AWS Certified Machine Learning Engineer - Associate Course Overview

The Exam Prep: AWS Certified Machine Learning Engineer – Associate (MLA-C01) course offers a comprehensive review of the exam topics. It helps candidates validate their ability to build and manage ML solutions on AWS. Learners will explore domain-specific knowledge, analyze exam-style questions, and understand how to apply ML engineering best practices on the AWS platform.

After completing Machine Learning Engineer - Associate Course, participants will be able to:

  • Identify the scope and content tested in the AWS Certified Machine Learning Engineer – Associate exam.
  • Practice with MLA-C01 exam-style questions to evaluate and enhance your test preparation strategy.
  • Review real-world use cases and distinguish between similar scenarios to apply the correct solutions.

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Key Features of MLA-C01 AWS Machine Learning Engineer - Associate Training:

  • Complete Exam Coverage
    Addresses all four domains of the MLA-C01 exam, including data preparation, model development, deployment, and monitoring.

  • Practical Question Walkthroughs
    Offers hands-on practice with AWS certification exam-style questions and explanations to reinforce core concepts.

  • Real-World ML Use Cases
    Includes examples such as fraud detection, sentiment analysis, and recommendations to contextualize ML on AWS.

  • Certification Readiness Strategies
    Provides MLA C01 exam tips, preparation strategies, and techniques to identify and avoid common pitfalls.

Who Should Attend AWS Machine Learning Engineer Associate Training?

  • ML Engineers using AWS for production ML workloads
  • Backend Software Developers
  • DevOps Engineers
  • Data Engineers
  • Data Scientists

Prerequisites of AWS Certified Machine Learning Engineer Course:

    While there are no mandatory prerequisites, it is recommended that participants have:
  • General IT Knowledge
  • Upto1 year of experience in ML-related roles
  • Basic understanding of common ML algorithms and their applications
  • Familiarity with data engineering (data formats, ingestion, transformation)
  • Proficiency in querying and transforming data
  • Knowledge of modular code development, CI/CD, debugging
  • Experience in provisioning and monitoring ML resources

      Recommended AWS Knowledge
  • Upto1 year of experience using Amazon SageMaker and other AWS ML services
  • Knowledge of SageMaker capabilities and AWS algorithms
  • Familiarity with AWS storage and processing tools for ML data
  • Deployment experience with AWS infrastructure
  • Understanding of AWS logging, monitoring, orchestration, and CI/CD
  • Awareness of AWS security practices (IAM, encryption, data protection)

    • Why choose CloudThat as your AWS certification training partner?

    • Expert Instructors: CloudThat's courses are led by industry experts with extensive experience in AI and AWS, ensuring high-quality instruction.
    • Hands-On Learning: Emphasis on practical, hands-on labs and real-world demos to provide participants with valuable, applicable skills.
    • Comprehensive Curriculum: Courses cover a wide range of topics, from introductory concepts to advanced implementation, offering a well-rounded learning experience.
    • Focus on Responsible AI: Training includes responsible AI principles, ensuring ethical practices and compliance with industry standards.
    • Career Advancement: CloudThat's training programs are designed to enhance career prospects, preparing participants for various roles in AI and machine learning.
    • Post-Training Support: CloudThat offers post-training support, additional resources, and forums for ongoing learning and development

    Course Outline Download Course Outline

    • Ingest and store data.
    • Transform data and perform feature engineering.
    • Ensure data integrity and prepare data for modeling.

    • Choose a modeling approach.
    • Train and refine models.
    • Analyze model performance.

    • Select deployment infrastructure based on existing architecture and requirements.
    • Create and script infrastructure based on existing architecture and requirements.
    • Use automated orchestration tools to set up continuous integration and continuous delivery (CI/CD) pipelines.

    • Monitor model interference.
    • Monitor and optimize infrastructure costs.
    • Secure AWS resources.

    Certification Details:

      AWS Certified Machine Learning – Associate

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    Course ID: 25299

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    FAQs:

    This training helps prepare you for roles such as Machine Learning Engineer, MLOps Engineer, Data Scientist, AI/ML Developer, ML Platform Engineer, and Cloud ML Specialist.

    In India, entry-level ML engineers earn between ₹8–₹15 lakhs per annum, while professionals with deeper AWS and MLOps expertise can earn ₹20–₹40 lakhs or more, especially in high-demand industries.

    You will strengthen your understanding of the full ML lifecycle on AWS, including data preparation, model building and evaluation, deployment, monitoring, and automation using SageMaker and other AWS services.

    This course provides exam-focused preparation and practical insights, helping you validate your skills and transition into more advanced ML engineering or cloud AI roles that require AWS proficiency.

    Yes. This course is specifically aligned with the AWS Certified Machine Learning Engineer – Associate (MLA-C01) exam and supports your preparation with domain-based content and exam-style questions.

    While not mandatory, it is recommended that participants have 1+ year of experience in ML or backend/cloud engineering, and familiarity with SageMaker, Python, data processing, and basic AWS services.

    Yes. Learners typically gain access to exam resources such as sample questions, recommended study guides, and discussion forums for continued support toward certification success.

    This is an exam prep course focused on theoretical understanding and exam strategies. It includes question walkthroughs, discussions, and use case analysis rather than hands-on labs.

    You will receive a certificate of completion from AWS Training, which confirms your participation but is distinct from the official AWS certification.

    You can register for the exam through the AWS Certification Portal, where you can select your exam date and test center or choose online proctoring.

    Enquire Now