The Machine Learning Pipeline on AWS (ML-PIPE)

 

Course Overview

This course explores how to use the machine learning (ML) pipeline to solve a real business problem in a project-based learning environment. Students will learn about each phase of the pipeline from instructor presentations and demonstrations and then apply that knowledge to complete a project solving one of three business problems: fraud detection, recommendation engines, or flight delays. By the end of the course, students will have successfully built, trained, evaluated, tuned, and deployed an ML model using Amazon SageMaker that solves their selected business problem.

Who should attend

This course is intended for:

  • Developers
  • Solutions Architects
  • Data Engineers
  • Anyone with little to no experience with ML and wants to learn about the ML pipeline using Amazon SageMaker

Certifications

This course is part of the following Certifications:

Prerequisites

We recommend that attendees of this course have:

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

Course Objectives

In this course, you will learn 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 using 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

Prices & Delivery methods

Online Training

Duration
4 days

Price
  • 3,190.— €
Classroom Training

Duration
4 days

Price
  • Germany: 3,190.— €
  • Switzerland: CHF 3,500.—

Schedule

Guaranteed date:   The course is guaranteed to run regardless of the number of participants. This excludes unforeseeable events (e.g. accident, illness of the trainer) which make it impossible to carry out the course.
Instructor-led Online Training:   Course conducted online in a virtual classroom.
FLEX Classroom Training (hybrid course):   Course participation either on-site in the classroom or online from the workplace or from home.

English

2 hours difference

Online Training
Classroom option: Cairo, Egypt
Time zone: Eastern European Summer Time (EEST)

7 hours difference

Online Training Time zone: Central Standard Time (CST)
Online Training Time zone: Central Standard Time (CST)
Online Training Time zone: UTC+8
FLEX Classroom Training (hybrid course):   Course participation either on-site in the classroom or online from the workplace or from home.

Germany

Hamburg

Switzerland

Zurich
Zurich
Zurich
Zurich
Zurich
Zurich
Zurich

If you can't find a suitable date, don't forget to check our world-wide FLEX training schedule.