MLOps Engineering on AWS Training

Live Online & Classroom Enterprise Certification Training

Could your Machine Learning (ML) workflow use some DevOps agility? MLOps Engineering on AWS will help you bring DevOps-style practices into the building, training, and deployment of ML models by learning from an expert AWS instructor.

COURSE BROCHURE DOWNLOAD PDF

Looking for a private batch ?

REQUEST A CALLBACK

Certified Trainer
Authorized Courseware
Completion Certificate from ATP

Enterprise Reporting
Lifetime Access
CloudLabs
24x7 Support
Real-time code analysis and feedback

What is MLOps Engineering on AWS Certification Training about?

This course builds upon and extends the DevOps methodology prevalent in software development to build, train, and deploy machine learning (ML) models. The course is based on the four-level MLOps maturity framework. It focuses on the first three levels, including the initial, repeatable, and reliable levels. The course emphasizes the importance of data, model, and code to successful ML deployments. It demonstrates 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 also discusses the use of tools and processes to monitor and take action when the model prediction in production drifts from agreed-upon key performance indicators.

What are the objectives of MLOps Engineering on AWS Certification Training ?

In this course, you will learn to:

Explain the benefits of MLOps
Compare and contrast DevOps and MLOps
Evaluate the security and governance requirements for an ML use case and describe possible solutions and mitigation strategies
Set up experimentation environments for MLOps with Amazon SageMaker
Explain best practices for versioning and maintaining the integrity of ML model assets (data, model, and code)
Describe three options for creating a full CI/CD pipeline in an ML context
Recall best practices for implementing automated packaging, testing, and deployment (data/model/code)
Demonstrate how to monitor ML-based solutions
Demonstrate how to automate an ML solution that tests, packages, and deploys a model in an automated fashion; detects performance degradation; and re-trains the model on top of newly acquired data

Who is MLOps Engineering on AWS Certification Training for?

This course is intended for:

MLOps engineers who want to productionize and monitor ML models in the AWS cloud
DevOps engineers who will be responsible for successfully deploying and maintaining ML models in production

What are the prerequisites for MLOps Engineering on AWS Certification Training?

We recommend that attendees of this course have:

AWS Technical Essentials (classroom or digital)
DevOps Engineering on AWS, or equivalent experience
Practical Data Science with Amazon SageMaker, or equivalent experience

Available Training Modes

Live Online Training

Classroom Training

3 Days

Course Outline Expand All

Expand All

Introduction to MLOps

Processes

People

Technology

Security and governance

MLOps maturity model

Initial MLOps: Experimentation Environments in SageMaker Studio

Bringing MLOps to experimentation

Setting up the ML experimentation environment

Demonstration: Creating and Updating a Lifecycle Configuration for SageMaker Studio

Hands-On Lab: Provisioning a SageMaker Studio Environment with the AWS Service Catalog

Workbook: Initial MLOps

Repeatable MLOps: Repositories

Managing data for MLOps

Version control of ML models

Code repositories in ML

Repeatable MLOps: Orchestration

ML pipelines

Demonstration: Using SageMaker Pipelines to Orchestrate Model Building Pipelines

Repeatable MLOps: Orchestration (continued)

End-to-end orchestration with AWS Step Functions

Hands-On Lab: Automating a Workflow with Step Functions

End-to-end orchestration with SageMaker Projects

Demonstration: Standardizing an End-to-End ML Pipeline with SageMaker Projects

Using third-party tools for repeatability

Demonstration: Exploring Human-in-the-Loop During Inference

Governance and security

Demonstration: Exploring Security Best Practices for SageMaker

Workbook: Repeatable MLOps

Reliable MLOps: Scaling and Testing

Scaling and multi-account strategies

Testing and traffic-shifting

Demonstration: Using SageMaker Inference Recommender

Hands-On Lab: Testing Model Variants

Reliable MLOps: Scaling and Testing (continued

Hands-On Lab: Shifting Traffic

Workbook: Multi-account strategies

Reliable MLOps: Monitoring

The importance of monitoring in ML

Hands-On Lab: Monitoring a Model for Data Drift

Operations considerations for model monitoring

Remediating problems identified by monitoring ML solutions

Workbook: Reliable MLOps

Hands-On Lab: Building and Troubleshooting an ML Pipeline

DOWNLOAD COURSE BROCHURE

Who is the instructor for this training?

The trainer for this MLOps Engineering on AWS Training has extensive experience in this domain, including years of experience training & mentoring professionals.

Reviews

My outlook on training changed completely after attending SpringPeople BPC training. The content, the trainer and infrastructure at SpringPeople were top notch and perfectly in tune with the industry requirements. Regardless to say, training is now something that I look forward to to. Kudos to everyone at SpringPeople!

Shweta Priya

Sony

I attended the 3-day AngularJs training at SpringPeople. The trainer was an industry veteran with vast experience in the subject. Notably, the hands-on training, and the Q&A session stood out. Overall, I found SpringPeople a great place to learn with excellent facilities and great trainers. Would recommend SpringPeople to my colleagues and friends.

Swati Singh

I attended the training on API Design for Mulesoft. The sessions were well planned and value-laden. I benefited immensely from the hands-on experience enabled through virtual labs. I would like to specifically commend the efficiency of the support team who were always available to resolve my concerns.

Nikhil Kohli

Stryker

I attended the jQuery training batch, conducted by Mr. Vijay, an SME who did a thorough coverage of all the essentials. He took us through concepts such as jQuery animations, event handlers, plugins, and jQuery-UI by small programs, very easily. The sessions were useful and well structured. By the end of the training, I was well equipped to develop a SPA on Product Management System. Overall, the learning experience at SpringPeople was great!

Heena Rajan

Mindtree