Machine Learning Engineering on AWS Training
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.
Machine Learning Engineering on AWS
Course Overview
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.
Course Outline
- 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
Prerequisites
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)
Related training topics
Justify your training
Use this sample request letter — copy it into an email to your manager and personalize the bracketed details to make the case for the time and budget.
Sample training request letter
Subject: Request for AI & AI Security training from Applied Technology Academy
[Decision Maker Name],
I'm writing to request time and budget approval to complete Applied Technology Academy's course, Machine Learning Engineering on AWS Training. The information below outlines how this training benefits our organization, the tasks I'll be able to perform after completing it, and relevant cost and funding details.
Course Description
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. Applied Technology Academy is an award-winning, SBA-certified woman-owned training provider (est. 2008) whose instructors are active practitioners; the course is hands-on with virtual labs and a learn-by-doing methodology.
Course Objectives
Once I've completed the course, I'll have hands-on, job-ready skills in ai & ai security that I can apply immediately to our work.
Expected Organizational Benefits
After completing this course, I will be better equipped to apply these skills directly to our projects, reduce our reliance on outside expertise, strengthen our team's capabilities, and share what I learn with colleagues.
Expected Cost & Funding
Course fee: [request an itemized quote at the link below]. Applied Technology Academy supports multiple funding paths that may reduce or cover this cost: GSA MAS purchasing and government purchase orders, military credentialing funding (Army CA, AF COOL, CG COOL), VA GI Bill and VR&E, ATA Flexible Spending, and student financing. Private team cohorts are available if colleagues should attend with me.
Conclusion
This training provides practical, hands-on experience I can apply immediately to strengthen our work in ai & ai security. Additional course information is available at https://appliedtechnologyacademy.com/aws-training/machine-learning-engineering-on-aws-training/.
Thank you for your consideration,
[Your Name]
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