AW233: Practical Data Science with Amazon SageMaker

Training: AWS™ - Cloud - Artificial Intelligence - Certifications

AWS ATP Select Tier Logo

Participants receive a practical introduction to the development process of machine learning solutions with Amazon SageMaker. The course covers the steps for creating, training, and deploying an ML model. It addresses the daily work of a data scientist, complemented by instructor-led demonstrations and practical exercises.

Unfortunately there are currently no available appointments.
Would you like to request an appointment? Then click on 'No matching appointment?'

Request prefered appointment period:

* All fields marked with an asterisk are mandatory fields.

Agenda:

  • Introduction to Machine Learning
    • Benefits of machine learning (ML)
    • Types of ML approaches
    • Framing the business problem
    • Prediction quality
    • Processes, roles, and responsibilities for ML projects

  • Preparing a Dataset
    • Data analysis and preparation
    • Data preparation tools
    • Demonstration: Review Amazon SageMaker Studio and Notebooks
    • Hands-On Lab: Data Preparation with SageMaker Data Wrangler

  • Training a Model
    • Steps to train a model
    • Choose an algorithm
    • Train the model in Amazon SageMaker
    • Hands-On Lab: Training a Model with Amazon SageMaker
    • Amazon CodeWhisperer
    • Demonstration: Amazon CodeWhisperer in SageMaker Studio Notebooks

  • Evaluating and Tuning a Model
    • Model evaluation
    • Model tuning and hyperparameter optimization
    • Hands-On Lab: Model Tuning and Hyperparameter Optimization with Amazon SageMaker

  • Deploying a Model
    • Model deployment
    • Hands-On Lab: Deploy a Model to a Real-Time Endpoint and Generate a Prediction

  • Operational Challenges
    • Responsible ML
    • ML team and MLOps
    • Automation
    • Monitoring
    • Updating models (model testing and deployment)

  • Other Model-Building Tools
    • Different tools for different skills and business needs
    • No-code ML with Amazon SageMaker Canvas
    • Demonstration: Overview of Amazon SageMaker Canvas
    • Amazon SageMaker Studio Lab
    • Demonstration: Overview of SageMaker Studio Lab
    • (Optional) Hands-On Lab: Integrating a Web Application with an Amazon SageMaker Model Endpoint

Objectives:

In this course AW233 Practical Data Science with Amazon SageMaker, you will learn to:
  • Discuss the benefits of different types of machine learning for solving business problems
  • Describe the typical processes, roles, and responsibilities on a team that builds and deploys ML systems
  • Explain how data scientists use AWS™ tools and ML to solve a common business problem
  • Summarize the steps a data scientist takes to prepare data
  • Summarize the steps a data scientist takes to train ML models
  • Summarize the steps a data scientist takes to evaluate and tune ML models
  • Summarize the steps to deploy a model to an endpoint and generate predictions
  • Describe the challenges for operationalizing ML models
  • Match AWS™ tools with their ML function

Target audience:

This course AW233 Practical Data Science with Amazon SageMaker is intended for:
  • Development Operations (DevOps) engineers
  • Application developers

Prerequisites:

To participate in the course AW233 Practical Data Science with Amazon SageMaker at qSkills™, you should meet the following prerequisites::

Description:

Artificial intelligence and machine learning (AI/ML) are becoming mainstream. In this course AW233 Practical Data Science with Amazon SageMaker, you will spend a day in the life of a data scientist so that you can collaborate efficiently with data scientists and build applications that integrate with ML. You will learn the basic process data scientists use to develop ML solutions on Amazon Web Services (AWS™) with Amazon SageMaker. You will experience the steps to build, train, and deploy an ML model through instructor-led demonstrations and labs.

This course AW233 Practical Data Science with Amazon SageMaker includes presentations, hands-on labs, and demonstrations.
check-icon

Guaranteed implementation:

from 2 Attendees

Booking information

Price:

750,00 € plus VAT.

(including lunch & drinks)

Authorized training partner

NetApp Partner Authorized Learning
Commvault Training Partner
CQI | IRCA Approved Training Partner
Veeam Authorized Education Center
Acronis Authorized Training Center
AWS Partner Select Tier Training
ISACA Accredited Partner
iSAQB
CompTIA Authorized Partner
EC-Council Accredited Training Center

Memberships

Allianz für Cyber-Sicherheit
TeleTrust Pioneers in IT security
Bundesverband der IT-Sachverständigen und Gutachter e.V.
Bundesverband mittelständische Wirtschaft (BVMW)
Allianz für Sicherheit in der Wirtschaft
NIK - Netzwerk der Digitalwirtschaft
BVSW
Bayern Innovativ
KH-iT
CAST
IHK Nürnberg für Mittelfranken
eato e.V.
Sicherheitsnetzwerk München e.V.