MLOps Engineering on AWS

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MLOps Engineering on AWS Course Overview


The MLOps Engineering on AWS course provides an in-depth review of all the steps and skills required to deploy ML models on Amazon Web Services (AWS). This course is designed to help developers and engineers understand the challenges and best practices of MLOps.
This course covers the challenges of MLOps and the importance of using best practices and processes throughout the development life cycle. You’ll learn the fundamentals of how to set up a development pipeline, how to integrate machine learning into a continuous integration/ continuous delivery (CI/CD) workflow, and how to deploy ML models on AWS. In addition, you’ll learn about best practices for scaling ML/AI models and for monitoring and debugging mobile applications.
This course is ideal for developers, engineers, or data scientists looking to gain a practical understanding of MLOps on AWS. You should be familiar with basic AWS cloud concepts and have some experience in the development of machine learning models.
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The 1-on-1 Advantage
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Flexible Dates

  • • Choose Start Date
  • • Reschedule After Booking
  • • Weekend / Evening Option
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4-Hour Sessions

Destination Training
(Dubai/London/Sydney
New York/Delhi/Goa
Singapore)

Flexi
(On Demand Videos)

You will learn:

Module 1: Introduction to MLOps
  • 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
Live Online Training (Duration : 24 Hours)
We Offer :
  • 1-on-1 Public - Select your own start date. Other students can be merged.
  • 1-on-1 Private - Select your own start date. You will be the only student in the class.

1950 + If you accept merging of other students. Incl. Official Courseware
8 Hours
Week Days
Weekend

Start Time : At any time

12 AM
12 PM

1-On-1 Training is Guaranteed to Run (GTR)
Group Training
1700 Per Participant Incl. Official Courseware
Online
03 - 05 Apr 09:00 AM - 05:00 PM CST
(8 Hours/Day)
Online
01 - 03 May 09:00 AM - 05:00 PM CST
(8 Hours/Day)
Course Prerequisites

The prerequisites for MLOps Engineering on AWS Training are as follows:
• Basic knowledge in Machine Learning and Python programming
• Working experience in Linux-based Operating System
• Good understanding of Continuous Delivery and Continuous Integration using DevOps tools
• Familiarity with AWS Cloud Services
• Understanding of Containers (Docker and Kubernetes) and container orchestration
• Understanding of Infrastructure as Code concepts
• Experience in building CI/CD pipelines with Jenkins

Target Audience


The target audience for MLOps Engineering on AWS training would be technology professionals who have experience in building and deploying Machine Learning models, as well as individuals who want to obtain expertise in managing and executing an MLOps workflow on the AWS Cloud
This course is also geared towards teams in organizations developing an MLOps pipeline around their existing machine learning models to make them more automated and simplified
Specific roles that would benefit from this course include ML developers, ML engineers, data scientists, cloud engineers, DevOps engineers and operations professionals
This training is ideal for those who want to gain an in-depth understanding of the process, tools and technologies needed to design, execute and manage MLOps on AWS

Learning Objectives of MLOps Engineering on AWS


MLOps Engineering on AWS Training provides an understanding of the fundamentals, methods and best practices for helping developers and DevOps teams use automation, scalability and high availability in achieving a successful deployment of machine learning models on AWS.
The objectives of this training include:
1. Understand the core concepts of MLOps and the key components of its architecture
2. How to prepare, deploy, and operate ML models on AWS services, such as Amazon Sagemaker, Amazon EC2, and Amazon ECS
3. Configure data management and analytics pipelines on AWS
4. Deploy ML models in production on AWS layers
5. Monitor and optimize ML applications with Amazon Cloudwatch
6. Automate common tasks related to machine learning lifecycle using AWS CloudFormation and automation scripts
7. Understand the security and compliance requirements of deploying machine learning models to production on AWS.

Student Feedback  (Check Koenig Feedback on Trustpilot)

Q1 Say something about the Trainer? Q2 How is Koenig different from other training Companies? Q3 Will you come back to Koenig for training ?
Student Name Feedback
Abu
United States
A1. Yes, she was very clear & a strong mastery of both English & Azure platforms hence following was easy. She was also patient and was answering every question asked, she also shared material & tips on how to pass the exam, Well done, and keep it up.
Nick Barker
United States
A1. Calm and understanding, she not only kept the course running well but also took time to help those with lots of questions. Very well done.
Robin Johnson
United States
A2. Individual attention during training, excellent customer service and coordination. Neha has been ever so helpful and is definitely an asset to Koenig.
Shivani Prasad
United States
A1. The trainer was great and his teaching methods were incredible. He used different teaching methods to ensure I was learning well. A fun trainer with lots of patience and understanding.
Adam
United States
A1. The trainer was very knowledgeable and well prepared about the presentation/training subject, with a positive attitude towards students and making every effort in answering questions during the training session. Top-notch service!
Suresh
United States
A1. Exceptional... recommend to everyone!
Shyam Vaddakapett
United States
A1. My trainer, Mohit Kakkar was excellent as he focused on hands-on assignments to supplement the concepts of AZ 900. The training coordinator Jasmeet as well as the ops manager Sheshadri are also very professional and customer-centric. I recommend Koenig for training courses, and I will take some more courses with them soon.
Gilles Chirlias
United States
A1. Chavi was a great teacher, I have learned a lot from her. I would like to have her for the next training, which would be the AZ 301 and AZ 500.
Abdulrahman Saad Alshahrani
United States
A1. Excellent trainer. I will take another course with him someday. He deserves a good appreciation from his Manager.
Anonymous
United States
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FAQ's

You can pay through debit/credit card or bank wire transfer.
You will receive the digital certificate post training completion via learning enhancement tool after registration.
Yes, we do. For details go to flexi
Yes you can.
1-on-1 Public - Select your start date. Other students can be merged.
1-on-1 Private - Select your start date. You will be the only student in the class.
Yes, course requiring practical include hands-on labs.
Buy-Now. Pay-Later option is available using credit card in USA and India only.
Yes you can request your customer experience manager for the same.
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You can request a refund if you do not wish to enroll in the course.
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Yes, we also offer weekend classes.
It is recommended but not mandatory. Being acquainted with the basic course material will enable you and the trainer to move at a desired pace during classes.You can access courseware for most vendors.
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The Fee includes:
  • Official courseware
Yes, Koenig Solutions is a AWS Learning Partner
Schedule for Group Training is decided by Koenig. Schedule for 1-on-1 is decided by you.
In 1-on-1 you can select your own schedule, other students can be merged but you select the schedule. Choose 1-on-1 if published schedule do not meet your requirement. If you also want a private session, opt for 1-on-1 Public.
Yes.
No, it is not included.

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