10 Best Microsoft Azure Data Scientist Associate DP-100 Courses On Udemy (2025)

The Microsoft Azure Data Scientist DP-100 exam is designed to certify individuals who have the skills to design and implement data science solutions on the Azure cloud platform.

Passing this exam can open doors to exciting career opportunities as a Data Scientist, Machine Learning Engineer, or related roles within the Azure ecosystem.

It demonstrates your proficiency in utilizing Azure Machine Learning services and tools to build, deploy, and manage machine learning models.

However, finding the right DP-100 preparation course on Udemy can feel overwhelming with the sheer number of options available.

You’re looking for a course that provides comprehensive coverage of the exam topics, offers hands-on practice, and is taught by experienced instructors.

Based on our thorough analysis, DP-100: A-Z Machine Learning using Azure Machine Learning emerges as the best overall course on Udemy for DP-100 certification preparation.

This course provides a comprehensive and practical learning experience covering all the essential DP-100 exam topics.

It combines theory with hands-on exercises and real-world projects, ensuring you gain the practical skills needed to excel in the exam.

While DP-100: A-Z Machine Learning using Azure Machine Learning is our top recommendation, other excellent courses are available on Udemy.

Continue reading to discover our curated list of the best DP-100 courses, tailored to different learning styles and preferences.

DP-100: A-Z Machine Learning using Azure Machine Learning

You will start by learning the fundamentals of machine learning, including key concepts, types of models, and common terms.

The course then dives into Azure Machine Learning, covering the architecture, workflow, and model selection process.

You will learn how to set up an Azure ML workspace, create datastores and datasets, and utilize compute resources like clusters and instances.

A significant portion focuses on using the Azure ML Studio Designer to run experiments, train models, deploy real-time and batch inference endpoints, and perform data processing tasks like normalization and cleaning missing data.

You will gain hands-on experience with classification algorithms like logistic regression and decision trees, as well as regression techniques like linear regression.

The course also covers using Python libraries like Pandas and Scikit-learn for data manipulation and model building.

You will learn how to use the AzureML SDK to create and register datastores, datasets, run experiments, train models, and deploy web services.

Advanced topics like automated machine learning, hyperparameter tuning with HyperDrive, and model interpretability using techniques like Shapley values are also covered.

Additionally, you will explore integrating Azure Machine Learning with Databricks for big data processing using Spark.

The course includes a Python crash course and an overview of Azure fundamentals to provide a solid foundation.

Throughout the course, you will work on practical examples and hands-on exercises, ensuring you gain real-world experience in applying machine learning techniques using Azure’s powerful tools and services.

DP-100 Microsoft Azure Data Scientist Complete Exam Prep

This course covers everything from setting up your Azure Machine Learning workspace to deploying models as services.

You’ll start by learning how to create an Azure ML workspace, manage data objects like datastores and datasets, and set up your Python environment to work with Azure ML.

The course then dives into experiment compute contexts, showing you how to create compute instances and clusters for training models.

A major focus is on actually building machine learning models.

You’ll use the Azure ML Designer to create pipelines for training and evaluating models, incorporating custom code.

The course also covers running training scripts directly using the Azure ML SDK, as well as automating the model training process with pipelines built using the SDK.

Automated machine learning (AutoML) and hyperparameter tuning with HyperDrive are covered in-depth, giving you powerful tools to create optimal models without manual effort.

You’ll learn to register trained models and create production compute targets to deploy them as web services.

Deployment scenarios include real-time inferencing with AutoML models, ML Designer models, and SDK models.

You’ll also learn how to create pipelines for batch inferencing use cases.

Throughout, you’ll work with key Azure tools like the CLI, PowerShell, and the Azure Portal/Studio.

The hands-on nature of this course ensures you gain practical experience with every aspect of the Azure ML workflow.

Microsoft DP-100 Exam certification Tests 2024

The course covers a comprehensive set of exam-like questions and practice tests to prepare you for the DP-100 certification exam.

You’ll start with Exam Like Questions 1, which provides a solid foundation for the concepts covered in the exam.

From there, you’ll move on to Exam Number 2, diving deeper into the material and testing your understanding with realistic practice questions.

As you progress, you’ll tackle Exam Number 3 and Exam Number 4, each presenting a new set of challenges and helping you solidify your knowledge.

But the course doesn’t stop there – you’ll also work through Exam Number 5, which is particularly valuable for its focus on some of the more advanced topics covered in the exam.

Finally, you’ll round out your preparation with Exam Number 6, giving you one last opportunity to put your skills to the test before taking the actual certification exam.

Throughout the course, you’ll encounter a variety of exam-like questions that closely mirror the format and difficulty level of the real exam.

Microsoft Azure Data Scientist DP-100 Practice Exams [2024]

This course provides you with three full-length practice exams to prepare for the Microsoft Azure Data Scientist DP-100 certification exam.

The practice exams closely mirror the actual exam, allowing you to get a realistic sense of the exam format, question types, and difficulty level.

You’ll start with Practice Exam 1, which covers a comprehensive range of topics aligned with the DP-100 exam objectives.

This exam will test your understanding of core data science concepts, Azure tools and services for data science workflows, and best practices for building and operationalizing machine learning models on Azure.

After completing the first practice exam, you can review your performance and identify areas that need further study.

Practice Exam 2 offers a fresh set of questions, enabling you to reinforce your knowledge and gauge your progress.

The course culminates with Practice Exam 3, providing a final opportunity to assess your readiness for the actual DP-100 exam.

By taking all three practice exams, you’ll gain valuable experience with the exam format and develop confidence in your ability to tackle the real certification test.

Additionally, the course includes a set of bonus questions that delve into advanced topics and scenarios, further challenging your understanding of Azure data science concepts and techniques.

With this course, you’ll have access to a comprehensive collection of practice questions that accurately reflect the DP-100 exam content.

You can take the exams at your own pace, review explanations for each question, and focus your study efforts on areas where you need improvement.

DP-100: Designing and Implementing a Data Science Solution

The course starts with Practice Test 1, allowing you to assess your current knowledge and identify areas for improvement.

As you progress, you’ll encounter Practice Test 2, providing another opportunity to reinforce your understanding.

However, the highlight is Practice Test 3.

This comprehensive assessment covers all the key concepts you’ve learned throughout the course, ensuring you’re well-prepared for the certification exam.

You’ll have the chance to apply your skills and knowledge in a simulated testing environment, giving you the confidence to tackle the real exam.

The course is structured in a way that allows you to continuously evaluate your progress through these practice tests.

You’ll receive valuable feedback, enabling you to focus on the areas that need more attention.

This iterative approach ensures that by the time you reach Practice Test 3, you’ll be fully equipped with the necessary expertise to excel in the DP-100 certification.

Microsoft Azure Data Scientist DP-100 Practice Test [2024]

The course covers two main exams - Exam 1 and Exam 2.

With Exam 1, you’ll dive into the fundamentals of data science on Azure.

You’ll learn how to explore and analyze data using Azure Databricks and automate machine learning model training with Azure Machine Learning service.

Mastering these concepts will give you a solid foundation for working with data on the Azure platform.

Exam 2 takes your skills to the next level by teaching you how to operationalize machine learning models.

This includes deploying models as web services, managing models in production, and monitoring their performance over time.

You’ll also learn techniques for improving model accuracy through techniques like automated machine learning.

The course seamlessly blends theory with hands-on practice, ensuring you gain practical experience with the tools and services covered in the exams.

Microsoft DP-100 Practice Test

The course starts with a warmup section to get you prepared.

Then, you’ll dive into three comprehensive practice tests - A, B, and C. Practice Test A covers core data science concepts and how to implement them in Azure.

You’ll work through real-world scenarios to solidify your understanding.

Practice Test B builds on the first one, challenging you with more advanced data wrangling and model deployment tasks.

This test ensures you can handle the complexities of production data science workloads.

Practice Test C is the final hurdle, testing your end-to-end mastery of the Azure Data Scientist role.

You’ll be asked to design, build, operationalize, and manage machine learning solutions from scratch.

With these three rigorous practice tests, you’ll gain hands-on experience across all the key DP-100 exam objectives.

The course progressively ramps up the difficulty level, making you job-ready by the end.

You’ll be confident in your ability to clear the certification and take on real data science projects using Azure’s powerful tools and services.

DP-100 Microsoft Azure Data Scientist Practice test 2024

This course consists of four practice tests, each containing multiple-choice and multiple-answer questions.

This allows you to thoroughly prepare for the actual DP-100 exam.

One of the standout features is the ability to pause the test at any point and continue later.

You can also retake the tests as many times as needed, which is incredibly helpful for reinforcing your understanding.

The progress bar displays your test progress and remaining time, but even if time runs out, you can still complete the test.

The course offers flexibility by allowing you to skip questions and revisit them later.

The “Mark for review” feature is particularly useful for flagging questions you’re unsure about, ensuring you don’t miss any before submitting the test.

With its comprehensive practice tests, flexible format, and user-friendly features, this course provides an excellent opportunity to assess your knowledge and identify areas for improvement before taking the DP-100 Microsoft Azure Data Scientist certification exam.

Latest Microsoft Azure DP-100 Practice Tests & Explanations

With this course, you’ll get access to three comprehensive practice tests that will help you prepare for the Microsoft Azure DP-100 exam.

The first practice test covers a wide range of topics, allowing you to assess your current knowledge and identify areas that need further study.

As you progress, the second practice test dives deeper into more advanced concepts, ensuring you have a solid grasp of the material.

Finally, the third practice test serves as a final checkpoint, simulating the actual exam environment.

You’ll have the opportunity to put your skills to the test and gain confidence before taking the real certification exam.

Each practice test comes with detailed explanations, providing you with valuable insights and clarifications on the questions you may have struggled with.

Throughout the course, you’ll encounter questions that closely mirror the format and difficulty level of the actual DP-100 exam, ensuring you’re well-prepared for the real thing.

With these three comprehensive practice tests, you’ll be able to identify your strengths and weaknesses, focus your study efforts, and ultimately increase your chances of passing the Azure DP-100 certification exam on your first attempt.

DP-100: Azure Machine Learning & Data Science Exam Prep

You will start by learning how to create resources like workspaces, compute instances, and datasets in Azure Machine Learning.

The course then dives into the Azure ML Designer, where you’ll learn to build machine learning pipelines, preprocess data, train models using algorithms like linear regression, decision trees, and neural networks, and evaluate results.

You’ll also learn how to deploy your trained models as real-time and batch inference pipelines, making them accessible as web services.

The course covers data preprocessing techniques like handling missing data, normalizing datasets, and splitting data.

It also teaches you how to automate model training using pipelines and leverage AutoML for a no-code approach to building models.

The Python SDK is extensively covered, allowing you to create resources, prepare data, train models, tune hyperparameters, interpret models using explainers, and deploy models as web services.

You’ll work on projects that reinforce the concepts learned, such as building a regression model for house price prediction and a classification model for income prediction.

The course also introduces you to Azure fundamentals like virtual machines, managed compute services (App Service, Containers, Serverless), storage (Blob Storage, Files), and databases (Relational, NoSQL, In-Memory).

You’ll learn about key concepts like scaling, load balancing, monitoring, and reducing costs, helping you design good solutions with Azure services.