• Date: Monday, January 24, 2022
  • Time: 9:00 AM to 5:00 PM CST
  • Location: Virtual Classroom
  • Course Level: Intermediate
  • Duration: 3 Days
  • Enrollment Cost: $1999 or €1682 or £1431
  • Not Ready to Enroll? Get Access Now

DP-100 : Designing and Implementing a Data Science Solution on Azure


In this course students will gain the necessary knowledge about how to use Azure services to develop, train, and deploy, machine learning solutions. The course starts with an overview of Azure services that support data science. From there, it focuses on using Azure's premier data science service, Azure Machine Learning service, to automate the data science pipeline. This course is focused on Azure and does not teach the student how to do data science. It is assumed students already know that.

Pass the DP-100 Designing and Implementing a Data Science Solution on Azure exam to be awarded the Microsoft Certified: Azure Data Scientist Associate certification.
Students learn how to develop data models that solve business problems using Azure technologies.

The Azure Data Scientist applies their knowledge of data science and machine learning to implement and run machine learning workloads on Azure; in particular, using Azure Machine Learning Service. This entails planning and creating a suitable working environment for data science workloads on Azure, running data experiments and training predictive models, managing and optimizing models, and deploying machine learning models into production.

This course is 50% presentation and demonstration and 50% hands-on learning using Microsoft Azure.

Benefits Includes 6 Months of Skill Me UP Academy

Live Training

Live Tech Sessions

Keep your skills sharp with expert talks and much more


Real-Time Labs

Learn by doing in live cloud environments

Who This Course Is Designed for

  • Candidates for this course apply scientific rigor and data exploration techniques to gain actionable insights and communicate results to stakeholders. Candidates use machine learning techniques to train, evaluate, and deploy models to build AI solutions that satisfy business objectives. Candidates use applications that involve natural language processing, speech, computer vision, and predictive analytics.


  • Knowledge of common statistical methods and data analysis best practices
  • Working knowledge of relational databases

Course Objectives

Course Modules

Course Outline

Module 1: Introduction to Azure Machine Learning

Module 2: "No-code" Machine Learning with Designer

Module 3: Running Experiments and Training Models

Module 4: Working with Data

Module 5: Compute Contexts

Module 6: Orchestrating Operations with Pipelines

Module 7: Deploying and Consuming Models

Module 8: Training Optimal Models

Module 9: Interpreting Models

Module 10: Monitoring Models