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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.

Intended Audience

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

Delivery Method

This course is delivered through a mix of:

Instructor-led training
Hands-on labs
Demonstrations
Group exercises

We recommend that attendees of this course have the following prerequisites:

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

In this course, you will learn how 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

Module 1: Introduction to Machine Learning and the ML Pipeline

Overview of machine learning, including use cases, types of machine learning, and key concepts
Overview of the ML pipeline
Introduction to course projects and approach

Module 2: Introduction to Amazon SageMaker

Introduction to Amazon SageMaker
Demo: Amazon SageMaker and Jupyter notebooks
Lab 1: Introduction to Amazon SageMaker

Module 3: Problem Formulation

Overview of problem formulation and deciding if ML is the right solution
Converting a business problem into an ML problem
Demo: Amazon SageMaker Ground Truth
Hands-on: Amazon SageMaker Ground Truth
Problem Formulation Exercise and Review
Project work for Problem Formulation

Day Two

Recap and Checkpoint #1

Module 4: Preprocessing

Overview of data collection and integration, and techniques for data preprocessing and visualization
Lab 2: Data Preprocessing (including project work)

Module 5: Model Training

Choosing the right algorithm
Formatting and splitting your data for training
Loss functions and gradient descent for improving your model
Demo: Create a training job in Amazon SageMaker

Day Three

Recap and Checkpoint #2

Module 6: Model Training

How to evaluate classification models
How to evaluate regression models
Practice model training and evaluation
Train and evaluate project models
Lab 3: Model Training and Evaluation (including project work)
Project Share-Out 1

Module 7: Feature Engineering and Model Tuning

Feature extraction, selection, creation, and transformation
Hyperparameter tuning
Demo: SageMaker hyperparameter optimization

Day Four

Lab 4: Feature Engineering (including project work)

Recap and Checkpoint #3

Module 8: Module Deployment

How to deploy, inference, and monitor your model on Amazon SageMaker
Deploying ML at the edge

Module 9: Course Wrap-Up

Project Share-Out 2
Post-Assessment
Wrap-up

Why have you chosen us?

I have attended a training from Bilginc IT Academy before and I was satisfied.

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Machine Learning Pipelines on AWS Training Course in Germany

The Federal Republic of Germany is the second most populous country in Europe and is located in Central Europe. The official language of the country is German. Germany is one of the richest countries in the world. The main exports of the country include motor vehicles and iron and steel products.

Here are some fun facts about Germany:
The fairy tale writer, the Brothers Grimm, came from Germany and wrote many famous stories such as Cinderella, Snow White, and Sleeping Beauty.
Germany is home to the largest theme park in Europe, the Europa-Park.
The famous composer Ludwig van Beethoven was born in Germany.
The Autobahn, the German highway system, is known for having no general speed limit.

Berlin was divided by the Berlin Wall from 1961 to 1989. Known for its street art, Berlin has many colorful murals and graffiti throughout the city. Also, Berlin is home to many famous museums, such as the Pergamon Museum and the Museum Island. Many clubs and bars stay open until the early hours of the morning in this big city.

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The country's capital and largest city is Berlin, however Frankfurt is considered to be the business and financial center of Germany. It is home to the Frankfurt Stock Exchange, the European Central Bank, and many other financial institutions. Because of its central location within Europe and its status as a major financial hub, Frankfurt is often referred to as the "Mainhattan," a play on the city's name and its association with the Manhattan financial district in New York City.

Frankfurt is also a major transportation hub, with the largest airport in Germany and one of the largest in Europe, Frankfurt Airport. Additionally, it is a popular destination for tourists, with its historic city center, beautiful parks, and vibrant cultural scene.

Some of the top German technology companies like Siemens AG, Bosch, SAP SE, Deutsche Telekom, Daimler AG and Volkswagen has business centers in Frankfurt. The country has a strong tradition of engineering and innovation, and is home to many other world-class technology companies and research institutions.

Tailored to meet the specific needs of Germany, Bilginç IT Academy combines cutting-edge training methodologies with our comprehensive range of Certification Exam preparation courses and accredited corporate training programs. Experience a transformative approach to IT training that will redefine your expectations.

Machine Learning Pipelines on AWS Training in Germany

Upcoming Trainings

Machine Learning Pipelines on AWS Training in Germany

Prerequisites

What You Will Learn

Outline

3 REASONS WHY AWS IS THE LEADING CLOUD PLATFORM

Upcoming Trainings