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You will learn how to solve a real-world use case with Machine Learning (ML) and produce actionable results using Amazon SageMaker. This course walks through the stages of a typical data science process for Machine Learning from analyzing and visualizing a dataset to preparing the data, and feature engineering. Individuals will also learn practical aspects of model building, training, tuning, and deployment with Amazon SageMaker. Real life use case includes customer retention analysis to inform customer loyalty programs

Activities

This course includes presentations, group exercises, and hands-on labs.

Intended audience

This course is intended for:

Developers
Data Scientists

This course is intended for:

Developers
Data Scientists

In this course, you will:

Prepare a dataset for training
Train and evaluate a Machine Learning model
Automatically tune a Machine Learning model
Prepare a Machine Learning model for production
Think critically about Machine Learning model results

Module 1: Introduction to machine learning

Types of ML
Job Roles in ML
Steps in the ML pipeline

Module 2: Introduction to data prep and SageMaker

Training and test dataset defined
Introduction to SageMaker
Demonstration: SageMaker console
Demonstration: Launching a Jupyter notebook

Module 3: Problem formulation and dataset preparation

Business challenge: Customer churn
Review customer churn dataset

Module 4: Data analysis and visualization

Demonstration: Loading and visualizing your dataset
Exercise 1: Relating features to target variables
Exercise 2: Relationships between attributes
Demonstration: Cleaning the data

Module 5: Training and evaluating a model

Types of algorithms
XGBoost and SageMaker
Demonstration: Training the data
Exercise 3: Finishing the estimator definition
Exercise 4: Setting hyper parameters
Exercise 5: Deploying the model
Demonstration: hyper parameter tuning with SageMaker
Demonstration: Evaluating model performance

Module 6: Automatically tune a model

Automatic hyper parameter tuning with SageMaker
Exercises 6-9: Tuning jobs

Module 7: Deployment / production readiness

Deploying a model to an endpoint
A/B deployment for testing
Auto Scaling
Demonstration: Configure and test auto scaling
Demonstration: Check hyper parameter tuning job
Demonstration: AWS Auto Scaling
Exercise 10-11: Set up AWS Auto Scaling

Module 8: Relative cost of errors

Cost of various error types
Demo: Binary classification cutoff

Module 9: Amazon SageMaker architecture and features

Accessing Amazon SageMaker notebooks in a VPC
Amazon SageMaker batch transforms
Amazon SageMaker Ground Truth
Amazon SageMaker Neo

Why have you chosen us?

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

I have attended a training from a different provider and it was not helpful.

Other

How many employees do you have in your IT department?

0 – 50

50 – 250

250 – 1000

1000+

Practical Data Science with Amazon SageMaker Training Course in Norway

The Nordic country Norway, is in Northern Europe. Known for its stunning natural beauty, including fjords, mountains, and forests, Norway is also famous for its high standard of living and strong social welfare system. Norway's capital and largest city is Oslo. Tromsø, Bergen, Trondheim and Stavanger are the other tourist attracting cities of Norway.

Norway is a constitutional monarchy with King Harald V as the head of state. The country has a population of 5,425,270 as of January 2022. Norway is a relatively small country and has a relatively low population density, with much of its land area covered by forests, mountains, and fjords. Despite its small size, Norway is known for its rich cultural heritage, strong economy, and stunning natural beauty, which attracts millions of visitors every year. This Nordic country is also known for its winter sports, such as skiing and snowboarding, and is a popular destination for outdoor enthusiasts.

Norway has a long history of invention and is home to numerous more top-tier tech firms and research facilities, such as; Kongsberg Gruppen, Telenor, Atea, Evry and Gjensidige Forsikring.

Due to the country's high latitude, there are large seasonal variations in daylight. From late May to late July, the sun never completely descends beneath the horizon. Which attracts many tourists around the world to see the "Land of the Midnight Sun". Tourists mainly visit Sognefjord, Norway's Largest Fjord, Pulpit Rock, one of the most photographed sites in Norway and of course the capital; Oslo.

Oslo is considered the business center of Norway. It is the country's largest city and the capital of Norway. The city is home to many of Norway's largest and most important companies, as well as several international organizations and research institutions. Additionally, the city is a popular tourist destination, known for its scenic location on the Oslo Fjord, its many museums and cultural attractions, and its vibrant nightlife and dining scene. Some of the most popular museums in Oslo are The Norwegian Museum of Cultural History, The Nobel Peace Center, The National Museum of Art, Architecture, and Design, The Munch Museum and The Vigeland Museum.

Practical Data Science with Amazon SageMaker Training in Norway

Activities

Intended audience

Upcoming Trainings

Practical Data Science with Amazon SageMaker Training in Norway

Activities

Intended audience

Prerequisites

What You Will Learn

Outline

HOW TO LEARN DATA SCIENCE IN 2024

Upcoming Trainings