This course concludes the role-based training for machine learning (ML) engineers on Amazon Web Services (AWS). In this course, you will recap the machine learning lifecycle and the skills you built across data preparation, model development, deployment, and operations. This course provides a consolidated review of the key concepts, AWS services, and generative AI techniques covered throughout the training. You will also find curated resources and study materials, including a downloadable resource guide and links to AWS documentation, to support your continued learning and your ongoing work as an ML engineer.
AWS ML Engineer Associate Conclusion (ML Engineer)
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AWS ML Engineer Associate Conclusion (ML Engineer)
This course is part of AWS ML Engineer Associate Professional Certificate
Instructor: AWS Instructor
Included with Learn more
Gain insight into a topic and learn the fundamentals.
Advanced level
Recommended experience
1 hour to complete
Flexible schedule
Learn at your own pace
What you'll learn
Prepare data for ML and AI, including features, RAG documents, and fine-tuning datasets.
Choose, train, fine-tune, and evaluate ML models and foundation models.
Deploy and orchestrate ML and AI workflows using AWS services.
Details to know
Shareable certificate
Add to your LinkedIn profile
Recently updated!
November 2026
Assessments
1 assignment
Taught in English
See how employees at top companies are mastering in-demand skills
Build your Machine Learning expertise
This course is part of the AWS ML Engineer Associate Professional Certificate
When you enroll in this course, you'll also be enrolled in this Professional Certificate.
- Learn new concepts from industry experts
- Gain a foundational understanding of a subject or tool
- Develop job-relevant skills with hands-on projects
- Earn a shareable career certificate from Amazon Web Services
There is 1 module in this course
Earn a career certificate
Add this credential to your LinkedIn profile, resume, or CV. Share it on social media and in your performance review.
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