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This Machine Learning Pipeline on AWS course from CloudThat teaches candidates how to use the iterative machine learning (ML) process pipeline to solve a real business problem in a project-based learning environment. Candidates taking up this Machine Learning Pipeline on AWS training also learn to solve one of three business problems, including recommendation engines, fraud detection, or flight delays.
By the end of the Machine Learning Pipeline AWS training and certification course, candidates are successfully trained to build, evaluate, tune, and deploy an ML model using Amazon SageMaker. Candidates with basic knowledge of Statistics will find this course helpful. This course comprises presentations, group exercises, demonstrations, and hands-on labs.
After completing this course, students will be able to:
To be Decided
We recommend that attendees of this Machine Learning Pipeline on AWS course must have:
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
Day 2
Checkpoint 1 and Answer Review
Module 4: Preprocessing
Day 3
Checkpoint 2 and Answer Review
Module 5: Model Training
Module 6: Model Evaluation
Day 4
Checkpoint 3 and Answer Review
Module 7: Feature Engineering and Model Tuning
Module 8: Deployment
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