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LinkedIn Learning

Master Excel for Data Science

via LinkedIn Learning Path


As data strategies become pervasive in all business and institutional sectors, Excel will become even more popular as a bridge tool for non-data scientists doing more work, more often, with data. This learning path is the perfect entry point to the world of data-centric projects and skills.
  • Master statistics functions in Excel.
  • Learn the data analytics and modeling capabilities of Excel.
  • Explore how to work with R, a tool for advanced data work.


Courses under this program:
Course 1: Statistics Foundations: The Basics
-Learn to understand your data using basics of statistics, such as defining the middle, mean, and median of your data set; measuring the standard deviation; and finding outliers.

Course 2: Excel Statistics Essential Training: 1
-Learn statistics. Dr. Joseph Schmuller uses Microsoft Excel to teach the fundamentals of descriptive and inferential statistics.

Course 3: Learning Excel: Data Analysis
-Unlock the power of your organization's data. Learn how to perform data analysis in Microsoft Excel.

Course 4: Excel for Business Analysts
-This course shows business analysts how to use Excel to measure the health of an organization. Learn how to use Excel to gather, assess, and use business analytics information.

Course 5: Excel: Tracking Data Easily and Efficiently
-Learn how to build a super-charged Excel spreadsheet to easily track any kind of data -from sales activity and inventory levels to household spending.

Course 6: Excel: Filtering Data for Beginners
-Make the most of the filtering capabilities in Microsoft Excel. Learn how to use filters to zero in on exactly the data you need.

Course 7: Excel: Power Query for Beginners
-Get an intro to Power Query, a set of robust features in Microsoft Excel.

Course 8: Excel: Charts in Depth
-Explore how to add visual appeal to your spreadsheets and workbooks with this in-depth course on the powerful charting features of Microsoft Excel.


Taught by

Eddie Davila, Joseph Schmuller, Curtis Frye, Michael M., Oz du Soleil, Dave Ludwig and Dennis Taylor


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