We may earn an affiliate commission when you visit our partners.
Amy Coughlin
In this course, **DP-100: Designing and Implementing a Data Science Solution on Azure**, you’ll learn to design, build, run, optimize, manage, and monitor machine learning experiments in Azure, with a focus on the objectives outlined in the Microsoft DP-100 certification exam study guide, including: * Designing and preparing a machine learning solution * Exploring data and training models * Preparing a model for deployment * Deploying and retraining a model When you’re finished with the course lessons, labs, quizzes, and practice exams, you’ll have the skills and knowledge necessary to approach the DP-100 exam with confidence.
Register for this course and see more details by visiting:
OpenCourser.com/course/u67ssc/dp
Here's a deal for you
We found an offer that may be relevant to this course.
Save money when you learn.
All coupon codes, vouchers, and discounts are applied automatically unless otherwise noted.
Good to know
Good to know
Know what's good ,
what to watch for , and
possible dealbreakers
Explores designing and implementing a data science solution on Azure, which is highly relevant to individuals working in cloud computing and data analysis
Covers the objectives outlined in the Microsoft DP-100 certification exam study guide, which can be valuable for learners seeking industry recognition
Provides hands-on labs and interactive materials, enabling learners to apply the concepts and techniques discussed in the course
Taught by Amy Coughlin, an experienced instructor recognized for her expertise in data science and machine learning
Examines designing, preparing, deploying, and retraining a machine learning model, which are core skills for data scientists and machine learning engineers
Save this course
Save DP-100: Designing and Implementing a Data Science Solution on Azure to your list so you can find it easily later:
Save
Save
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 DP-100: Designing and Implementing a Data Science Solution on Azure with these
activities:
Review core Python concepts
Show steps
Refreshes your understanding of core Python concepts to strengthen your foundation for this course.
Browse courses on
Python
Show steps
-
Revisit basic data types, variables, and operators
-
Review control flow statements (if-else, loops)
-
Practice writing simple functions
Consolidate and organize course materials
Show steps
Improves retention by consolidating and organizing your notes and materials.
Show steps
-
Gather and organize notes, slides, and assignments
-
Create a note-taking system and review materials regularly
Solve practice problems on data preprocessing techniques
Show steps
Develops your proficiency in data preprocessing techniques through practice.
Browse courses on
Data Preprocessing
Show steps
-
Find practice problems or exercises online
-
Solve problems related to data cleaning, handling missing values, and feature scaling
Four other activities
Expand to see all activities and additional details
Show all seven activities
Follow tutorials on model evaluation metrics
Show steps
Expands your understanding of model evaluation metrics and their applications.
Browse courses on
Model Evaluation
Show steps
-
Search for tutorials on common model evaluation metrics
-
Follow the tutorials to learn about different metrics and their strengths and weaknesses
Participate in study group discussions
Show steps
Strengthens your understanding through discussions and collaboration with peers.
Show steps
-
Join or form a study group with other course participants
-
Discuss course concepts, share insights, and work on assignments together
Develop a data science solution prototype
Show steps
Applies your learning by creating a practical solution to a real-world problem.
Show steps
-
Identify a suitable problem or use case
-
Design and implement a machine learning solution
-
Deploy and evaluate the solution
Initiate a personal machine learning project
Show steps
Provides practical experience and deepens your understanding by applying your knowledge in a real-world setting.
Show steps
-
Define a project scope and goals
-
Collect and prepare data
-
Build, train, and evaluate a machine learning model
Review core Python concepts
Show steps
Refreshes your understanding of core Python concepts to strengthen your foundation for this course.
Browse courses on
Python
Show steps
Show steps
Show steps
- Revisit basic data types, variables, and operators
- Review control flow statements (if-else, loops)
- Practice writing simple functions
Consolidate and organize course materials
Show steps
Improves retention by consolidating and organizing your notes and materials.
Show steps
Show steps
Show steps
- Gather and organize notes, slides, and assignments
- Create a note-taking system and review materials regularly
Solve practice problems on data preprocessing techniques
Show steps
Develops your proficiency in data preprocessing techniques through practice.
Browse courses on
Data Preprocessing
Show steps
Show steps
Show steps
- Find practice problems or exercises online
- Solve problems related to data cleaning, handling missing values, and feature scaling
Four other activities
Expand to see all activities and additional details
Show all seven activities
Follow tutorials on model evaluation metrics
Show steps
Expands your understanding of model evaluation metrics and their applications.
Browse courses on
Model Evaluation
Show steps
Show steps
Show steps
- Search for tutorials on common model evaluation metrics
- Follow the tutorials to learn about different metrics and their strengths and weaknesses
Participate in study group discussions
Show steps
Strengthens your understanding through discussions and collaboration with peers.
Show steps
Show steps
Show steps
- Join or form a study group with other course participants
- Discuss course concepts, share insights, and work on assignments together
Develop a data science solution prototype
Show steps
Applies your learning by creating a practical solution to a real-world problem.
Show steps
Show steps
Show steps
- Identify a suitable problem or use case
- Design and implement a machine learning solution
- Deploy and evaluate the solution
Initiate a personal machine learning project
Show steps
Provides practical experience and deepens your understanding by applying your knowledge in a real-world setting.
Show steps
Show steps
Show steps
- Define a project scope and goals
- Collect and prepare data
- Build, train, and evaluate a machine learning model
Career center
Learners who complete DP-100: Designing and Implementing a Data Science Solution on Azure will develop knowledge and skills
that may be useful to these careers:
Data Scientist
Data Scientist
Data Scientists collect and analyze data, identify patterns, and use those patterns to make predictions or recommendations. They build and maintain predictive models that can be used to achieve business goals. The DP-100 course teaches the skills and knowledge necessary to design, build, run, optimize, manage, and monitor machine learning experiments in Azure, which are essential skills for Data Scientists. By completing this course, learners will be well-prepared to enter or advance their career in Data Science.
Machine Learning Engineer
Machine Learning Engineer
Machine Learning Engineers design, develop, and maintain machine learning models. They work closely with Data Scientists to ensure that models are accurate and efficient. The DP-100 course teaches the skills and knowledge necessary to design, build, run, optimize, manage, and monitor machine learning experiments in Azure, which are essential skills for Machine Learning Engineers. By completing this course, learners will be well-prepared to enter or advance their career in Machine Learning Engineering.
Data Analyst
Data Analyst
Data Analysts collect, clean, and analyze data to identify trends and patterns. They use their findings to make recommendations to businesses on how to improve their operations. The DP-100 course teaches the skills and knowledge necessary to design, build, run, optimize, manage, and monitor machine learning experiments in Azure, which can be helpful for Data Analysts who want to use machine learning to improve their data analysis. By completing this course, learners will be well-prepared to enter or advance their career in Data Analysis.
Business Intelligence Analyst
Business Intelligence Analyst
Business Intelligence Analysts use data to help businesses make better decisions. They analyze data to identify trends and patterns, and they develop reports and visualizations to communicate their findings to business leaders. The DP-100 course teaches the skills and knowledge necessary to design, build, run, optimize, manage, and monitor machine learning experiments in Azure, which can be helpful for Business Intelligence Analysts who want to use machine learning to improve their data analysis. By completing this course, learners will be well-prepared to enter or advance their career in Business Intelligence Analysis.
Data Engineer
Data Engineer
Data Engineers design, build, and maintain data pipelines. They work with Data Scientists and Machine Learning Engineers to ensure that data is available and accessible for analysis and modeling. The DP-100 course teaches the skills and knowledge necessary to design, build, run, optimize, manage, and monitor machine learning experiments in Azure, which can be helpful for Data Engineers who want to learn more about machine learning. By completing this course, learners will be well-prepared to enter or advance their career in Data Engineering.
Software Engineer
Software Engineer
Software Engineers design, develop, and maintain software applications. They work with Data Scientists and Machine Learning Engineers to integrate machine learning models into software applications. The DP-100 course teaches the skills and knowledge necessary to design, build, run, optimize, manage, and monitor machine learning experiments in Azure, which can be helpful for Software Engineers who want to learn more about machine learning. By completing this course, learners will be well-prepared to enter or advance their career in Software Engineering.
Database Administrator
Database Administrator
Database Administrators design, build, and maintain databases. They work with Data Scientists and Machine Learning Engineers to ensure that data is stored and managed efficiently. The DP-100 course teaches the skills and knowledge necessary to design, build, run, optimize, manage, and monitor machine learning experiments in Azure, which can be helpful for Database Administrators who want to learn more about machine learning. By completing this course, learners will be well-prepared to enter or advance their career in Database Administration.
Cloud Architect
Cloud Architect
Cloud Architects design and manage cloud computing environments. They work with Data Scientists and Machine Learning Engineers to ensure that machine learning models are deployed and managed in a scalable and efficient manner. The DP-100 course teaches the skills and knowledge necessary to design, build, run, optimize, manage, and monitor machine learning experiments in Azure, which can be helpful for Cloud Architects who want to learn more about machine learning. By completing this course, learners will be well-prepared to enter or advance their career in Cloud Architecture.
Data Visualization Specialist
Data Visualization Specialist
Data Visualization Specialists create visualizations to communicate data insights to business leaders. They work with Data Scientists and Machine Learning Engineers to create visualizations that are clear, concise, and actionable. The DP-100 course teaches the skills and knowledge necessary to design, build, run, optimize, manage, and monitor machine learning experiments in Azure, which can be helpful for Data Visualization Specialists who want to learn more about machine learning. By completing this course, learners will be well-prepared to enter or advance their career in Data Visualization.
Actuary
Actuary
Actuaries use data to assess the financial risks of insurance companies. They work with Data Scientists and Machine Learning Engineers to use machine learning to improve risk assessment. The DP-100 course teaches the skills and knowledge necessary to design, build, run, optimize, manage, and monitor machine learning experiments in Azure, which can be helpful for Actuaries who want to learn more about machine learning. By completing this course, learners will be well-prepared to enter or advance their career in Actuarial Science.
Statistician
Statistician
Statisticians use data to design and conduct experiments, analyze data, and interpret results. They work with Data Scientists and Machine Learning Engineers to use machine learning to improve data analysis. The DP-100 course teaches the skills and knowledge necessary to design, build, run, optimize, manage, and monitor machine learning experiments in Azure, which can be helpful for Statisticians who want to learn more about machine learning. By completing this course, learners will be well-prepared to enter or advance their career in Statistics.
Financial Analyst
Financial Analyst
Financial Analysts use data to make investment decisions. They work with Data Scientists and Machine Learning Engineers to use machine learning to improve investment decisions. The DP-100 course teaches the skills and knowledge necessary to design, build, run, optimize, manage, and monitor machine learning experiments in Azure, which can be helpful for Financial Analysts who want to learn more about machine learning. By completing this course, learners will be well-prepared to enter or advance their career in Financial Analysis.
Marketing Analyst
Marketing Analyst
Marketing Analysts use data to understand customer behavior and develop marketing campaigns. They work with Data Scientists and Machine Learning Engineers to use machine learning to improve marketing campaigns. The DP-100 course teaches the skills and knowledge necessary to design, build, run, optimize, manage, and monitor machine learning experiments in Azure, which can be helpful for Marketing Analysts who want to learn more about machine learning. By completing this course, learners will be well-prepared to enter or advance their career in Marketing Analytics.
Risk Analyst
Risk Analyst
Risk Analysts use data to identify and assess risks. They work with Data Scientists and Machine Learning Engineers to use machine learning to improve risk assessment. The DP-100 course teaches the skills and knowledge necessary to design, build, run, optimize, manage, and monitor machine learning experiments in Azure, which can be helpful for Risk Analysts who want to learn more about machine learning. By completing this course, learners will be well-prepared to enter or advance their career in Risk Analysis.
Product Manager
Product Manager
Product Managers are responsible for the development and launch of new products and features. They work with Data Scientists and Machine Learning Engineers to ensure that new products and features are based on data-driven insights. The DP-100 course teaches the skills and knowledge necessary to design, build, run, optimize, manage, and monitor machine learning experiments in Azure, which can be helpful for Product Managers who want to learn more about machine learning. By completing this course, learners will be well-prepared to enter or advance their career in Product Management.
For more career information including salaries, visit:
OpenCourser.com/course/u67ssc/dp
Reading list
We've selected nine books
that we think will supplement your
learning. Use these to
develop background knowledge, enrich your coursework, and gain a
deeper understanding of the topics covered in
DP-100: Designing and Implementing a Data Science Solution on Azure.
Save
Provides a comprehensive overview of deep learning. It covers the fundamentals of deep learning, deep learning architectures, and deep learning applications.
Classic textbook on statistical learning. It provides a comprehensive coverage of the underlying mathematical and statistical foundations of machine learning.
Provides a practical introduction to machine learning using R. It covers the fundamentals of machine learning, data preparation, model training and evaluation, and model deployment.
Provides a comprehensive introduction to machine learning using Python. It covers the fundamentals of machine learning, data preparation, model training and evaluation, and model deployment.
Provides a probabilistic perspective on machine learning. It covers the fundamental concepts of probability theory, Bayesian inference, and graphical models.
Save
Provides a comprehensive overview of data mining techniques. It covers the fundamentals of data mining, data preparation, model training and evaluation, and model deployment.
Is designed for readers with no prior knowledge of machine learning. It provides a gentle introduction to the fundamental concepts, with a focus on practical applications.
Is suitable for readers who have some programming experience and are interested in learning deep learning. It covers the fundamentals of deep learning and provides practical examples using fastai and PyTorch.
Is designed for readers with no prior knowledge of machine learning. It provides a clear and concise introduction to the fundamental concepts, with a focus on practical applications. Suitable as a background or introductory text.
For more information about how these books relate to this course, visit:
OpenCourser.com/course/u67ssc/dp
Share
Similar courses
Here are nine courses similar to
DP-100: Designing and Implementing a Data Science Solution on Azure.
Prepare for DP-100: Data Science on Microsoft Azure Exam
OpenCourser.com/course/wcbl5r/prepare
Prepare for DP-100: Data Science on Microsoft Azure Exam
Most relevant
Perform data science with Azure Databricks
OpenCourser.com/course/gaa7fh/perform
Perform data science with Azure Databricks
Most relevant
Build and Operate Machine Learning Solutions with Azure
OpenCourser.com/course/mztrml/build
Build and Operate Machine Learning Solutions with Azure
Most relevant
Microsoft Azure Machine Learning for Data Scientists
OpenCourser.com/course/rfp7xr/microsoft
Microsoft Azure Machine Learning for Data Scientists
Most relevant
DP-203: Processing in Azure Using Streaming Solutions
OpenCourser.com/course/53e3se/dp
DP-203: Processing in Azure Using Streaming Solutions
Most relevant
Create Machine Learning Models in Microsoft Azure
OpenCourser.com/course/bxmp4q/create
Create Machine Learning Models in Microsoft Azure
Most relevant
Data Integration with Microsoft Azure Data Factory
OpenCourser.com/course/ri63yn/data
Data Integration with Microsoft Azure Data Factory
Most relevant
Data Storage in Microsoft Azure for Associate Developers
OpenCourser.com/course/o1vpe2/data
Data Storage in Microsoft Azure for Associate Developers
Most relevant
Data Storage in Microsoft Azure
OpenCourser.com/course/sonykf/data
Data Storage in Microsoft Azure
Most relevant
Time
1290 hours
Level
Advanced
Via
Pluralsight
Instructor
Amy Coughlin
Language
English
Good to know
Explores designing and implementing a data science solution on Azure, which is highly relevant to individuals working in cloud computing and data analysis
Covers the objectives outlined in the Microsoft DP-100 certification exam study guide, which can be valuable for learners seeking industry recognition
Provides hands-on labs and interactive materials, enabling learners to apply the concepts and techniques discussed in the course
Taught by Amy Coughlin, an experienced instructor recognized for her expertise in data science and machine learning
Examines designing, preparing, deploying, and retraining a machine learning model, which are core skills for data scientists and machine learning engineers
Our mission
OpenCourser helps millions of learners each year. People visit us to learn workspace skills, ace their exams, and nurture their curiosity.
Our extensive catalog contains over 50,000 courses and twice as many books. Browse by search, by topic, or even by career interests. We'll match you to the right resources quickly.
Find this site helpful? Tell a friend about us.
Affiliate disclosure
We're supported by our community of learners. When you purchase or subscribe to courses and programs or purchase books, we may earn a commission from our partners.
Your purchases help us maintain our catalog and keep our servers humming without ads.
Thank you for supporting OpenCourser.
© 2016 - 2024 OpenCourser