When does class start/end?
Class hours may vary, please reach out to contact@ascendientlearning.com if you have any questions.
Machine Learning Engineering on AWS
Machine Learning (ML) Engineering on Amazon Web Services (AWS) is a 3-day intermediate course designed for ML professionals seeking to learn machine learning engineering on AWS. Participants learn to...
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$2,190 USD
Duration
3 days
Course Code
AWS-MLENG
Available Formats
Classroom, Virtual
Upcoming Course Dates
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Aug 5, 2026 - Aug 7, 2026 (3 days)
Live Virtual | 9:00AM – 5:00PM EDT Language English Select from 1 option(s) below Live Virtual | 9:00AM – 5:00PM EDT- Enroll
- Enroll Add to quote
-
Oct 27, 2026 - Oct 29, 2026 (3 days)
Live Virtual | 9:00AM – 5:00PM EDT Language English Select from 1 option(s) below Live Virtual | 9:00AM – 5:00PM EDT- Enroll
- Enroll Add to quote
-
Overview
Course Description
Machine Learning (ML) Engineering on Amazon Web Services (AWS) is a 3-day intermediate course designed for ML professionals seeking to learn machine learning engineering on AWS. Participants learn to build, deploy, orchestrate, and operationalize ML solutions at scale through a balanced combination of theory, practical labs, and activities. Participants will gain practical experience using AWS services such as Amazon SageMaker AI and analytics tools such as Amazon EMR to develop robust, scalable, and production-ready machine learning applications.
Skills Gained
In this course, you will learn to do the following:
- Explain ML fundamentals and its applications in the AWS Cloud.
- Process, transform, and engineer data for ML tasks by using AWS services.
- Select appropriate ML algorithms and modeling approaches based on problem requirements and model interpretability.
- Design and implement scalable ML pipelines by using AWS services for model training, deployment, and orchestration.
- Create automated continuous integration and delivery (CI/CD) pipelines for ML workflows.
- Discuss appropriate security measures for ML resources on AWS.
- Implement monitoring strategies for deployed ML models, including techniques for detecting data drift.
Who Can Benefit
training machine learning engineers who might have little prior experience with AWS. Other roles that can benefit from this training are DevOps engineer, developer, and SysOps engineer.
Prerequisites
Recommended previous knowledge
- Familiarity with basic machine learning concepts
- Working knowledge of Python programming language and common data science libraries such as NumPy, Pandas, and Scikit-learn
- Basic understanding of cloud computing concepts and familiarity with AWS
- Experience with version control systems such as Git (beneficial but not required)
Course Details
Course Details
Module 0: Course Introduction
Module 1: Introduction to Machine Learning (ML) on AWS
- Topic A: Introduction to ML
- Topic B: Amazon SageMaker AI
- Topic C: Responsible ML
Module 2: Analyzing Machine Learning (ML) Challenges
- Topic A: Evaluating ML business challenges
- Topic B: ML training approaches
- Topic C: ML training algorithms
Module 3: Data Processing for Machine Learning (ML)
- Topic A: Data preparation and types
- Topic B: Exploratory data analysis
- Topic C: AWS storage options and choosing storage
Module 4: Data Transformation and Feature Engineering
- Topic A: Handling incorrect, duplicated, and missing data
- Topic B: Feature engineering concepts
- Topic C: Feature selection techniques
- Topic D: AWS data transformation services
- Lab 1: Analyze and Prepare Data with Amazon SageMaker Data Wrangler and Amazon EMR
- Lab 2: Data Processing Using SageMaker Processing and the SageMaker Python SDK
Module 5: Choosing a Modeling Approach
- Topic A: Amazon SageMaker AI built-in algorithms
- Topic B: Selecting built-in training algorithms
- Topic C: Amazon SageMaker Autopilot
- Topic D: Model selection considerations
- Topic E: ML cost considerations
Module 6: Training Machine Learning (ML) Models
- Topic A: Model training concepts
- Topic B: Training models in Amazon SageMaker AI
- Lab 3: Training a model with Amazon SageMaker AI
Module 7: Evaluating and Tuning Machine Learning (ML) models
- Topic A: Evaluating model performance
- Topic B: Techniques to reduce training time
- Topic C: Hyperparameter tuning techniques
- Lab 4: Model Tuning and Hyperparameter Optimization with Amazon SageMaker AI
Module 8: Model Deployment Strategies
- Topic A: Deployment considerations and target options
- Topic B: Deployment strategies
- Topic C: Choosing a model inference strategy
- Topic D: Container and instance types for inference
- Lab 5: Shifting Traffic A/B
Module 9: Securing AWS Machine Learning (ML) Resources
- Topic A: Access control
- Topic B: Network access controls for ML resources
- Topic C: Security considerations for CI/CD pipelines
Module 10: Machine Learning Operations (MLOps) and Automated Deployment
- Topic A: Introduction to MLOps
- Topic B: Automating testing in CI/CD pipelines
- Topic C: Continuous delivery services
- Lab 6: Using Amazon SageMaker Pipelines and the Amazon SageMaker Model Registry with Amazon SageMaker Studio
Module 11: Monitoring Model Performance and Data Quality
- Topic A: Detecting drift in ML models
- Topic B: SageMaker Model Monitor
- Topic C: Monitoring for data quality and model quality
- Topic D: Automated remediation and troubleshooting
- Lab 7: Monitoring a Model for Data Drift
Module 12: Course Wrap-up
Schedule
2 options available
-
Aug 5, 2026 - Aug 7, 2026 (3 days)
Live Virtual | 9:00AM – 5:00PM EDT Language English Select from 1 option(s) below Live Virtual | 9:00AM – 5:00PM EDT- Enroll
- Enroll Add to quote
-
Oct 27, 2026 - Oct 29, 2026 (3 days)
Live Virtual | 9:00AM – 5:00PM EDT Language English Select from 1 option(s) below Live Virtual | 9:00AM – 5:00PM EDT- Enroll
- Enroll Add to quote
FAQ
Does the course schedule include a Lunchbreak?
Classes typically include a 1-hour lunch break around midday. However, the exact break times and duration can vary depending on the specific class. Your instructor will provide detailed information at the start of the course.
What languages are used to deliver training?
Most courses are conducted in English, unless otherwise specified. Some courses will have the word "FRENCH" marked in red beside the scheduled date(s) indicating the language of instruction.
What does GTR stand for?
GTR stands for Guaranteed to Run; if you see a course with this status, it means this event is confirmed to run. View our GTR page to see our full list of Guaranteed to Run courses.
How do I find an Ascendient Learning training location?
We have training locations across the United States and Canada - View a complete list of classroom training locations.
Which delivery formats are available?
At Ascendient Learning, we offer training that is Instructor-Led, Online, Virtual, and Self-Paced.
Does Ascendient Learning deliver group training?
Yes, we provide training for groups, individuals and private on sites. View our group training page for more information.
What does vendor-authorized training mean?
As a vendor-authorized training partner, we offer a curriculum that our partners have vetted. We use the same course materials and facilitate the same labs as our vendor-delivered training. These courses are considered the gold standard and, as such, are priced accordingly.
Is the training too basic, or will you go deep into technology?
It depends on your requirements, your role in your company, and your depth of knowledge. The good news about many of our learning paths, you can start from the fundamentals to highly specialized training.
How up-to-date are your courses and support materials?
We continuously work with our vendors to evaluate and refresh course material to reflect the latest training courses and best practices.
Are your instructors seasoned trainers who have deep knowledge of the training topic?
Ascendient Learning instructors have an average of 27 years of practical IT experience and have also served as consultants for an average of 15 years. To stay current, instructors spend at least 25 percent of their time learning new, emerging technologies and courses.
Do you provide hands-on training and exercises in an actual lab environment?
Lab access is dependent on the vendor and the type of training you sign up for. However, many of our top vendors will provide lab access to students to test and practice. The course description will specify lab access.
Will you customize the training for our company’s specific needs and goals?
We will work with you to identify training needs and areas of growth. We offer a variety of training methods, such as private group training, on-site of your choice, and virtually. We provide courses and certifications that are aligned with your business goals.
How do I get started with certification?
Getting started on a certification pathway depends on your goals and the vendor you choose to get certified in. Many vendors offer entry-level IT certification to advanced IT certification that can boost your career. To get access to certification vouchers and discounts, please contact info@ascendientlearning.com.
Will I get access to content after I complete a course?
You will get access to the PDF of course books and guides, but access to the recording and slides will depend on the vendor and type of training you receive.
How do I request a W9 for Ascendient Learning?
View our filing status and how to request a W9.
Reviews
it was good and very informative. Instructure covered everything in detail.
Easy to use and exactly what I was looking for. Value for money was exceptional.
Concise and good to follow along. Although it is a lot to take in under a short period of time.
The tool provided to practice the course teachings is very functional and easy to use.
Overall it was a good bootcamp. A lot to cover so it is understandable that the pace had to be a little fast.
