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

Preise & Trainingsmethoden

Online Training

Dauer
4 Tage

Preis
  • 3.190,– €
Classroom Training

Dauer
4 Tage

Preis
  • Österreich: 3.190,– €
  • Deutschland: 3.190,– €
  • Schweiz: CHF 3.500,–

Kurstermine

Instructor-led Online Training:   Kursdurchführung online im virtuellen Klassenraum.
FLEX Classroom Training (Hybrid-Kurs):   Kursteilnahme wahlweise vor Ort im Klassenraum oder online vom Arbeitsplatz oder von zu Hause aus.

Deutsch

Zeitzone: Mitteleuropäische Sommerzeit (MESZ)   ±1 Stunde

Online Training
Klassenraum-Option: Hamburg, Deutschland
Zeitzone: Mitteleuropäische Sommerzeit (MESZ)
Online Training
Klassenraum-Option: Zürich, Schweiz
Zeitzone: Mitteleuropäische Sommerzeit (MESZ)
Online Training
Klassenraum-Option: Berlin, Deutschland
Zeitzone: Mitteleuropäische Sommerzeit (MESZ)
Online Training
Klassenraum-Option: Zürich, Schweiz
Zeitzone: Mitteleuropäische Zeit (MEZ)
Online Training
Klassenraum-Option: Hamburg, Deutschland
Zeitzone: Mitteleuropäische Zeit (MEZ)

Englisch

Zeitzone: Mitteleuropäische Sommerzeit (MESZ)   ±1 Stunde

Online Training Zeitzone: British Summer Time (BST)

2 Stunden Differenz

Online Training
Klassenraum-Option: Kairo, Ägypten
Zeitzone: Osteuropäische Sommerzeit (OESZ)

3 Stunden Differenz

Online Training
Klassenraum-Option: Dubai, Vereinigte Arabische Emirate
Zeitzone: Gulf Standard Time (GST)

6 Stunden Differenz

Online Training Zeitzone: UTC+8
Online Training Zeitzone: Eastern Daylight Time (EDT)

7 Stunden Differenz

Online Training Zeitzone: Central Standard Time (CST)
Online Training Zeitzone: UTC+8
FLEX Classroom Training (Hybrid-Kurs):   Kursteilnahme wahlweise vor Ort im Klassenraum oder online vom Arbeitsplatz oder von zu Hause aus.

Europa

Deutschland

Hamburg
Berlin
Hamburg

Schweiz

Zürich
Zürich

Italien

Rom