The Machine Learning Pipeline on AWS

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.

Who Should Take This Course

AUDIENCE

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

PREREQUISITES

Basic knowledge of Python
Basic understanding of AWS Cloud infrastructure (Amazon S3 and Amazon CloudWatch)
Basic understanding of working in a Jupyter notebook environment

Why You Should Take This Course

This course will prepare you to:

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

Schedule

Course Outline

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

Module 3: Problem Formulation (continued)
Module 4: Preprocessing

Day 3

Module 5: Model Training
Module 6: Model Evaluation

Day 4

Module 7: Feature Engineering and Model Tuning
Module 8: Deployment

FAQs

Is there a discount available for current students?

UMBC students and alumni, as well as students who have previously taken a public training course with UMBC Training Centers are eligible for a 10% discount, capped at $250. Please provide a copy of your UMBC student ID or an unofficial transcript or the name of the UMBC Training Centers course you have completed. Asynchronous courses are excluded from this offer.

What is the cancellation and refund policy?

Student will receive a refund of paid registration fees only if UMBC Training Centers receives a notice of cancellation at least 10 business days prior to the class start date for classes or the exam date for exams.