MLOps Engineering on AWS:  Build, Automate and Deploy Scalable Machine Learning Pipelines in 2026.

  • Why get trained: Learn how to build and automate end-to-end ML pipelines using Amazon SageMaker, CI/CD tools and MLOps practices for model development and deployment.
  • Why it matters: MLOps skills enable teams to deploy reliable, repeatable and scalable ML workflows while improving collaboration across data, engineering and operations teams.
  • Who should attend: MLOps engineers, DevOps engineers, data engineers and technical professionals responsible for deploying and managing machine learning models on AWS.

Build production-ready machine learning capability and develop skills to automate, deploy and monitor ML solutions at scale. HRD Corp Claimable.

Explore the top Data and AI certifications for 2026. Be the professional businesses are searching for—get certified today!

Overview

Learn how to extend DevOps practices to build, train and deploy machine learning models.

  • This  course builds upon and extends the DevOps practice prevalent in software development to build, train, and deploy machine learning (ML) models.
  • The course stresses the importance of data, model, and code to successful ML deployments.
  • It will demonstrate the use of tools, automation, processes, and teamwork in addressing the challenges associated with handoffs between data engineers, data scientists, software developers, and operations.
  • The course will also discuss the use of tools and processes to monitor and take action when the model prediction in production starts to drift from agreed-upon key performance indicators.

Trainocate is an AWS Authorized Training Partner as well as the AWS Global Training Partner of the Year 2022-2025 is trusted by AWS to offer, deliver, and/or incorporate official AWS Training, including classroom and digital offerings.

Whether your team prefers to learn from live instructors, on-demand courses, or both, ATPs offer a breadth of AWS Training options for learners of all levels.

 

Skills Covered

  • Describe machine learning operations
  • Understand the key differences between DevOps and MLOps
  • Describe the machine learning workflow
  • Discuss the importance of communications in MLOps
  • Explain end-to-end options for automation of ML workflows
  • List key Amazon SageMaker features for MLOps automation
  • Build an automated ML process that builds, trains, tests, and deploys models
  • Build an automated ML process that retrains the model based on change(s) to the model code
  • Identify elements and important steps in the deployment process
  • Describe items that might be included in a model package, and their use in training or inference
  • Recognize Amazon SageMaker options for selecting models for deployment, including support for ML frameworks and built-in algorithms or bring-your-own-models
  • Differentiate scaling in machine learning from scaling in other applications
  • Determine when to use different approaches to inference
  • Discuss deployment strategies, benefits, challenges, and typical use cases
  • Describe the challenges when deploying machine learning to edge devices
  • Recognize important Amazon SageMaker features that are relevant to deployment and inference
  • Describe why monitoring is important
  • Detect data drifts in the underlying input data
  • Demonstrate how to monitor ML models for bias
  • Explain how to monitor model resource consumption and latency
  • Discuss how to integrate human-in-the-loop reviews of model results in production

Prerequisites

Required:

Target Audience

  • ML data platform engineers
  • DevOps engineers
  • Developers/operations staff with responsibility for operationalizing ML models

Course Curriculum

Module 0: Welcome

  • Course Introduction

Module 1: Introduction to MLOps

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

Module 2: MLOps Development

  • Intro to build, train, and evaluate machine learning models
  • MLOps security
  • Automating
  • 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

Module 3: MLOps Deployment

  • Introduction to deployment operations
  • Model packaging
  • Inference
  • Lab: Deploy your model to production
  • SageMaker production variants
  • Deployment strategies
  • Deploying to the edge
  • Lab: Conduct A/B testing
  • Activity: MLOps Action Plan Workbook

Module 4: Model Monitoring and Operations

  • 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)
  • Activity: MLOps Action Plan Workbook

Module 5: Wrap-up

  • Course review
  • Activity: MLOps Action Plan Workbook
  • Wrap-up

Dates & Locations

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June 24, 2026 - June 26, 2026

Location: Kuala Lumpur
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Availability: TBC
RM 5400 RM 4500
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June 24, 2026 - June 26, 2026

Location: Online
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RM 5400 RM 4500
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August 26, 2026 - August 28, 2026

Location: Kuala Lumpur
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RM 5400 RM 4500
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August 26, 2026 - August 28, 2026

Location: Online
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RM 5400 RM 4500
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October 21, 2026 - October 23, 2026

Location: Kuala Lumpur
Modal: ILT
Availability: TBC
RM 5400

October 21, 2026 - October 23, 2026

Location: Online
Modal: VILT
Availability: TBC
RM 5400

December 16, 2026 - December 18, 2026

Location: Kuala Lumpur
Modal: ILT
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RM 5400

December 16, 2026 - December 18, 2026

Location: Online
Modal: VILT
Availability: TBC
RM 5400
Trainocate exam and cert

Exam & Certification

There is no exam directly associated with this course. However, AWS offers an extensive portfolio of industry-recognized certifications that can help you stand out as a tech professional in 2026 and beyond. Achieving AWS credentials is one of the most effective ways to validate your skills and accelerate your career.

With our expert-led training, you’ll be prepared to:

  • Master in-demand capabilities across Cloud, Data & AI, and Cybersecurity — areas driving global digital transformation.
  • Prove your expertise with a globally respected credential recognized by employers worldwide.
  • Advance your career by enhancing your credibility, increasing your earning potential, and opening doors to new opportunities.

Explore our top AWS Certifications for 2026 and start building the skills that matter today.

Training & Certification Guide

The AWS Certified Machine Learning – Specialty certification is intended for individuals who perform a development or data science role. It validates a candidate’s ability to design, implement, deploy, and maintain machine learning (ML) solutions for given business problems.

  • Select and justify the appropriate ML approach for a given business problem
  • Identify appropriate AWS services to implement ML solutions
  • Design and implement scalable, cost-optimized, reliable, and secure ML solutions

  • 1-2 years of experience developing, architecting, or running ML/deep learning workloads on the AWS Cloud
  • The ability to express the intuition behind basic ML algorithms
  • Experience performing basic hyperparameter optimization
  • Experience with ML and deep learning frameworks
  • The ability to follow model-training best practices
  • The ability to follow deployment and operational best practices

  • Format: 65 questions; either multiple choice or multiple response
  • Type: Specialty
  • Delivery Method: Testing center or online proctored exam
  • Time: 180 minutes to complete the exam
  • Cost: 300 USD (Practice exam: 40 USD)
  • Language: Available in English, Japanese, Korean, and Simplified Chinese

Validate Your Skills with AWS Certification

Certification is the one of the best ways to validate your cloud skills. And AWS Certifications are industry-recognized credentials. And AWS Certifications, in particular, are industry-recognized credentials that showcase your expertise in the AWS Cloud. This e-book provides an overview of what you need to know to earn an AWS Certification, acting as your guide throughout the process. It will help you determine which AWS Certifications are right for you and show you how to prepare for and obtain them.

Training and Certification for your Machine Learning Journey

Organizations are struggling to find data scientists and developers with machine learning experience. Learn how you can become the machine learning problem-solver others look to. In this eBook, we’ll review the promise of machine learning and how innovations in training and certification give developers and data scientists an advantage by equipping them with the skills to help their organizations achieve success.

Innovate Securely and Confidently with AWS Training and Certification

Across nearly every industry, organizations are discovering a greater need to empower every employee with cloud security skills. This e-book will guide you on how AWS Training and Certification can help your organization innovate securely and confidently by offering flexible in-demand digital training that can help your teams build security skills quickly and comprehensively.

How people are bringing the possibilities of purpose-built databases to life

It’s time to push the limits of innovation by building your database of skills. The power of data has grown at an exponential rate over the last several years. It has created a new universe of possibilities for applications, services and beyond. In this e-book, we’ll introduce you to effective methods of building your database skills. We’ll help you start your journey and propel you into this new universe of data empowering you to explore and innovate throughout the ever-growing expanse of purpose-built database possibilities.

Accelerate Your Modernization Journey

Develop skills in designing, building and managing modern applications. As companies look to become more agile so they can innovate and respond to change faster and innovate rapidly, this inadvertently requires a different kind of application than what was common years ago. This e-book gives you insights on the importance of training and skilling to accelerate your company’s digital transformation.

Accelerate Migration with Comprehensive Cloud Skills Enablement

As benefits of the cloud like speed, scale and modernization have become more widely understood, the conversation at many organizations has shifted from “why cloud?” to “which cloud?” Thousands of companies, including GE, The Coca-Cola Company, BP, Enel, Samsung, News Corp, and 21st Century Fox, have found their answer with AWS.

AWS also helps provide the answer to another critical questions in your cloud journey: “How to get to the cloud in the fastest, most efficient way possible?” A transformative migration is now within your reach. Now you can learn how you can migrate with your confidence by building your team’s cloud skills with AWS Training and certification by downloading this e-book.

10 Reasons to learn the AWS Cloud

It does not matter you’re new to AWS Cloud services, seeking to update your cloud skills, or exploring a cloud-first strategy for your organization it’s time to make a plan. Download this free E-Book and learn how AWS Training can help you better understand how the AWS Cloud works and how you can troubleshoot with confidence and skill

Frequently Asked Questions

Build credibility

  • Skills validation – Earn an industry-recognized credential from AWS that validates expertise in building, training, tuning, and deploying machine learning models on AWS. Highlight your ability to innovate with machine learning solutions for your customers and business.
  • Confidence – Feel confident selecting and justifying the appropriate machine learning solution for a use case. With the AWS Certified Machine Learning – Specialty certification, your credential validates your expertise with machine learning on AWS.

Discover more opportunities

  • Recognition – Be recognized as an innovator ready to build and deploy machine learning solutions on AWS.
  • Job performance – Deliver value through designing and implementing scalable, cost-optimized, reliable, and secure machine learning solutions with the appropriate AWS services.

AWS Training and Certification helps you build and validate your cloud skills so you can get more out of the cloud. We offer both digital and classroom training—delivered virtually and in person—so you can choose to learn online at your own pace or learn best practices from an instructor. AWS Training and Certification offers prescriptive learning paths to get you started quickly. Progress along the path from foundational to intermediate training, and then dive deeper with advanced training to continue your learning.

Trainocate Malaysia offers technical role-based learning paths for architects, developers, and operations staff. We also offer a Cloud Practitioner learning path for business decision makers who want to learn AWS Cloud fundamentals. Additional solutions-based learning paths focus on topics like machine learning, storage, data analytics, and security.

You will learn directly from AWS experts who have domain experience and access to the latest AWS Cloud products, services, and teaching methods. This training will increase your credibility as someone who uses and makes decisions about cloud services. Building clouds skills through high-quality digital training can also support the credibility of your entire organization. When your technologists and strategists are well trained in cloud skills, they can more easily project confidence about your cloud strategy.

AWS Certification helps learners build credibility and confidence by validating their cloud expertise with an industry-recognized credential and organizations identify skilled professionals to lead cloud initiatives using AWS. Just like learning music theory enables you to jam, a strong grounding in cloud principles empowers you to creatively explore cloud options.

Having the skills and insight to act upon your creativity and inspiration is essential to discovering new business opportunities in the cloud and helping your organization innovate. You’ll be able to experiment with AWS Cloud services, quickly testing products and implementing strategies to determine what best delivers your organizational goals.

You don’t need to be a technologist to benefit from learning cloud basics. By learning the AWS Cloud, you’ll gain first-hand knowledge of how the cloud can support greater efficiency, flexibility, and opportunity for both you and your organization.

You’ll also gain confidence in your ability to consider cloud options, so you’re better informed when making business and management decisions involving the cloud. By investing in training, organizations can accelerate cloud adoption, achieve business objectives sooner, and overcome concerns related to cloud adoption. Also, comprehensively trained organizations are nearly three times more likely to use the cloud to jump-start innovation. They’re also nearly four times more likely to meet cloud ROI requirements, and over four times more likely to overcome operational and performance concerns.

Learn about each AWS Certification in our AWS Training and Certification blog post. To answer that question, you’ll need to consider your role and honestly evaluate your existing level of experience and knowledge across various areas of technical and cloud expertise. AWS offers four categories of certifications, three of which correspond to the amount of experience you have with the AWS Cloud. For Specialty certifications, the amount of recommended experience varies by certification.

Learn how to apply machine learning (ML), artificial intelligence (AI), and deep learning (DL) to your business, unlocking new insights and value with these recommended courses:

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In this course, learn how to solve a real-world use case with machine learning and produce actionable results using Amazon SageMaker. This course teaches you how to use Amazon SageMaker to cover the different stages of the typical data science process, from analyzing and visualizing a data set, to preparing the data and feature engineering, down to the practical aspects of model building, training, tuning and deployment.

AWS-DEEPL: Deep Learning on AWS

In this one-day Deep Learning on AWS course, you’ll learn cloud-based deep learning solutions on the AWS platform. You’ll learn how to run your models on the cloud using Amazon EC2‒based deep learning Amazon Machine Image (AMI) and Apache MXNet on AWS frameworks.

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