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

Experimentation for Improvement (Coursera) Coursera
McMaster University

Experimentation for Improvement (Coursera)

We are always using experiments to improve our lives, our community, and our work. Are you doing it efficiently? Or are you (incorrectly) changing one thing at a time and hoping for the best? In this course, you will learn how to plan efficient experiments - testing with many variables. Our goal is to find the best results using only a few experiments. A key part of the course is how to optimize a system.

Sep 14th 2026
5-12 Weeks
Introduction to Machine Learning (Coursera) Coursera
Duke University

Introduction to Machine Learning (Coursera)

This course will provide you a foundational understanding of machine learning models (logistic regression, multilayer perceptrons, convolutional neural networks, natural language processing, etc.) as well as demonstrate how these models can solve complex problems in a variety of industries, from medical diagnostics to image recognition to text prediction.

Sep 21st 2026
5-12 Weeks
Programming with Cloud IoT Platforms (Coursera) Coursera
Pohang University of Science and Technology - POSTECH

Programming with Cloud IoT Platforms (Coursera)

Internet of Things (IoT) is an emerging area of information and communications technology (ICT) involving many disciplines of computer science and engineering including sensors/actuators, communications networking, server platforms, data analytics and smart applications. IoT is considered to be an essential part of the 4th Industrial Revolution along with AI and Big Data.

Sep 21st 2026
5-12 Weeks
Sistemas difusos (Coursera) Coursera
Universidad Nacional de Colombia

Sistemas difusos (Coursera)

Los sistemas difusos permiten efectuar cálculos cuando hay información con incertidumbre, o cuando se debe combinar información tanto cuantitativa como cualitativa. Se trata de una aproximación matemática para modelar esas situaciones. Este curso está diseñado para ayudar a entender y explicar cómo funcionan dichos sistemas. El curso tiene una aproximación teórica y práctica. Los principios matemáticos son de un nivel bajo y están al alcance de un público muy amplio. El curso cuenta con varios laboratorios para aprender a utilizar las herramientas de software que usan esos principios. Este componente práctico requiere una comprensión mínima de programación.

Sep 21st 2026
4 Weeks
Precision Medicine (Coursera) Coursera
University of Geneva

Precision Medicine (Coursera)

This course will provide you with the key knowledge and tools to understand the fundamentals and practical implications of precision medicine, its opportunities and challenges. It will address precision-medicine era diagnostics, treatment selection, genetic counseling, public health interventions, and biomedical research. It will also deal with data science and ethical issues. From genomic analysis and genetic counseling to cancer biomarkers, from risk assessment of chronic diseases to the understanding of gene-environment interactions, from pharmacogenomics to multi-omics data integration, experts will walk you through the many aspects of precision medicine, from the bench to the bedside and to population health.

Sep 21st 2026
5-12 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.

Sep 14th 2026
5-12 Weeks
Programming for Data Science (Coursera) Coursera
University of Leeds

Programming for Data Science (Coursera)

Explore the basics of programming and familiarise yourself with the Python language. After completing this course, you will be able to write Python programs in Jupyter Notebook and describe basic programming. In this course, you will learn everything you need to start your programming journey. You will discover the different data types available in Python and how to use them, learn how to apply conditional and looping control structures, and write your own functions.

Sep 21st 2026
3 Weeks
Avoiding AI Harm (Coursera) Coursera
Fred Hutchinson Cancer Center

Avoiding AI Harm (Coursera)

This course is designed for those in roles with decision making power, to help them understand major topics to consider for using and developing Artificial Intelligence (AI) responsibly, including popular Generative AI tools like ChatGPT and others. It covers real-world examples of situations where AI was used in variety of fields and situations in ways hat revealed ethical concerns. Strategies are suggested to avoid doing harm working with AI, including a framework for working responsibly with AI.

Sep 21st 2026
1 Week
Data Science Ethics (Coursera) Coursera
University of Michigan

Data Science Ethics (Coursera)

What are the ethical considerations regarding the privacy and control of consumer information and big data, especially in the aftermath of recent large-scale data breaches? This course provides a framework to analyze these concerns as you examine the ethical and privacy implications of collecting and managing big data. Explore the broader impact of the data science field on modern society and the principles of fairness, accountability and transparency as you gain a deeper understanding of the importance of a shared set of ethical values.

Sep 21st 2026
4 Weeks
Preparing for the Google Cloud Professional Data Engineer Exam (Coursera) Coursera
Google Cloud

Preparing for the Google Cloud Professional Data Engineer Exam (Coursera)

From the course: "The best way to prepare for the exam is to be competent in the skills required of the job." This course uses a top-down approach to recognize knowledge and skills already known, and to surface information and skill areas for additional preparation. You can use this course to help create your own custom preparation plan. It helps you distinguish what you know from what you don't know. And it helps you develop and practice skills required of practitioners who perform this job.

Sep 21st 2026
5-12 Weeks