The Machine Learning Pipeline on AWS

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.

Retail Price: $2,700.00

Next Date: 10/06/2020

Course Days: 4


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Skills Gained

  • 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 Can Benefit

  • 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

 


Course Details

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
Course Dates Course Times (EST) Delivery Mode GTR
10/6/2020 - 10/9/2020 12:00 PM - 8:00 PM Virtual Enroll
10/27/2020 - 10/30/2020 9:00 AM - 5:00 PM Virtual Enroll
11/16/2020 - 11/19/2020 9:00 AM - 5:00 PM Virtual Enroll
12/14/2020 - 12/17/2020 10:00 AM - 6:00 PM Virtual Enroll