Prepare for DP-100: Data Science on Microsoft Azure Exam from 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.

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.

What's inside

Syllabus

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.

Exam preparation - Course 1

In this module you’ll review Course 1 of the Microsoft Azure Data Scientist Associate specialization.

Exam preparation - Course 2

In this module you’ll review Course 2 of the Microsoft Azure Data Scientist Associate specialization.

Exam preparation - Course 3

In this module you’ll review Course 3 of the Microsoft Azure Data Scientist Associate specialization.

Exam preparation - Course 4

In this module you’ll review Course 4 of the Microsoft Azure Data Scientist Associate specialization.

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.

Good to know

Know what's good

, what to watch for

, and possible dealbreakers

Examines Microsoft role-based certifications, important for career advancement

Covers all topics covered in the DP-100 certification exam, ensuring thorough preparation

Provides a comprehensive review of the Microsoft Azure Data Scientist Associate specialization, reinforcing key concepts

Offers a detailed overview of the Microsoft certification program, guiding career advancement

Course is part of a five-course program, providing a structured learning path towards certification

Taught by Microsoft instructors, recognized experts in the field

Activities

Be better prepared before your course. Deepen your understanding during and after it. Supplement your coursework and achieve mastery of the topics covered in Prepare for DP-100: Data Science on Microsoft Azure Exam with these activities:

Review basics of machine learning

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Review core concepts in machine learning to strengthen foundational knowledge and enhance understanding of the course materials.

Browse courses on Machine Learning Basics

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Read introductory resources on machine learning concepts, such as supervised learning, unsupervised learning, and model evaluation
Complete online tutorials or exercises to practice implementing basic machine learning algorithms
Review existing notes or materials from previous machine learning courses or projects

Solve practice problems on Azure Machine Learning

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Engage in hands-on practice to reinforce skills in using Azure Machine Learning for data preparation, model training, and deployment.

Browse courses on Azure Machine Learning

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Access online platforms or resources that provide practice problems related to Azure Machine Learning
Set aside dedicated time to solve these practice problems, focusing on applying concepts learned in the course
Review solutions and identify areas for improvement or further learning

Follow tutorials on Azure Databricks for data exploration and modeling

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Expand knowledge and practical skills in using Azure Databricks for data exploration, preparation, and modeling to enhance understanding of the course content.

Browse courses on Azure Databricks

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Identify online tutorials or documentation that provide step-by-step guidance on using Azure Databricks for data exploration and modeling
Follow the tutorials and complete the exercises, applying the concepts and techniques covered in the course
Document insights and learnings gained from completing the tutorials

Three other activities

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Contribute to open-source projects related to data science

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Gain practical experience, expand knowledge, and contribute to the data science community by participating in open-source projects.

Browse courses on Data Science Projects

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Identify open-source projects on platforms like GitHub that align with interests and skills
Reach out to project maintainers and express interest in contributing
Work on specific tasks or issues within the project, contributing code or documentation
Collaborate with other contributors and learn from their expertise

Participate in Azure Machine Learning hackathons or competitions

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Enhance problem-solving skills, foster innovation, and deepen understanding of Azure Machine Learning by participating in industry-related events.

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Locate and register for Azure Machine Learning hackathons or competitions that align with interests and skill level
Collaborate with others or work individually to develop and submit solutions
Learn from the experiences and solutions of other participants

Develop a data science project using Azure Machine Learning

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Demonstrate proficiency in applying course concepts by creating a practical data science project leveraging Azure Machine Learning.

Browse courses on Data Science Project

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Identify a real-world problem or dataset that can be addressed using machine learning
Design and implement a data science solution using Azure Machine Learning, covering data preparation, model training, and deployment
Evaluate the performance of the solution and document the results
Prepare a presentation or report to showcase the project and its outcomes

Career center

Learners who complete Prepare for DP-100: Data Science on Microsoft Azure Exam will develop knowledge and skills that may be useful to these careers:

Machine Learning Engineer

A Machine Learning Engineer builds, deploys, and maintains machine learning models. The course prepares learners for the DP-100: Data Science on Microsoft Azure Exam, which will help them demonstrate their proficiency in operating machine learning solutions using Azure Machine Learning. The course curriculum includes managing Azure resources for machine learning, running experiments and training models, and deploying and operationalizing machine learning solutions, all of which are essential skills for a successful Machine Learning Engineer.

See salaries and explore the career path for Machine Learning Engineer

Data Scientist

The course prepares learners for the DP-100: Data Science on Microsoft Azure Exam. A Data Scientist uses Azure Machine Learning to build and operate machine learning solutions at a cloud scale. This course teaches learners how to manage data ingestion and preparation, model training and deployment, and machine learning solution monitoring. With this knowledge, graduates will be well-prepared for a career as a Data Scientist.

See salaries and explore the career path for Data Scientist

Data Analyst

The course helps learners prepare for the DP-100: Data Science on Microsoft Azure Exam, which assesses their ability to manage data ingestion and preparation, model training and deployment, and machine learning solution monitoring. Data Analysts leverage this knowledge to analyze and interpret data to extract meaningful insights and inform decision-making. By completing the course, learners can enhance their skills and advance their careers as Data Analysts.

See salaries and explore the career path for Data Analyst

Business Intelligence Analyst

Business Intelligence Analysts use data analysis to provide insights and recommendations to businesses. The course prepares learners for the DP-100: Data Science on Microsoft Azure Exam, which tests their ability to manage data ingestion and preparation, model training and deployment, and machine learning solution monitoring. These skills enable Business Intelligence Analysts to effectively analyze data, identify trends, and develop strategies to improve business outcomes.

See salaries and explore the career path for Business Intelligence Analyst

Data Engineer

A Data Engineer designs, builds, and maintains data pipelines, which are systems that collect, process, and store data. The course prepares learners for the DP-100: Data Science on Microsoft Azure Exam, which assesses their ability to manage Azure resources for machine learning, run experiments and train models, and deploy and operationalize machine learning solutions. These skills can enhance the capabilities of Data Engineers to build and maintain robust data pipelines for various applications.

See salaries and explore the career path for Data Engineer

Software Engineer

Software Engineers design, develop, and maintain software systems. The course may be useful for Software Engineers who want to specialize in developing machine learning solutions. It covers topics such as managing Azure resources for machine learning, running experiments and training models, and deploying and operationalizing machine learning solutions. These skills can complement the technical expertise of Software Engineers and enable them to build innovative and efficient machine learning applications.

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Cloud Architect

Cloud Architects design and manage cloud computing environments. The course may be useful for Cloud Architects who want to gain expertise in designing and implementing machine learning solutions on Microsoft Azure. It covers topics such as managing Azure resources for machine learning, running experiments and training models, and deploying and operationalizing machine learning solutions. These skills can help Cloud Architects create scalable and reliable machine learning environments that meet the needs of organizations.

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Product Manager

Product Managers lead the development and launch of new products or features. The course may be useful for Product Managers who want to incorporate machine learning into their products. It covers topics such as managing Azure resources for machine learning, running experiments and training models, and deploying and operationalizing machine learning solutions. These skills can help Product Managers make informed decisions about the integration of machine learning into their products and ensure successful outcomes.

See salaries and explore the career path for Product Manager

Quantitative Analyst

Quantitative Analysts use mathematical and statistical models to analyze and forecast financial data. The course may be useful for Quantitative Analysts who want to apply machine learning techniques to their work. It covers topics such as managing Azure resources for machine learning, running experiments and training models, and deploying and operationalizing machine learning solutions. These skills can enhance the capabilities of Quantitative Analysts to develop more accurate and sophisticated financial models.

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Research Scientist

Research Scientists conduct research and develop new theories and technologies. The course may be useful for Research Scientists who want to explore the application of machine learning in their field. It covers topics such as managing Azure resources for machine learning, running experiments and training models, and deploying and operationalizing machine learning solutions. These skills can enable Research Scientists to leverage machine learning to make breakthroughs in their respective disciplines.

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Data Science Manager

Data Science Managers lead teams of data scientists and oversee the development and implementation of machine learning solutions. The course prepares learners for the DP-100: Data Science on Microsoft Azure Exam, which assesses their ability to manage Azure resources for machine learning, run experiments and train models, and deploy and operationalize machine learning solutions. These skills are crucial for Data Science Managers to effectively lead their teams and ensure the successful execution of machine learning projects.

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Machine Learning Researcher

Machine Learning Researchers develop new machine learning algorithms and techniques. The course may be useful for Machine Learning Researchers who want to gain practical experience in applying machine learning on Microsoft Azure. It covers topics such as managing Azure resources for machine learning, running experiments and training models, and deploying and operationalizing machine learning solutions. These skills can complement the theoretical knowledge of Machine Learning Researchers and enable them to contribute to the advancement of the field.

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Data Visualization Engineer

Data Visualization Engineers design and develop data visualizations to communicate insights from data. The course may be useful for Data Visualization Engineers who want to incorporate machine learning into their visualizations. It covers topics such as managing Azure resources for machine learning, running experiments and training models, and deploying and operationalizing machine learning solutions. These skills can enable Data Visualization Engineers to create more interactive and informative visualizations that effectively convey the value of machine learning insights.

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IT Consultant

IT Consultants advise businesses on the use of technology. The course may be useful for IT Consultants who want to specialize in advising clients on machine learning solutions. It covers topics such as managing Azure resources for machine learning, running experiments and training models, and deploying and operationalizing machine learning solutions. These skills can enable IT Consultants to provide valuable guidance to clients and help them make informed decisions about the adoption of machine learning.

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Business Analyst

Business Analysts analyze business processes and develop solutions to improve efficiency. The course may be useful for Business Analysts who want to incorporate machine learning into their solutions. It covers topics such as managing Azure resources for machine learning, running experiments and training models, and deploying and operationalizing machine learning solutions. These skills can enable Business Analysts to develop more innovative and data-driven solutions that drive business value.

See salaries and explore the career path for Business Analyst