In this machine learning course, you will learn about the machine learning lifecycle, and how to use AWS services at every stage. Additionally, you will discover the diverse sources for machine learning models and learn techniques to evaluate their performance. You will also understand the importance of machine learning operations (MLOps) in streamlining the development and deployment of your machine learning projects.
Who should attend
This course is intended for the following:
- Individuals interested in machine learning and artificial intelligence, independent of a specific job role
Course Prerequisites
Developing Machine Learning Solutions is part of a series that facilitates a foundation on artificial intelligence, machine learning, and generative AI. If you have not done so already, it is recommended that you complete these two courses:
- Fundamentals of Machine Learning and Artificial Intelligence
- Exploring Artificial Intelligence Use Cases and Applications
What you will learn
In this course, you will learn how to do the following:
- Describe the components of machine learning lifecycle.
- Identify relevant AWS services and features for each stage of the ML lifecycle.
- Explain the types of data used to train artificial intelligence (AI) models.
- Understand sources of machine learning models.
- Understand model performance metrics.
- Describe methods to use a model in production.
- Understand fundamental concepts of MLOps.
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