You learn about each phase of the pipeline through presentations and demonstrations by the trainers and apply this knowledge to implement a project to solve one of three business problems: fraud detection, recommendation engines, or flight delays.
By the end of the course, you will have successfully built, trained, evaluated, tuned, and deployed an ML model using Amazon SageMaker that solves your selected business problem.
Module 0: Introduction
Module 1: Introduction to Machine Learning and the ML Pipeline
Module 2: Introduction to Amazon SageMaker
Module 3: Problem Formulation
Checkpoint 1 and Answer Review
Module 4: Preprocessing
Checkpoint 2 and Answer Review
Module 5: Model Training
Module 6: Model Evaluation
Checkpoint 3 and Answer Review
Module 7: Feature Engineering and Model Tuning
Module 8: Deployment
This course includes instructor lecture, presentations, hands-on labs, demonstrations, and group exercises/discussions.
This course is intended for the following job roles:
We recommend that attendees of this course have the following prerequisites:
and have attended the following course (or equivalent knowlege):
The training is carried out in cooperation with an authorized training partner.
For the purpose of implementation, participant data will be transferred to the training partner and the training partner assumes responsibility for the processing of these data.