AWS Certified Machine Learning Engineer Associate: Hands On!
Practice exam included! Master MLA-C01 / ME1-C01 AWS Machine Learning Engineer Exam: SageMaker, Bedrock, and AI Skills.
4.67 (2215 reviews)
25 736
students
23.5 hours
content
May 2025
last update
$89.99
regular price
What you will learn
Prepare confidently for the AWS Certified Machine Learning Engineer Associate exam.
Understand and apply key AWS machine learning services like SageMaker, Bedrock, and more.
Perform data preparation, feature engineering, and data validation for ML models.
Master hyperparameter tuning, model training, and deployment strategies on AWS.
Implement CI/CD pipelines and automation for scalable machine learning workflows.
Secure, monitor, and optimize AWS ML infrastructure for performance and cost-efficiency.
Course Gallery
Loading charts...
Comidoc Review
Our Verdict
AWS Certified Machine Learning Engineer Associate: Hands On! is a well-structured and comprehensive course that serves as an excellent reference guide. The practice exam is undoubtedly a standout feature, offering crucial preparation for certification. While the course occasionally stumbles with overly theoretical sections and content organization issues, its solid foundational knowledge of AWS machine learning services and extensive coverage of relevant topics position it as a valuable resource for learners seeking to master MLA-C01 materials.
What We Liked
- This comprehensive course offers an informative introduction to AWS machine learning services, making it an ideal starting point for learners new to AI/ML concepts.
- The inclusion of a practice exam is invaluable for MLA-C01 certification preparation, enabling you to gauge your readiness and identify areas requiring further study.
- Real-world examples and hands-on experience with Amazon SageMaker facilitate understanding of complex topics and resource management strategies.
- High-quality slides from Stephane Maarek contribute to a clear, concise revision tool for the exam.
Potential Drawbacks
- Some sections can feel theoretical and challenging to grasp, particularly in data transformation and data cleaning. More detailed explanations or practical demonstrations could enhance comprehension.
- Occasional reuse of content from other courses may result in some redundancy, potentially affecting engagement.
- Slide content organization, image usage, and phrase-heavy formatting in some instances demand improvement for better revision efficiency.
6125705
udemy ID
13/08/2024
course created date
21/08/2024
course indexed date
Bot
course submited by