computer vision and provide examples of popular tasks,Describe how reinforcement learning works in the context of AWS DeepRacer,Explain the fundamentals of generative AI and its applications, and describe three famous generative AI models in the context of music and AWS DeepComposer
Software Engineering Practices, Part 1
Writing clean and modular code,Writing efficient code,Code refactoring,Adding meaningful documentation,Using version control
Software Engineering Practices, Part 2
Introduction to Object-Oriented Programming
Object-oriented programming syntax,Using object-oriented programming to make a Python package
Maryam Rezapoor, Eva Pagneux, Phu Nguyen, Juno Lee and Andrew Paster