Overview

Take your Excel data science skills to an advanced level. As data strategies become more pervasive, Excel will become even more popular for non-data scientists doing more work, more often, with data. This learning path extends the Master Excel for Data Science learning path, into VBA coding, data viz, and advanced interfacing between Excel and R.

Master Excel's powerful VBA coding functions for advanced modeling and analytics.
Build your expertise in Excel's increasingly powerful data mapping functions.
Master the use of Excel with R, the language and data science environment for statistical computing.

Syllabus

Courses under this program:
Course 1: Excel VBA: Managing Files and Data
-Learn how to automate complex tasks and get more meaningful insights from data in Excel using Visual Basic for Applications (VBA) code.

Course 2: Excel VBA: Process Modeling
-Learn how to use Excel and VBA for business process modeling. Find out how to create and run simulations for customer flow, queuing, and manufacturing.

Course 3: Excel: Working Together with Power Query and Power Pivot
-Learn how to combine Power Query and Power Pivot, two robust features of Microsoft Excel, to analyze data.

Course 4: Using Python with Excel
-Take your Excel skills further by using Python. Discover how to inspect, filter, clean, convert, and visualize data with Excel and Python libraries like pandas and openpyxl.

Course 5: From Excel to SQL
-As big data gets bigger, you may need to pull insights directly from SQL. Learn how to apply your knowledge of Excel to gain new skills at capturing data from SQL.

Course 6: Machine Learning with Logistic Regression in Excel, R, and Power BI
-Learn how to perform logistic regression using R and Excel and use Power BI to integrate these methods into a scalable, sharable model.

Course 7: Business Analytics: Multiple Comparisons in R and Excel
-Learn how to run multiple comparison tests in Excel and R to pinpoint mean differences in multiple groups of data.

Course 8: Business Analytics: Understanding and Using Confidence Intervals
-Learn basic techniques for constructing and interpreting confidence intervals, as well as what they can tell you about your personal and business decisions.

Courses

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51 minutes
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Learn how to combine Power Query and Power Pivot, two robust features of Microsoft Excel, to analyze data.
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Learn how to run multiple comparison tests in Excel and R to pinpoint mean differences in multiple groups of data.
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57 minutes
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Take your Microsoft Excel skills to the next level using Python, one of the world’s most popular object-oriented programming languages.
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1-2 hours
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Learn basic techniques for constructing and interpreting confidence intervals, as well as what they can tell you about your personal and business decisions.
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3-4 hours
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Learn how to automate complex tasks and get more meaningful insights from data in Excel using Visual Basic for Applications (VBA) code.
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2-3 hours
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Learn how to use Excel and VBA for business process modeling. Find out how to create and run simulations for customer flow, queuing, and manufacturing.
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1 hour 25 minutes
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As big data gets bigger, you may need to pull insights directly from SQL. Learn how to apply your knowledge of Excel to gain new skills at capturing data from SQL.
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2-3 hours
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Learn how to perform logistic regression using R and Excel and use Power BI to integrate these methods into a scalable, sharable model.