Course Overview
Learn how to use the machine learning (ML) pipeline with Amazon SageMaker with hands-on exercises and four days of instruction. You will learn how to frame your business problems as ML problems and use Amazon SageMaker to train, evaluate, tune, and deploy ML models. Hands-on learning is a key component of this course, so you’ll choose a project to work on, and then apply the knowledge and skills you learn to your chosen project in each phase of the pipeline. You’ll have a choice of projects: fraud detection, recommendation engines, or flight delays.
Course Objectives
Select and justify the appropriate ML approach for a given business problem
Use the ML pipeline to solve a specific business problem
Train, evaluate, deploy, and tune an ML model in Amazon SageMaker
Describe some of the best practices for designing scalable, cost-optimized, and secure ML pipelines in AWS
Apply machine learning to a real-life business problem after the course is complete
Who Should Attend?
- Developers
- Solutions architects
- Data engineers
- Anyone who wants to learn about the ML pipeline via Amazon SageMaker, even if you have little to no experience with machine learning
- Top-rated instructors: Our crew of subject matter experts have an average instructor rating of 4.8 out of 5 across thousands of reviews.
- Authorized content: We maintain more than 35 Authorized Training Partnerships with the top players in tech, ensuring your course materials contain the most relevant and up-to date information.
- Interactive classroom participation: Our virtual training includes live lectures, demonstrations and virtual labs that allow you to participate in discussions with your instructor and fellow classmates to get real-time feedback.
- Post Class Resources: Review your class content, catch up on any material you may have missed or perfect your new skills with access to resources after your course is complete.
- Private Group Training: Let our world-class instructors deliver exclusive training courses just for your employees. Our private group training is designed to promote your team’s shared growth and skill development.
- Tailored Training Solutions: Our subject matter experts can customize the class to specifically address the unique goals of your team.
Course Prerequisites
There are no prerequisites for this course.
Agenda
1 - Day 1
- Module 0: Introduction
- Module 1: Introduction to Machine Learning and the ML Pipeline
- Module 2: Introduction to Amazon SageMaker
- Module 3: Problem Formulation
2 - Day 2
- Module 3: Problem Formulation (continued)
- Module 4: Preprocessing
3 - Day 3
- Module 5: Model Training
- Module 6: Model Evaluation
4 - Day 4
- Module 7: Feature Engineering and Model Tuning
- Module 8: Deployment