AWS Machine Learning Engineer Associate (MLA-C02) Exam Prep

★ UPDATED FOR MLA-C02 ★ This course now covers BOTH exam versions.

Amazon Bedrock and foundation models — the new content added in MLA-C02 — are covered in a dedicated section.

• Taking MLA-C01? Every domain of the current exam is covered. (Last day for C01: January 14, 2027)

• Taking MLA-C02? The added Amazon Bedrock section, updated exam overview, and updated practice test are ready for you.

Maintenance Mode: Services in maintenance mode are marked with special notes.

Important Notice: AWS AI certifications typically have a 3-month lead time for service updates to be reflected. Therefore, questions regarding recently changed services may still appear on the exam immediately after the transition.

[Course Description]

Welcome to the most comprehensive prep course for the AWS Certified Machine Learning Engineer - Associate exam.

This course is meticulously designed for developers, data analysts, and aspiring data scientists who want to validate their skills in building, training, tuning, and deploying Machine Learning (ML) models on the AWS cloud. This certification is the new standard for validating your practical ML skills on AWS.

We go far beyond just theory. This course provides a deep dive into the critical services and concepts you must know for this challenging associate-level certification. We will cover the complete machine learning lifecycle, from data ingestion and preparation to model training, evaluation, and deployment — and now, working with foundation models on Amazon Bedrock.

This course is your complete guide to mastering the exam domains and earning one of the industry's most valuable certifications.

[What's New in MLA-C02]

AWS is updating this certification, and the exam adds foundation models to its scope. The exam guide states that the exam validates your ability to work with both traditional machine learning models and foundation models. This course has been updated so that you are prepared either way:

• Amazon Bedrock: Foundation model capabilities, use cases, and the core features of Amazon Bedrock.

• Retrieval Augmented Generation (RAG): Building RAG applications with Knowledge Bases.

• Responsible AI: Applying safeguards with Guardrails.

• Model Selection & Evaluation: How to select a foundation model and evaluate it for your use case.

• Also updated: the exam overview section and the full-length practice test.

The exam duration and the passing score do not change in MLA-C02.

[What You Will Master]

In this course, you will gain hands-on expertise and deep technical knowledge across all exam domains:

• Core Machine Learning Services: Master Amazon SageMaker from end-to-end. This includes using SageMaker Studio, built-in algorithms, running training jobs, performing hyperparameter tuning (HPO), and deploying models for both real-time and batch inference.

• Foundation Models on AWS: Work with Amazon Bedrock, including foundation model selection, Knowledge Bases for RAG, Guardrails, and model evaluation — the new scope of MLA-C02.

• Data Preparation & Engineering: Learn to build robust data processing pipelines using AWS Glue, AWS Lambda, Amazon Kinesis, and Amazon S3 to prepare, clean, and transform your data for training.

• Model Training & Evaluation: Understand the ML pipeline in depth, including feature engineering, model training, and the key metrics used to evaluate model performance.

• Model Deployment & Operations: Master the art of deploying your trained models using SageMaker Endpoints. You'll also learn how to monitor their performance with Amazon CloudWatch and ensure your ML operations are secure and efficient.

• Security & Governance: Implement essential security using IAM roles and policies, network isolation with VPCs, and data encryption with AWS KMS to protect your models and data.

[Course Agenda]

This course is logically structured to build your knowledge from the ground up:

• Section 1: AWS Certification and Exam Preparation — Overview of AWS, exam overview for the ML Engineer - Associate (including the MLA-C01 to MLA-C02 changes), account creation, etc.

• Section 2: Fundamentals of AI and Machine Learning — Basic terminology of AI, ML, and Generative AI, fundamental knowledge, and the ML pipeline.

• Section 3: Deep Dive into AWS Services — This is the core of the course. We will review all essential AWS services, category by category, as they relate to the exam.

  • AI/ML: SageMaker, Bedrock, and other fully-managed services.

  • Management & Governance: Organizations, Systems Manager, CloudWatch, Config, CloudTrail, CloudFormation.

  • Security, Identity, Compliance: IAM, KMS, Secrets Manager, Macie.

  • Storage: S3, EFS, EBS, Storage Gateway.

  • Compute & Container: EC2, Auto Scaling, ECS, EKS, Lambda, AWS Batch.

  • Networking & Content Delivery: VPC, Network Firewall, CloudFront, Direct Connect.

  • Database: RDS, Aurora, Redshift, DynamoDB, ElastiCache.

  • Application Integration: API Gateway, SQS, SNS, EventBridge, Step Functions, MWAA.

  • Analytics: Lake Formation, Glue, Kinesis, Data Firehose, Managed Service for Apache Flink, Athena, EMR, OpenSearch, QuickSight.

  • Developer Tools: CodeBuild, CodeDeploy, CodePipeline.

• Section 4: Amazon Bedrock and Foundation Models (NEW - for MLA-C02) — Foundation model capabilities and use cases, Amazon Bedrock features, Knowledge Bases and RAG, Guardrails, and model selection and evaluation.

• Section 5: Practice Test — One Original Full-Length Practice Test (65 Questions), updated for MLA-C02.

• Section 6: Summary — We'll wrap up the course with key takeaways and final tips for exam day.

[Meet Your Instructor]

Hello, I am Maruchin Tech, from Sapporo, Japan.

With a background spanning over a decade in technology, I've been working in major firms, including the Renault-Nissan-Mitsubishi Alliance, Accenture, and NTT Data.

I have created +70 courses covering Cloud Computing, Programming, Python, and Machine Learning, which have reached +100,000 students on Udemy. As an IT consultant, I specialize in cloud computing solutions for leading corporations.

I hold all currently available AWS certifications (12x AWS Certified), and I am passionate about sharing my knowledge with you.

Join me in exploring the dynamic world of IT, where continuous learning and innovation open the door to endless possibilities. Let's embark on this journey together.

This course is your complete guide to mastering the exam domains and earning this in-demand certification.

I look forward to seeing you in the course!