Get started on your data science journey, as you learn what it takes to become a Data Scientist. Learn to work with and explore data using a variety of visualization, analytical, and statistical techniques.

Option 1: Analyzing and Visualizing Data with Excel

Explore tools in Excel that enable the analysis of more data than ever before, with improved visualizations and more sophisticated business logic. Learn how to import data from different sources, create mashups between data sources, and prepare data for analysis.



Option 2: Analyzing and Visualizing Data with Power BI

Learn how to connect and visualize your data with Microsoft Power BI. Find out how to import your data, author reports using Power BI Desktop, and publish those reports to the Power BI service. Create dashboards and share with business users on the web and on mobile devices.


Learn effective strategies and tools to master data communication in the most impactful way possible—through well-crafted analytics stories. Find out how stories create value and why they matter.

Learn to apply ethical and legal frameworks to initiatives in the data profession. You will explore practical approaches to data and analytics problems posed by work in Big Data, Data Science, and AI.

From querying and modifying data in SQL Server or Azure SQL to programming with Transact-SQL, learn essential skills that employers need.

Option 1: Introduction to R for Data Science

Learn the R statistical programming language, the tool of choice for data science professionals. Discover its basic syntax, starting with variables and basic operations, and then learn how to handle data structures, such as vectors, matrices, data frames, and lists.


Option 2: Introduction to Python for Data Science

Learn the basics of Python, including simple arithmetic operations, variables, and data structures. Explore Python functions and control flow, and create your own visualizations based on real data.

Option 1: Essential Math for Machine Learning: R Edition

Learn the essential mathematical foundations for machine learning and artificial intelligence using R. The couse focuses on mathematical concepts that you’ll encounter in studies of machine learning.



Option 2: Essential Math for Machine Learning: Python Edition

Learn the essential mathematical foundations for machine learning and artificial intelligence using Python. The couse focuses on mathematical concepts that you’ll encounter in studies of machine learning.


Option 1: Data Science Research Methods: R Edition

Learn the essential skills and hands-on experience with the science and research aspects of data science work using R, from setting up a proper data study to making valid claims and inferences from data experiments.



Option 2: Data Science Research Methods: Python Edition

Learn the essential skills and hands-on experience with the science and research aspects of data science work using Python, from setting up a proper data study to making valid claims and inferences from data experiments.

Option 1: Principles of Machine Learning: R Edition

Get hands-on experience building and deriving insights from machine learning models using R and Azure Notebooks.


Option 2: Principles of Machine Learning: Python Edition

Get hands-on experience building and deriving insights from machine learning models using Python and Azure Notebooks.

Option 1: Developing Big Data Solutions with Azure Machine Learning

Learn how to build predictive web services for Big Data workflows using Azure Machine Learning.



Option 2: Implementing Predictive Solutions with Spark in HDInsight

Learn how to use Spark in Microsoft Azure HDInsight to create predictive analytics and machine learning solutions. Find out how to cleanse and transform data, build machine learning models, and create real-time machine learning solutions using Python, Scala, and R with Apache Spark.


Option 3: Analyzing Big Data with Microsoft R

Learn how to use Microsoft R to analyze large datasets using R, one of the most powerful programming languages.

Showcase the knowledge and skills you’ve acquired during the Microsoft Professional Program for Data Science, and solve a real-world data science problem in this program capstone project. The project takes the form of a challenge in which you will explore a dataset and develop a machine learning solution that is tested and scored to determine your grade. Note: This course assumes you have completed the previous courses in the Microsoft Professional Program for Data Science.