Study Guide for Microsoft DP-100 Certification Exam: Designing and Implementing Data Science Solution on Azure

“Any advanced technology was believably once called magic”

1. Case study:

   ENGIE Cofely has thousands of connected systems (such as different brands, models, and versions of heating systems) that generate a large volume of heterogeneous data (devices sending a few bytes of telemetry messages several times an hour in normal conditions) through different kinds of networks (private networks and Sigfox networks). This situation is becoming more and more challenging with time as new systems are deployed and more data is collected.
   The big data environment can be quite difficult to set up and maintain; the cloud is often a good way to make things easier while being able to scale on demand.

ENGIE Cofely has already experimented with technologies such as Azure Data Lake, and now they are facing two new challenges:

• What happens before using Data Lake (IoT)?
• What happens after using Data Lake (advanced data analytics)?

ENGIE Cofely saw a great opportunity to set up a Hackfest with Microsoft and experiment in those areas. Read more here.

2. Introduction: 

Data Scientist is a trending job title right now in the IT market. More and more organizations are seeking experienced candidates for big and small organizations. An Azure Data Scientist applies their knowledge of data science and machine learning to implement and run machine learning workloads on Azure. Do you want to become an accredited Data Scientist? Then get the DP-100 Certification exam by Microsoft with a step-by-step approach detailed here.

3. What to expect from this article?

A one-stop guide for your learning needs is curated in this article. Core data concepts, prerequisites, exam patterns, percentage of questions from different modules, and various learning paths have been made available for you. Self-learning portals links, tips, and tricks useful during the exam and available in the later sections. If you follow this guide thoroughly, your journey towards becoming a certified Azure Data Scientist will be smooth and successful.

4. Prerequisites  

DP-100 is a level 2, associate certification exam, applicable to anyone working or wants to on Machine Learning, Artificial Intelligence, and Data Science. Candidates appearing for the DP-100 certification exam should have basic knowledge of these Azure data fundamentals by taking the DP-900 certification exam. Although DP-900 is not mandatory, it will be helpful to crack the Microsoft Azure Data Scientist DP-100 certification exam.

5. Key Benefits:

• Run Machine learning models by creating different workspaces
• Implement and run Machine learning workloads on Azure, using Machine Learning Service
• Plan and create a working environment for data science workloads on Azure, run data experiments, and train predictive models
• AI/ML Data Scientist jobs are hot and selling faster in the IT industry than expected
• IT market is flooded with jobs for people who work with data and use Microsoft Azure Services. Candidates having Microsoft certification badges in their CV have a huge advantage.
• Certification is a way to let others know that your skills have been validated

6. Exam Pattern:

Microsoft offers concessions for students who can take the exam for $15. The table below summarizes all additional information about the exam.

7. Percentage of the question for all the modules:

• Set Up an Azure Machine Learning Workspace (30-35%)

Most questions on implementation can be expected from this module. Questions will be based on the creation of Azure Machine Learning Workspace, create and manage Datastores and Datasets, deploy ML workloads.

• Run Experiments and Train Models (25-30%)

From this module, you can expect questions on Azure Machine Learning Designer, Azure Machine Learning workspace, generate and log metrics, Automate the model training process by creating a pipeline and then monitoring pipeline runs.

• Optimize and Manage Models (20-25%)

From this module, the question will be based on the use of the Automated ML interface in Azure Machine Learning studio, use of hyperdrive to tune hyperparameters, interpret models, and manage models.

• Deploy and consume Models (20-25%)

Creating production compute targets, deploying model as a service, batch interference, publishing a designer pipeline as a web service are the highlighted topics from this module and you can expect scenario-based questions on them.

8. How to prepare for the exam:

There are various ways to prepare for this certification

• Microsoft Official Courseware (MOC) are provided by CloudThat upon enrolment for the course

       Microsoft Designing and Implementing a Data Science Solution on Azure Learning Path

• Microsoft Documentation
• Case studies for understanding customer requirement
• Instructor lead training can help you understand the Azure Data Scientist concepts better and in a structured approach
• CloudThat also provides TestPrep for anyone attempting this course where unlimited access is provided to our library for Azure, MCQs, and performance tracker.
• Check out the course link for additional information

9. Tips & Tricks:

• Focus on core AI and Data concepts before appearing for the exam
• Acquire a thorough understanding of Azure Machine Learning Workspace, training models, and creating and deploying consume models
• Do not hesitate to refer to Microsoft Docs whenever in doubt
• Do not miss out on taking up CloudThat’s TestPrep before you write the actual exam

10. Get Certified now:

It is always great to get the right source of learning to Move Up. At CloudThat we have a course aimed at preparing participants/candidates for Designing and Implementing a Data Science Solution on Azure.

You can register for the exam by visiting the Microsoft website.

If you have just begun your Microsoft Azure journey related to data in the cloud, then “Microsoft Azure Data Fundamentals DP-900” will be a good course to get started. This is the first exam in Data Platform Series and is all about the fundamentals.

Join the Azure revolution along with 100+ fortune 500 companies and CloudThat will be there to support your career growth.

WRITTEN BY Anusha Shanbhag

Anusha Shanbhag is an AWS Certified Cloud Practitioner Technical Content Writer specializing in technical content strategizing with over 10+ years of professional experience in technical content writing, process documentation, tech blog writing, and end-to-end case studies publishing, catering to consulting and marketing requirements for B2B and B2C audiences. She is a public speaker and ex-president of the corporate Toastmaster club.