Machine Learning Engineering on AWS
Transform your ML expertise into production-scale solutions on AWS. Learn to build, deploy, and operationalize machine learning applications using Amazon SageMaker and EMR. Perfect for ML professionals seeking AWS certification, this hands-on course delivers practical skills for implementing enterprise-grade ML solutions in this three-day course.
Training at a glance
Level
Intermediate
Duration
3 Days
Experience
Basic Programing
Average Salary
125,000
Labs
Yes
Level
Beginner
Duration
1 Day
Experience
No Experience
Average Salary
$85,666
Labs
Yes
Training Details
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.
Module 1: Day 1
Module 0: Course Introduction
Module 1: Introduction to Machine Learning (ML) on AWS
Module 2: Analyzing Machine Learning (ML) Challenges
Module 3: Data Processing for Machine Learning (ML)
Module 4: Data Transformation and Feature Engineering
Module 2: Day 2
Module 5: Choosing a Modeling Approach
Module 6: Training Machine Learning (ML) Models
Module 7: Evaluating and Tuning Machine Learning (ML) models
Module 8: Model Deployment Strategies
Module 3: Day 3
- Module 9: Securing AWS Machine Learning (ML) Resources
- Module 10: Machine Learning Operations (MLOps) and Automated Deployment with Amazon SageMaker Studio
- Module 11: Monitoring Model Performance and Data Quality
- Module 12: Course Wrap-up
We recommend that attendees of this course have the following:
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)
Upcoming Classes
We Offer More Than Just AWS Training
That’s because we provide everything you need to succeed. This is true for all of our courses.
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