MLA-C01
AWS Certified Machine Learning Engineer - Associate
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The AWS Certified Machine Learning Engineer - Associate MLA-C01 exam is designed to validate the skills and technical ability required to implement machine learning (ML) workloads in production using Amazon Web Services (AWS). This AWS Certified Machine Learning Engineer - Associate certification is ideal for those looking to validate their technical expertise in deploying and maintaining machine learning models on AWS. It helps professionals position themselves for roles in ML engineering, MLOps, and data science, as well as building credibility in the growing field of machine learning and AI. The following MLA-C01 exam overview, target audience, domains and preparation material are valuable in your preparation.
AWS Certified Machine Learning Engineer - Associate MLA-C01 Exam Overview
| Category: | Associate |
| Exam Duration: | 130 minutes |
| Number of Questions: | 65 questions |
| Cost: | $150 |
| Minimum Passing Score: | 720 (out of 1000) |
| Testing Options: | Pearson VUE testing center or online proctored exam |
| Languages Offered: | English, Japanese, Korean, Simplified Chinese |
MLA-C01 Exam Target Audience
The MLA-C01 exam is targeted at individuals in roles such as:
Backend Software Developers
DevOps Engineers
Data Engineers
MLOps Engineers
Data Scientists
AWS Certified MLA-C01 Exam Domains
AWS Certified MLA-C01 exam domains cover the following details.
1. Data Preparation for Machine Learning (ML) (28%)
Techniques for ingesting, transforming, and validating data to ensure it's ready for modeling.
Data wrangling, dealing with missing values, and feature engineering.
2. ML Model Development (26%)
Selecting appropriate algorithms for ML problems.
Training models, hyperparameter tuning, evaluating performance, and model versioning.
3. Deployment and Orchestration of ML Workflows (22%)
Selecting deployment infrastructure and endpoints.
Provisioning compute resources and configuring auto-scaling.
Setting up CI/CD pipelines for automating ML workflows.
4. ML Solution Monitoring, Maintenance, and Security (24%)
Monitoring model performance and infrastructure health.
Detecting issues such as data drift or model degradation.
Managing security for ML systems, using access controls, and implementing best practices.
Practice AWS Certified MLA-C01 Exam preparation material from CertQueen
If you're preparing for the AWS Certified Machine Learning Engineer - Associate MLA-C01 exam, using exam preparation material from reliable sources like CertQueen can be an effective way to enhance your readiness. CertQueen provides a comprehensive collection of practice questions that closely simulate the actual exam environment, helping you familiarize yourself with the exam format and question types. These practice preparation material cover all the key domains of the MLA-C01 exam, including data preparation, ML model development, deployment, orchestration, and solution monitoring. By regularly testing yourself with CertQueen's preparation material, you can identify areas where you need further study and improve your time management skills.