Prepare for DP-100: Data Science on Microsoft Azure Exam (Coursera)

Offered by Microsoft,
Prepare for DP-100: Data Science on Microsoft Azure Exam (Coursera)

Microsoft certifications give you a professional advantage by providing globally recognized and industry-endorsed evidence of mastering skills in digital and cloud businesses. In this course, you will prepare to take the DP-100 Azure Data Scientist Associate certification exam. You will refresh your knowledge of how to plan and create a suitable working environment for data science workloads on Azure, run data experiments, and train predictive models. In addition, you will recap on how to manage, optimize, and deploy machine learning models into production.

Class Deals by MOOC List - Click here and see Coursera's Active Discounts, Deals, and Promo Codes.

You will test your knowledge in a practice exam mapped to all the main topics covered in the DP-100 exam, ensuring you’re well prepared for certification success.
You will also get a more detailed overview of the Microsoft certification program and where you can go next in your career. You’ll also get tips and tricks, testing strategies, useful resources, and information on how to sign up for the DP-100 proctored exam. By the end of this course, you will be ready to sign-up for and take the DP-100 exam.
This is the fifth course in a five-course program that prepares you to take the DP-100: Designing and Implementing a Data Science Solution on Azure certification exam.
The certification exam is an opportunity to prove knowledge and expertise operate machine learning solutions at a cloud-scale using Azure Machine Learning. This specialization teaches you to leverage your existing knowledge of Python and machine learning to manage data ingestion and preparation, model training and deployment, and machine learning solution monitoring in Microsoft Azure. Each course teaches you the concepts and skills that are measured by the exam.
This Specialization is intended for data scientists with existing knowledge of Python and machine learning frameworks like Scikit-Learn, PyTorch, and Tensorflow, who want to build and operate machine learning solutions in the cloud. It teaches data scientists how to create end-to-end solutions in Microsoft Azure. Students will learn how to manage Azure resources for machine learning; run experiments and train models; deploy and operationalize machine learning solutions, and implement responsible machine learning. They will also learn to use Azure Databricks to explore, prepare, and model data; and integrate Databricks machine learning processes with Azure Machine Learning.
Course 5 of 5 in the Microsoft Azure Data Scientist Associate - DP-100 Test Prep Specialization.

Syllabus

WEEK 1
Prepare for the DP-100: Designing and implementing a Data Science Solution on Azure Exam
After completing this module, you will have an understanding of Microsoft certification pathways, role-based certifications and jobs and careers associated with certification. You will also find out how to prepare for the proctored exam, including the topics covered in the exam, how the exam is administered and exam strategy, tips and tricks.

WEEK 2
Exam preparation - Course 1
In this module you’ll review Course 1 of the Microsoft Azure Data Scientist Associate specialization.

WEEK 3
Exam preparation - Course 2
In this module you’ll review Course 2 of the Microsoft Azure Data Scientist Associate specialization.

WEEK 4
Exam preparation - Course 3
In this module you’ll review Course 3 of the Microsoft Azure Data Scientist Associate specialization.

WEEK 5
Exam preparation - Course 4
In this module you’ll review Course 4 of the Microsoft Azure Data Scientist Associate specialization.

WEEK 6
Final Practice Exam
In this module, you will find out how the core concepts are weighted and skills are measured, before taking the full practice exam. Following this you will find out how you can book your certification exam.

Go to Class
MOOC List is learner-supported. When you buy through links on our site, we may earn an affiliate commission.

Related Courses

Data Science in Health Technology Assessment (Coursera) Coursera
Genentech

Data Science in Health Technology Assessment (Coursera)

This course explores key concepts and methods in Health Economics and Health Technology Assessment (HTA) and is intended for learners who have a foundation in data science, clinical science, regulatory and are new to this field and would like to understand basic principles used by payers for their reimbursement decisions.

Oct 12th 2026
3 Weeks
Visualization for Data Journalism (Coursera) Coursera
University of Illinois at Urbana-Champaign

Visualization for Data Journalism (Coursera)

While telling stories with data has been part of the news practice since its earliest days, it is in the midst of a renaissance. Graphics desks which used to be deemed as “the art department,” a subfield outside the work of newsrooms, are becoming a core part of newsrooms’ operation. Those people (they often have various titles: data journalists, news artists, graphic reporters, developers, etc.) who design news graphics are expected to be full-fledged journalists and work closely with reporters and editors.

Oct 5th 2026
5-12 Weeks
Applied Text Mining in Python (Coursera) Coursera
University of Michigan

Applied Text Mining in Python (Coursera)

This course will introduce the learner to text mining and text manipulation basics. The course begins with an understanding of how text is handled by python, the structure of text both to the machine and to humans, and an overview of the nltk framework for manipulating text. The second week focuses on common manipulation needs, including regular expressions (searching for text), cleaning text, and preparing text for use by machine learning processes. The third week will apply basic natural language processing methods to text, and demonstrate how text classification is accomplished. The final week will explore more advanced methods for detecting the topics in documents and grouping them by similarity (topic modelling).

Oct 12th 2026
4 Weeks
Data Science in Stratified Healthcare and Precision Medicine (Coursera) Coursera
University of Edinburgh

Data Science in Stratified Healthcare and Precision Medicine (Coursera)

An increasing volume of data is becoming available in biomedicine and healthcare, from genomic data, to electronic patient records and data collected by wearable devices. Recent advances in data science are transforming the life sciences, leading to precision medicine and stratified healthcare. In this course, you will learn about some of the different types of data and computational methods involved in stratified healthcare and precision medicine.

Oct 5th 2026
5-12 Weeks
Machine Learning Introduction for Everyone (Coursera) Coursera
IBM

Machine Learning Introduction for Everyone (Coursera)

This three-module course introduces machine learning and data science for everyone with a foundational understanding of machine learning models. You’ll learn about the history of machine learning, applications of machine learning, the machine learning model lifecycle, and tools for machine learning. You’ll also learn about supervised versus unsupervised learning, classification, regression, evaluating machine learning models, and more.

Oct 12th 2026
3 Weeks
Fundamentals of Machine Learning in Finance (Coursera) Coursera
New York University Tandon School of Engineering

Fundamentals of Machine Learning in Finance (Coursera)

The course aims at helping students to be able to solve practical ML-amenable problems that they may encounter in real life that include: (1) understanding where the problem one faces lands on a general landscape of available ML methods, (2) understanding which particular ML approach(es) would be most appropriate for resolving the problem, and (3) ability to successfully implement a solution, and assess its performance.

Oct 12th 2026
4 Weeks
Alibaba Cloud Native Solutions and Container Service (Coursera) Coursera
Alibaba Cloud Academy

Alibaba Cloud Native Solutions and Container Service (Coursera)

This course demonstrates how to use Alibaba Cloud Container Service and Container Registry Service to design and develop architectures related to cloud native applications, services, and security solutions. This course helps you understand the basic concepts of cloud native, the commercial implementation of container technology, and Kubernetes technology as well as extra benefits provided by Alibaba Cloud. This course is intended to prepare users to take the Alibaba Cloud Native ACA certification exam.

Oct 5th 2026
5-12 Weeks
Applied Plotting, Charting & Data Representation in Python (Coursera) Coursera
University of Michigan

Applied Plotting, Charting & Data Representation in Python (Coursera)

This course will introduce the learner to information visualization basics, with a focus on reporting and charting using the matplotlib library. The course will start with a design and information literacy perspective, touching on what makes a good and bad visualization, and what statistical measures translate into in terms of visualizations. The second week will focus on the technology used to make visualizations in python, matplotlib, and introduce users to best practices when creating basic charts and how to realize design decisions in the framework.

Oct 5th 2026
4 Weeks
Introduction to Genomic Technologies (Coursera) Coursera
Johns Hopkins University

Introduction to Genomic Technologies (Coursera)

This course introduces you to the basic biology of modern genomics and the experimental tools that we use to measure it. We'll introduce the Central Dogma of Molecular Biology and cover how next-generation sequencing can be used to measure DNA, RNA, and epigenetic patterns. You'll also get an introduction to the key concepts in computing and data science that you'll need to understand how data from next-generation sequencing experiments are generated and analyzed.

Oct 12th 2026
4 Weeks
Machine Learning Rapid Prototyping with IBM Watson Studio (Coursera) Coursera
IBM

Machine Learning Rapid Prototyping with IBM Watson Studio (Coursera)

An emerging trend in AI is the availability of technologies in which automation is used to select a best-fit model, perform feature engineering and improve model performance via hyperparameter optimization. This automation will provide rapid-prototyping of models and allow the Data Scientist to focus their efforts on applying domain knowledge to fine-tune models. This course will take the learner through the creation of an end-to-end automated pipeline built by Watson Studio’s AutoAI experiment tool, explaining the underlying technology at work as developed by IBM Research.

Oct 12th 2026
4 Weeks
Probabilistic Graphical Models 2: Inference (Coursera) Coursera
Stanford University

Probabilistic Graphical Models 2: Inference (Coursera)

Probabilistic graphical models (PGMs) are a rich framework for encoding probability distributions over complex domains: joint (multivariate) distributions over large numbers of random variables that interact with each other. These representations sit at the intersection of statistics and computer science, relying on concepts from probability theory, graph algorithms, machine learning, and more.

Oct 12th 2026
5-12 Weeks