Overview of Course

The "MLOps Engineering on AWS" course is designed to provide a comprehensive understanding of machine learning operations on AWS. This course covers the core principles of MLOps, including model training, deployment, and monitoring using AWS services.

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Course Highlights

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Learn from experienced AWS certified trainers

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Hands-on experience with real-world MLOps use cases

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In-depth coverage of AWS services 

Key Differentiators

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    Real-world Projects

    We work with experts to curate real business scenarios as training projects

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Skills You’ll Learn


Designing and implementing machine learning models on AWS


Building scalable and fault-tolerant machine learning systems


Applying DevOps best practices to machine learning workflows


Using AWS services for data processing, storage, and analytics


Monitoring and optimizing machine learning models in production

Training Options

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1-on-1 Training

USD 900 / INR 75000
  • Option Item Access to live online classes
  • Option Item Flexible schedule including weekends
  • Option Item Hands-on exercises with virtual labs
  • Option Item Session recordings and learning courseware included
  • Option Item 24X7 learner support and assistance
  • Option Item Book a free demo before you commit!
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Corporate Training

On Request
  • Option Item Everything in 1-on-1 Training plus
  • Option Item Custom Curriculum
  • Option Item Extended access to virtual labs
  • Option Item Detailed reporting of every candidate
  • Option Item Projects and assessments
  • Option Item Consulting Support
  • Option Item Training aligned to business outcomes
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Course Reviews


  • Machine learning operations
  • Goals of MLOps
  • From DevOps to MLOps
  • ML workflow
  • MLOps view of ML workflow
  • MLOps cases

  • Intro to build, train, and evaluate machine learning models
  • MLOps security
  • Apache Airflow
  • Kubernetes integration for MLOps
  • Amazon SageMaker for MLOps
  • Lab: Bring your own algorithm to an MLOps pipeline
  • Demonstration: Amazon SageMaker
  • Intro to build, train, and evaluate machine learning models
  • Lab: Code and serve your ML model with AWS CodeBuild
  • Activity: MLOps Action Plan Workbook

  • Introduction to deployment operations
  • Model packaging
  • Inference
  • Lab: Deploy your model to production
  • SageMaker production variants
  • Deploying to the edge
  • Lab: Conduct A/B testing

  • Lab: Troubleshoot your pipeline
  • The importance of monitoring
  • Monitoring by design
  • Lab: Monitor your ML model
  • Human-in-the-loop
  • Amazon SageMaker Model Monitor
  • Demonstration: Amazon SageMaker Pipelines, Model Monitor, model registry, and Feature Store
  • Solving the Problem(s)

  • Wrap-up                                                                             
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Target Audience:

  • Machine learning engineers
  • Data scientists
  • Developers interested in machine learning
  • Technical managers looking to implement machine learning in their organization
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  • Basic knowledge of machine learning concepts and Python programming
  • Familiarity with AWS services is recommended but not required
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Benefits of the course:

  • Hands-on experience with cutting-edge MLOps technologies on AWS
  • Learn from industry experts with real-world experience
  • Gain the skills needed to build and deploy machine learning models in production
  • Boost your career prospects with an in-demand skill set


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Exam details to pass the course:

  • There is no exam required to pass the course.
  • Participants will receive a certificate of completion upon finishing the course.
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Certification path:

  • Participants can pursue the AWS Certified Machine Learning – Specialty certification after completing this course.


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Career options after doing the course:

  • Machine learning engineer
  • Data scientist
  • MLOps engineer
  • Technical manager in machine learning projects

Why should you take this course from Skillzcafe:

Why should you take this course from Skillzcafe:
  • Bullet Icon Experienced and certified trainers with a proven track record of success
  • Bullet Icon Comprehensive curriculum covering all aspects of MLOps on AWS
  • Bullet Icon Hands-on experience with real-world use cases and projects
  • Bullet Icon Access to our online learning platform with 24/7 support


MLOps is a set of practices that combines machine learning and DevOps to improve the efficiency and effectiveness of machine learning workflows.

Basic knowledge of machine learning concepts and Python programming is recommended for this course.

Familiarity with AWS services is recommended, but not required. The course provides an overview of AWS services and hands-on experience with these services.

The duration of the course is 3 days.

Yes, you will receive a certificate of completion upon finishing the course. This certificate is recognized by industry leaders and can be added to your resume or LinkedIn profile.

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