Data Science Orientation - Updated Course-Learn what it takes to become a data scientist.

Learn what it takes to become a data scientist.

Data Science Orientation - Updated Course

Learn what it takes to become a data scientist.

A brief summary

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.

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Placement services also available for candidates who have bought a certificate and passed the exam

Instructor:

Graeme Malcolm, Senior Content Developer, Microsoft Learning Experiences, along with Liberty J. Munson, Principal Psychometrician and Quality Lead, Microsoft

What you will learn

  • How the Microsoft Data Science curriculum works
  • How to navigate the curriculum and plan your course schedule
  • Basic data exploration and visualization techniques in Microsoft Excel
  • Foundational statistics that can be used to analyze data


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The Data Science Curriculum

Guide to the Data Science Curriculum, Courses in the Curriculum, Curriculum Resources, Meet The Data Scientists, Introducing the Data Scientists, What Do You Enjoy About Being a Data Scientist?, What Does a Data Scientist Do?, What Kind of Person Succeeds as a Data Scientist?, What Skills Does a Data Scientist Need?, What Advice Would You Give an Aspiring Data Scientist?

Data Science Fundamentals

Getting Started with Data, Introduction to Data, Demo: Working with Data in Excel, Exploring Data, Demo: Exploring Data in Excel, Introduction to Data Visualization, Demo: Visualizing Data in Excel, Slicing and Dicing Data, Demo: PivotTables and PivotCharts

Basic Introduction to Statistics

Basic Statistics, Getting Started with Statistics, Measures of Central Tendency, Measures of Variance, Demo: Descriptive Statistics in Excel, Correlation, Hypothesis Testing, T-Tests, Two-Sample T-Tests, Paired T-Tests, Analysis of Variance, Regression

Lab- Exploring Data with Excel

Lab- Exploring Data with Excel

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