DP-100 Azure Data Scientist Associate Complete Exam Guide

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Henry Habib

8:38:18

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1 - Introduction

1 - What is DP100.mp4

04:23

2 - What are the objectives of this course.mp4

03:23

3 - Course roadmap.mp4

03:38

4 - DP-100-Curriculum.pdf

4 - Learning objectives.mp4

04:58

5 - Instructor overview.mp4

02:08

6 - Ways to reach out.mp4

01:48

7 - Keys to success.mp4

02:12

8 - Leave a rating.mp4

00:48

9 - Watch in 1080p.mp4

01:05

2 - Environment Setup

10 - Create an Azure account.mp4

02:17

11 - Cost management in Azure.mp4

03:52

12 - ReferenceMaterial.zip

12 - Reference material.mp4

04:50

13 - DP-100-Resources-PreReqs.pdf

13 - Resources and prerequisites.mp4

06:02

14 - Helpful advice from students.mp4

03:19

3 - LO1 Design and prepare a machine learning solution 2025

15 - 111 Determine the appropriate compute specifications.mp4

09:41

16 - 112 Model deployment requirements.mp4

05:48

17 - 113 Choice to development approach to build or train a model.mp4

09:53

18 - 121 Create an Azure Machine Learning workspace.mp4

03:31

19 - 121 Walkthrough of workspace.mp4

09:23

20 - 121 Resources created by ML workspace.mp4

03:03

21 - 121 How to access Azure ML tools.mp4

06:01

22 - 121 Create a compute instance.mp4

02:23

23 - 121 Run python SDK import statements.mp4

03:15

24 - 121 Stopping compute instance.mp4

01:09

25 - 131 Create Azure Data resources.mp4

07:24

26 - 132 Create and register a datastore.mp4

08:13

27 - 132 Example of transfering files to datastore.mp4

05:53

28 - 133 Create a data asset.mp4

07:09

29 - 133 Register a data asset through SDK.mp4

10:01

30 - 133 Register and consume data assets through SDK.mp4

06:48

4 - LO2 Explore data and train models 3540

31 - 211 Load and transform data.mp4

17:53

32 - 212 Analyze data using Azure Data Explorer 1.mp4

05:16

33 - 212 Analyze data using Azure Data Explorer 2.mp4

05:51

34 - 212 Use profile mechanics to explore data.mp4

01:34

35 - 221 Create a training pipeline introduction.mp4

03:27

36 - 222 Consume data assets into the designer.mp4

06:54

37 - 223 Use data preparation components in designer.mp4

14:35

38 - 223 Training model and scoring components in designer.mp4

08:34

39 - 223 Evaluating trained model components in designer.mp4

14:18

40 - 223 Evaluation results defined.mp4

00:33

41 - 224 Context and usecase for custom code components.mp4

05:52

42 - 224 Adding custom python code in custom components in designer.mp4

09:52

43 - 231 Automated ML introduction.mp4

01:30

44 - 231 Automated ML regression and tabular data example 1.mp4

05:57

45 - 231 Automated ML regression and tabular data example 2.mp4

01:27

46 - 231 Automated ML regression and tabular data example 3.mp4

10:03

47 - 232 Automated ML natural language processing NLP example.mp4

07:51

48 - 234 Training options in Automated ML including preprocessing and algorithms.mp4

16:00

49 - 241 Develop code using a compute instance.mp4

02:07

50 - 242 Consume data in a notebook.mp4

01:36

51 - 243 How to run an experiment.mp4

11:28

52 - 244 245 Evaluate and train a model using Python SDK 1.mp4

05:30

53 - 244 245 Evaluate and train a model using Python SDK 2.mp4

05:46

54 - 244 245 Evaluate and train a model using Python SDK 3.mp4

08:24

55 - 244 245 Run experiments and measure impact on evaluation metrics.mp4

08:37

5 - LO3 Prepare a model for deployment 2025

56 - 311 Introduction to model training scripts.mp4

03:09

57 - 311 313 314 316 317 Run model training script endtoend 1.mp4

08:47

58 - 311 313 314 316 317 Run model training script endtoend 2.mp4

10:57

59 - 311 313 314 316 317 Run model training script endtoend 3.mp4

02:33

60 - 311 313 314 316 317 Run model training script endtoend 4.mp4

02:14

61 - 311 313 314 316 317 Run model training script endtoend 5.mp4

04:26

62 - 318 312 Configure compute and set up script parameters set up.mp4

04:50

63 - 318 312 Using script parameters.mp4

05:45

64 - 318 312 Cycling through script parameters.mp4

08:34

65 - 318 312 Testing different script parameters.mp4

07:24

66 - 318 312 Configure compute for a job run.mp4

08:24

67 - 318 312 Adding compute to an environment.mp4

04:03

68 - 318 312 Deleting a compute through Python SDK.mp4

02:14

69 - 321 Introduction to pipelines.mp4

01:03

70 - 321 Pipeline context.mp4

02:11

71 - 321 Create a prepare data step in pipeline.mp4

07:41

72 - 321 Create a train model step in pipeline.mp4

04:17

73 - 321 Fix errors in pipeline.mp4

00:57

74 - 321 Create a pipeline run script.mp4

17:57

75 - 322 Pass data between steps in pipeline.mp4

05:50

76 - 323 Run the pipeline.mp4

07:15

77 - 323 Other ways to run the pipeline.mp4

02:18

78 - 323 Publishing the endpoint.mp4

02:28

79 - 323 Create a pipeline endpoint.mp4

01:44

80 - 323 Call an endpoint 1.mp4

03:05

81 - 323 Call an endpoint 2.mp4

06:21

82 - 324 Monitor pipeline runs.mp4

03:11

6 - LO4 Deploy and retrain a model 1015

83 - 411 413 415 Introduction to deploying model.mp4

01:41

84 - 411 413 415 Create a model to be deployed.mp4

08:44

85 - 411 413 415 Configure model for a realtime deployment.mp4

06:53

86 - 411 413 415 Removing the dependent variable.mp4

04:40

87 - 411 413 415 Deploy a model to a realtime endpoint.mp4

03:53

88 - 411 413 415 Test a realtime deployed service.mp4

06:00

89 - 411 413 415 Consume the deployed model in endpoint.mp4

03:09

90 - 411 413 415 Make modifications to deployed model.mp4

06:27

91 - 411 413 415 Redeploy a model.mp4

01:28

7 - Practice Exams

8 - Conclusion

92 - Congratulations.mp4

02:00

93 - Conclusion and next steps.mp4

04:55

94 - Ways to reach out.mp4

00:33

95 - Certificate.mp4

01:23

9 - Bonus

96 - Bonus.mp4

01:41

Description

Complete DP-100 Azure Machine Learning training guide to prepare you for DP-100, with practice exams on DP 100 Azure ML

What You'll Learn?

Everything you need to pass the DP-100 exam and receive the Azure Data Scientist Associate certification
All learning objectives found in the DP-100 curriculum, through video lectures, demos, applications, and practice exams
Learn and master Azure Machine Learning, a service by Microsoft that enables anyone to build, deploy, and manage Data Science and Machine Learning solutions
Create a predictive service based on a model that you create, with a full end-to-end walkthrough
Design and prepare a machine learning solution
Explore data and train models
Prepare a model for deployment
Deploy and retrain a model

Who is this for?

Business Analysts who want to build, test, and deploy models quickly, especially if they want to create Data Science solutions and predictive services

Students who want to pass the DP-100 exam and receive the Azure Data Scientist Associate certification

Individuals who want to receive a formal certificate from Microsoft for their progress and achievement (useful for moving upwards and getting hired)

Users who want to create and deploy Data Science and Machine Learning solutions with no-code

Data Scientists who want a more streamlined approach to creating, deploying, and managing Machine Learning solutions and services

Data Scientists and Machine Learning Engineers who want to focus on what matters most, and want to automate the rest (algorithm and hyperparameter tuning, endpoint containerization)

Anyone who wants to learn Azure Machine Learning, a tool for building ML model services, from the most basic to the most advanced

Students who want to make a career in Data Science and Machine Learning

More details

Description
Do you want to quickly build, deploy, and scale Data Science and Machine Learning solutions, without knowing any in-depth code, worrying about containers / endpoints, or coding data pipelines?

Do you want to learn and master Azure Machine Learning, an enterprise-grade service by Microsoft that gives you tools for the end-to-end machine learning lifecycle?

Do you want to build, deploy, and manage high quality models faster and with confidence?

Do you want to be certified from Microsoft, so that you can put it on your Resume/CV and showcase to potential employers that you know how to deploy Data Science solutions using Azure Machine Learning?

Do you want to pass the Microsoft DP 100 on the first try, and want one single complete resource that has everything you need for the DP-100 certification?

Then this is the course for you. Learn from over 15 hours of instructional content with video lectures, demos, real-life applications, and practice exams, with the only complete guide to everything you need to know to pass the DP-100 exam and receive your certification.

This course gives you all the training you need to pass - with detailed lectures, demos, and practice questions for each of the 62 learning objectives within the DP100 curriculum. This course gives you the structure you need to succeed - we go through each learning objective in sequential order, so that you are never lost.

This course is also for those students who want to learn Azure Machine Learning, and its underlying services. Along with the training required to pass the DP 100 certification, students master this tool.

DP-100 Designing and Implementing a Data Science Solution on Azure and Azure Data Scientist Associate certification is also called DP-100, DP100, and DP 100 certifications, and so these are used interchangeably.

What is the DP-100?
The DP-100 is a certification exam offered by Microsoft, that enables you to receive the Azure Data Scientist Associate certification. The exam covers how to design, build, and deploy a Machine Learning solution using Azure Machine Learning. The certification enables you to proves to employers and clients that you can build and operationalize Machine Learning and Data Science solutions and understand the core capabilities of the Azure Machine Learning. The exam format varies, but is most often 40-60 questions within about 2 hours. DP-100 is also referred to as DP 100 or DP100.

What is this course all about?
The purpose of this course is to prepare you for the DP 100 Designing and Implementing a Data Science Solution on Azure exam, so that you can pass it on the first try. It offers you dedicated video lectures, walk through demos, real-life applications, and practice exams to maximize your chances of success. This course covers 100% of the 62 learning objectives in Microsoft's curriculum, and trains you to receive the certification on the first try.

What does the DP-100 cover?
The DP-100 covers how to use Azure Machine Learning to design and implement a Data Science and Machine Learning solution. Specifically, it covers how to design and prepare a Machine Learning solution, how to explore data and train models, how to prepare a model for deployment, and how to deploy and retrain a model. The curriculum covers everything about Azure Machine Learning Studio, in both the designer (no-code) workflow, the Automated ML workflow, and the coding (Python SDK, Notebooks) workflow.

What are the prerequisites of taking the DP-100?
Candidates should have subject matter expertise in applying data science and ML to implement and run ML workloads.

What is Azure Machine Learning?
Azure Machine Learning (or Azure ML for short) is a service from Microsoft to create, validate, and deploy Machine Learning and Data Science solutions. It covers everything you would need, from data preparation, to model training and validation, to endpoint model management, and monitoring / model management. It makes it easier for anyone to deploy Data Science and Machine Learning solutions, especially if you are not familiar with Data Science algorithms, container management, compute monitoring, etc. - it does that all for you. Azure Machine Learning lets Data Scientists focus on what matters most, and automates the rest. It gives the power of Data Science and Machine Learning to anyone.

Why is Azure Machine Learning so important?
Azure Machine Learning is Microsoftâ€™s way to democratize Machine Learning and Data Science to the everyday user.

Why should you get the DP-100 certification?
The DP-100 certification from Microsoft is a recognized way to prove that you understand and can use Azure Machine Learning to build business critical machine learning models at scale. You can use the knowledge you learn in the DP-100 course to create impact in your organization, but deploying predictive services and endpoints. You can add it to your resume to significantly boost your chances of employment. Most employers even cover the cost of the training and exam because of the value that this certification provides. In certain countries, you can even receive ACE college credits.

Why choose this course?
Complete guide - this is the 100% complete, start to finish zero to hero training guide to passing the DP 100 exam. It includes lectures, demos, study guides, practice exams, and more. It is the only resource that you will ever need to ace the exam. It contains over 15 hours of instructional content!
Full coverage - we go through Microsoft's curriculum one-by-one and cover all aspects of each of the 62 different learning objectives. This means no surprises on the exam, and it ensures that you are best prepared to pass the DP-100 exam on the first try.
Structured to succeed - the course mirrors Microsoft's DP 100 curriculum exactly. Each of the 62 learning objectives has a combination of a PDF study guide, full video lectures, full video walk through demos, and application.
Instructional and applicable - we not only go through important concepts, but also apply them as we are building our application so that we can solidify them. This is not only a walkthrough of the all the features and theoretical concepts, but a DP-100 course that actually builds applications with you
Practice exams - this course contains practice exams with questions that exactly mirror the types of questions found on the DP-100 exam. Use them to validate your knowledge and find weaker areas where you need to review.
Step by step - each learning objective within Microsoft's DP 100 curriculum is covered in order, step by step. This ensures that you never get lost in the course.
Teacher response - if there's anything else you would like to learn, or if there's something you cannot figure out, I'm here for you! Look at the ways to reach out video
Community - when you enroll in this course, you join a DP100 community full of learners just like you
Master a new tool - Learn Azure Machine Learning, from basic no-code designer tools to fully customized code deployments using Python SDK

Course overview theory
The course follows exactly according to DP100 curriculum, based on 62 learning objectives (LO) that Microsoft has defined. Everything in this course is made to maximize your chances of passing the exam. For each learning objective, the course offers a combination of guided lecture videos, walk-through demos, and application. We then end with practice exams.

Course overview
Introduction - learn about the DP 100 exam and how best to succeed
Environment Setup - set up an Azure account so you can follow along, and review the curriculum
LO1: Design and prepare a machine learning solution (20â€“25%)
LO2: Explore data and train models (35â€“40%)
LO3: Prepare a model for deployment (20â€“25%)
LO4: Deploy and retrain a model (10â€“15%)
Practice Exams - practice what you have learned to validate your knowledge
Conclusion - take your exam, earn your certification, and next steps

Icons by Freepik / Flaticon. Music by Bensound.
Who this course is for:
Business Analysts who want to build, test, and deploy models quickly, especially if they want to create Data Science solutions and predictive services
Students who want to pass the DP-100 exam and receive the Azure Data Scientist Associate certification
Individuals who want to receive a formal certificate from Microsoft for their progress and achievement (useful for moving upwards and getting hired)
Users who want to create and deploy Data Science and Machine Learning solutions with no-code
Data Scientists who want a more streamlined approach to creating, deploying, and managing Machine Learning solutions and services
Data Scientists and Machine Learning Engineers who want to focus on what matters most, and want to automate the rest (algorithm and hyperparameter tuning, endpoint containerization)
Anyone who wants to learn Azure Machine Learning, a tool for building ML model services, from the most basic to the most advanced
Students who want to make a career in Data Science and Machine Learning

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As a manager at one of the world's top management consulting firms, he advises F500 companies on growth strategy, operation, and analytics. He has a vast background in applying data-driven solutions to create impact, in both large and small organizations. Henry is also a big proponent of no-code application development in business. He deploys business application to his clients using No-Code solutions, which are much easier to understand and faster. He believes in the No-Code revolution. As a professor, Henry is passionate about teaching students on how to succeed, on any topic (case interviews, no-code application development, automation). He does this by creating courses with engaging and helpful content, and always being around to answer any questions.

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