Microsoft Professional Program (MPP): Data Science

Microsoft Professional Program (MPP): Data Science

Program

Microsoft MPP-DS

From USD 890.00

To USD 1,188.00

Gain the skills you need to get the data science job you want.

Abstract


Accelerate your career in one of the hottest fields – data science. Learn data science fundamentals, key data science tools, and widely-used programming languages from industry and academic experts in this unique program created by Microsoft.

Built in collaboration with leading universities and employers, the Microsoft Professional Program Certificate in Data Science will develop the analytical and programming skills you need to take advantage of the 1.5 million career opportunities available now in data science.


What you'll learn


  • Use Microsoft Excel to explore data
  • Use Transact-SQL to query a relational database
  • Create data models and visualize data using Excel or Power BI
  • Apply statistical methods to data
  • Use R or Python to explore and transform data
  • Follow a data science methodology
  • Create and validate machine learning models with Azure Machine Learning
  • Write R or Python code to build machine learning models
  • Apply data science techniques to common scenarios
  • Implement a machine learning solution for a given data problem


To be eligible to earn a certificate for completing the Microsoft Professional Program for Data Science, please go to https://academy.microsoft.com/en-us/professional-program/tracks/data-science/ to create a Microsoft Academy account. After signing up, you’ll be able to track your progress on a personalized dashboard that updates every time you earn a Verified Certificate in a course from the Data Science track.


How it works


Made up of three units and a final project, the Microsoft Professional Program Certificate in Data Science provides a comprehensive program of study in data science. Learners can choose from different courses within each unit of study. For example, in Unit 1 - Fundamentals you can choose between Analyzing and Visualizing Data with Excel or Analyzing and Visualizing Data with Power BI to satisfy the requirement.


Data Science Professional Program - Unit Overview


  • Unit 1 - Fundamentals
    • Course 1: Introduction to Data Science
    • Course 2a: Analyzing and Visualizing Data with Power BI  |   Course 2b: Analyzing and Visualizing Data with Excel
    • Course 3: Analytics Storytelling for Impact
    • Course 4: Ethics and Law in Data and Analytics
  • Unit 2 - Core Data Science
    • Course 5: Querying Data with Transact-SQL
    • Course 6a: Introduction to R for Data Science Course   |   6b: Introduction to Python for Data Science
    • Course 7a: Essential Math for Machine Learning: R Edition Course   |   7b: Essential Math for Machine Learning: Python Edition Course   |   7c: Essential Statistics for Data Analysis using Excel
  • Unit 3 - Applied Data Science
    • Course 8a: Data Science Research Methods: R Edition   |   Course 8b: Data Science Research Methods: Python Edition
    • Course 9a: Principles of Machine Learning: R Edition   |   Course 9b: Principles of Machine Learning: Python Edition
    • Course 10a: Developing Big Data Solutions with Azure Machine Learning   |   Course 10b: Analyzing Big Data with Microsoft R   |   Course 10c: Implementing Predictive Analytics with Spark in Azure HDInsight
  • Unit 4 - Capstone Project
  • Showcase your data science knowledge and skills, and solve a real-world data science problem in Microsoft Professional Capstone : Data Science. 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.

Write Your Own Review

Only registered users can write reviews. Please Sign in or create an account

Unit 1 - Fundamentals

Course 1

Introduction to Data Science

Introduction to Data Science

Microsoft DAT101x
Microsoft
Open edX
90 days
Microsoft Certificate of Completion

This is the first stop in the Data Science curriculum from Microsoft. It will help you get started with the program, plan your learning schedule, and connect with fellow students and teaching assistants. Along the way, you’ll get an introduction to working with and exploring data using a variety of visualization, analytical, and statistical techniques.

Course 2 (choose one)

Analyzing and Visualizing Data with Excel

Analyzing and Visualizing Data with Excel

Microsoft DAT206x
Microsoft
Open edX
90 days
Microsoft Certificate of Completion

Excel is one of the most widely used solutions for analyzing and visualizing data. It now includes tools that enable the analysis of more data, with improved visualizations and more sophisticated business logics. In this data science course, you will get an introduction to the latest versions of these new tools in Excel 2016 from an expert on the Excel Product Team at Microsoft.


Learn how to import data from different sources, create mashups between data sources, and prepare data for analysis. After preparing the data, find out how business calculations can be expressed using the DAX calculation engine. See how the data can be visualized and shared to the Power BI cloud service, after which it can be used in dashboards, queried using plain English sentences, and even consumed on mobile devices.


Do you feel that the contents of this course is a bit too advanced for you and you need to fill some gaps in your Excel knowledge? Do you need a better understanding of how pivot tables, pivot charts and slicers work together, and help in creating dashboards? If so, check out DAT205x: Introduction to Data Analysis using Excel.

Analyzing and Visualizing Data with Power BI

Analyzing and Visualizing Data with Power BI

Microsoft DAT207x
Microsoft
Open edX
90 days
Microsoft Certificate of Completion

Power BI is quickly gaining popularity among professionals in data science as a cloud-based service that helps them easily visualize and share insights from their organizations’ data.


In this data science course, you will learn from the Power BI product team at Microsoft with a series of short, lecture-based videos, complete with demos, quizzes, and hands-on labs. You’ll walk through Power BI, end to end, starting from how to connect to and import your data, author reports using Power BI Desktop, and publish those reports to the Power BI service. Plus, learn to create dashboards and share with business users—on the web and on mobile devices.

Course 3

Analytics Storytelling for Impact

Analytics Storytelling for Impact

Microsoft DAT248x
Microsoft
Open edX
90 days
Microsoft Certificate of Completion

Course 4

Ethics and Law in Data and Analytics

Ethics and Law in Data and Analytics

Microsoft DAT249x
Microsoft
Open edX
90 days
Microsoft Certificate of Completion

Unit 2 - Core Data Science

Course 5

Querying with Transact-SQL

Querying with Transact-SQL

Microsoft DAT201x
Microsoft
Open edX
90 days
Microsoft Certificate of Completion

Transact-SQL is an essential skill for data professionals and developers working with SQL databases. With this combination of expert instruction, demonstrations, and practical labs, step from your first SELECT statement through to implementing transactional programmatic logic.


Work through multiple modules, each of which explore a key area of the Transact-SQL language, with a focus on querying and modifying data in Microsoft SQL Server or Azure SQL Database. The labs in this course use a sample database that can be deployed easily in Azure SQL Database, so you get hands-on experience with Transact-SQL without installing or configuring a database server.

Course 6 (choose one)

Introduction to R for Data Science

Introduction to R for Data Science

Microsoft DAT204x
Microsoft
Open edX
90 days
Microsoft Certificate of Completion

R is rapidly becoming the leading language in data science and statistics. Today, R is the tool of choice for data science professionals in every industry and field. Whether you are full-time number cruncher, or just the occasional data analyst, R will suit your needs.


This introduction to R programming course will help you master the basics of R. In seven sections, you will cover its basic syntax, making you ready to undertake your own first data analysis using R. Starting from variables and basic operations, you will eventually learn how to handle data structures such as vectors, matrices, data frames and lists. In the final section, you will dive deeper into the graphical capabilities of R, and create your own stunning data visualizations. No prior knowledge in programming or data science is required.


What makes this course unique is that you will continuously practice your newly acquired skills through interactive in-browser coding challenges using the DataCamp platform. Instead of passively watching videos, you will solve real data problems while receiving instant and personalized feedback that guides you to the correct solution.

Introduction to Python for Data Science

Introduction to Python for Data Science

Microsoft DAT208x
Microsoft
Open edX
90 days
Microsoft Certificate of Completion

Python is a very powerful programming language used for many different applications. Over time, the huge community around this open source language has created quite a few tools to efficiently work with Python. In recent years, a number of tools have been built specifically for data science. As a result, analyzing data with Python has never been easier.


In this practical course, you will start from the very beginning, with basic arithmetic and variables, and learn how to handle data structures, such as Python lists, Numpy arrays, and Pandas DataFrames. Along the way, you’ll learn about Python functions and control flow. Plus, you’ll look at the world of data visualizations with Python and create your own stunning visualizations based on real data.

Course 7 (choose one)

Essential Math for Machine Learning: R Edition

Essential Math for Machine Learning: R Edition

Microsoft DAT280x
Microsoft
Open edX
90 days
Microsoft Certificate of Completion

Want to study machine learning or artificial intelligence, but worried that your math skills may not be up to it? Do words like “algebra’ and “calculus” fill you with dread? Has it been so long since you studied math at school that you’ve forgotten much of what you learned in the first place?

You’re not alone. Machine learning and AI are built on mathematical principles like Calculus, Linear Algebra, Probability, Statistics, and Optimization; and many would-be AI practitioners find this daunting. This course is not designed to make you a mathematician. Rather, it aims to help you learn some essential foundational concepts and the notation used to express them. The course provides a hands-on approach to working with data and applying the techniques you’ve learned.

This course is not a full math curriculum. It’s not designed to replace school or college math education. Instead, it focuses on the key mathematical concepts that you’ll encounter in studies of machine learning. It is designed to fill the gaps for students who missed these key concepts as part of their formal education, or who need to refresh their memories after a long break from studying math.

Essential Math for Machine Learning: Python Edition

Essential Math for Machine Learning: Python Edition

Microsoft DAT256x
Microsoft
Open edX
90 days
Microsoft Certificate of Completion

This course is part of the Microsoft Professional Program in Artificial Intelligence.

Want to study machine learning or artificial intelligence, but worried that your math skills may not be up to it? Do words like “algebra’ and “calculus” fill you with dread? Has it been so long since you studied math at school that you’ve forgotten much of what you learned in the first place?

You’re not alone. machine learning and AI are built on mathematical principles like Calculus, Linear Algebra, Probability, Statistics, and Optimization; and many would-be AI practitioners find this daunting. This course is not designed to make you a mathematician. Rather, it aims to help you learn some essential foundational concepts and the notation used to express them. The course provides a hands-on approach to working with data and applying the techniques you’ve learned.

This course is not a full math curriculum; it’s not designed to replace school or college math education. Instead, it focuses on the key mathematical concepts that you’ll encounter in studies of machine learning. It is designed to fill the gaps for students who missed these key concepts as part of their formal education, or who need to refresh their memories after a long break from studying math.

Essential Statistics for Data Analysis using Excel

Essential Statistics for Data Analysis using Excel

Microsoft DAT222x
Microsoft
Open edX
90 days
Microsoft Certificate of Completion

If you’re considering a career as a data analyst, you need to know about histograms, Pareto charts, Boxplots, Bayes’ theorem, and much more. In this applied statistics course, the second in our Microsoft Excel Data Analyst XSeries, use the powerful tools built into Excel, and explore the core principles of statistics and basic probability—from both the conceptual and applied perspectives. Learn about descriptive statistics, basic probability, random variables, sampling and confidence intervals, and hypothesis testing. And see how to apply these concepts and principles using the environment, functions, and visualizations of Excel.

As a data science pro, the ability to analyze data helps you to make better decisions, and a solid foundation in statistics and basic probability helps you to better understand your data. Using real-world concepts applicable to many industries, including medical, business, sports, insurance, and much more, learn from leading experts why Excel is one of the top tools for data analysis and how its built-in features make Excel a great way to learn essential skills.

Before taking this course, you should be familiar with organizing and summarizing data using Excel analytic tools, such as tables, pivot tables, and pivot charts. You should also be comfortable (or willing to try) creating complex formulas and visualizations. Want to start with the basics? Check out DAT205x: Introduction to Data Analysis using Excel. As you learn these concepts and get more experience with this powerful tool that can be extremely helpful in your journey as a data analyst or data scientist, you may want to also take the third course in our series, DAT206x Analyzing and Visualizing Data with Excel. This course includes excerpts from Microsoft Excel 2016: Data Analysis and Business Modeling from Microsoft Press and authored by course instructor Wayne Winston.

Unit 3 - Applied Data Science

Course 8 (choose one)

Data Science Research Methods: R Edition

Data Science Research Methods: R Edition

Microsoft DAT274x
Microsoft
Open edX
90 days
Microsoft Certificate of Completion

Data scientists are often trained in the analysis of data. However, the goal of data science is to produce good understanding of some problem or idea and build useful models on this understanding. Because of the principle of “garbage in, garbage out,” it is vital that the data scientist know how to evaluate the quality of information that comes into a data analysis. This is especially the case when data are collected specifically for some analysis (e.g., a survey).

In this course, you will learn the fundamentals of the research process—from developing a good question to designing good data collection strategies to putting results in context. Although the data scientist may often play a key part in data analysis, the entire research process must work cohesively for valid insights to be gleaned.

Developed as a language with statistical analysis and modeling in mind, R has become an essential tool for doing real-world Data Science. With this edition of Data Science Research Methods, all of the labs are done with R, while the videos are tool-agnostic. If you prefer your Data Science to be done with Python, please see Data Science Research Methods: Python Edition.

Data Science Research Methods: Python Edition

Data Science Research Methods: Python Edition

Microsoft DAT273x
Microsoft
Open edX
90 days
Microsoft Certificate of Completion

Data scientists are often trained in the analysis of data. However, the goal of data science is to produce a good understanding of some problem or idea and build useful models on this understanding. Because of the principle of "garbage in, garbage out," it is vital that a data scientist know how to evaluate the quality of information that comes into a data analysis. This is especially the case when data are collected specifically for some analysis (e.g., a survey).

In this course, you will learn the fundamentals of the research process-from developing a good question to designing good data collection strategies to putting results in context. Although a data scientist may often play a key part in data analysis, the entire research process must work cohesively for valid insights to be gleaned.

Developed as a powerful and flexible language used in everything from Data Science to cutting-edge and scalable Artificial Intelligence solutions, Python has become an essential tool for doing Data Science and Machine Learning. With this edition of Data Science Research Methods, all of the labs are done with Python, while the videos are language-agnostic. If you prefer your Data Science to be done with R, please see Data Science Research Methods: R Edition.

Course 9 (choose one)

Principles of Machine Learning: R Edition

Principles of Machine Learning: R Edition

Microsoft DAT276x
Microsoft
Open edX
90 days
Microsoft Certificate of Completion

Machine learning uses computers to run predictive models that learn from existing data in order to forecast future behaviors, outcomes, and trends.

In this data science course, you will be given clear explanations of machine learning theory combined with practical scenarios and hands-on experience building, validating, and deploying machine learning models. You will learn how to build and derive insights from these models using R, and Azure Notebooks.

Principles of Machine Learning: Python Edition

Principles of Machine Learning: Python Edition

Microsoft DAT275x
Microsoft
Open edX
90 days
Microsoft Certificate of Completion

Machine learning uses computers to run predictive models that learn from existing data in order to forecast future behaviors, outcomes, and trends.

In this data science course, you will be given clear explanations of machine learning theory combined with practical scenarios and hands-on experience building, validating, and deploying machine learning models. You will learn how to build and derive insights from these models using Python, and Azure Notebooks.

Course 10 (choose one)

Developing Big Data Solutions with Azure Machine Learning

Developing Big Data Solutions with Azure Machine Learning

Microsoft DAT228x
Microsoft
Open edX
90 days
Microsoft Certificate of Completion

The past can often be the key to predicting the future. Big data from historical sources is a valuable resource for identifying trends and building machine learning models that apply statistical patterns and predict future outcomes.

This course introduces Azure Machine Learning, and explores techniques and considerations for using it to build models from big data sources, and to integrate predictive insights into big data processing workflows.

Analyzing Big Data with Microsoft R

Analyzing Big Data with Microsoft R

Microsoft DAT213x
Microsoft
Open edX
90 days
Microsoft Certificate of Completion
Implementing Predictive Analytics with Spark in Azure HDInsight

Implementing Predictive Analytics with Spark in Azure HDInsight

Microsoft DAT202.3x
Microsoft
Open edX
90 days
Microsoft Certificate of Completion

Are you ready for big data science? In this course, learn how to implement predictive analytics solutions for big data using Apache Spark in Microsoft Azure HDInsight. See how to work with Scala or Python to cleanse and transform data and build machine learning models with Spark ML (the machine learning library in Spark).


Note: To complete the hands-on elements in this course, you will require an Azure subscription and a Windows client computer. You can sign up for a free Azure trial subscription (a valid credit card is required for verification, but you will not be charged for Azure services). Note that the free trial is not available in all regions.

10 Official Microsoft Certificates

Microsoft
Microsoft Certificate of Completion

Original Microsoft Certificate of Completion


Get your Original Microsoft Certificate of Completion that certifies the successful passing of a Microsoft Massive Open Online Course (MOOC).

Optional: Coaching Services

Microsoft 1:1 Coaching

Microsoft 1:1 Coaching

MS-COACH
USD 199.00
Don’t waste time searching for answers when being stuck with a problem. Schedule an individual virtual meeting with a dedicated subject-matter expert and explore more difficult topics interactively using screen sharing capabilities.

Microsoft Q&A Support

Microsoft Q&A Support

MS-QA-SUPPORT
USD 99.00
Ask questions, get opinions and explore ideas with a dedicated subject-matter expert..

* Required Fields

Microsoft Professional Program (MPP): Data Science

Program Microsoft MPP-DS

USD 890.00