PROGRAM WORKSHOPS

Take one workshop or complete all five and receive at 10% discount

• Mastering Formulas

  Formulas are the backbone of working in Excel. Most people, however, don’t know how to use these They may not know exactly what’s available to them. 

  In this session, we’ll teach the Excel formulas every Excel user should know so that they feel comfortable working in the Excel environment. We’ll review how they can be prepared quickly to drive key decisions, and we’ll look at Excel’s new functions including LET(), XLOOKUP(), dynamic arrays, and more. We’ll also demonstrate how named ranges and Excel tables can make readable, transparent formulas. 

  By the end of the session you will understand:

  • When to use which function in a formula and why
  • How formulas can seamlessly drive how you present data
  • How to use formulas to create quick summaries of your data
  • How to stay organized with lots of formulas

  And you will be able to: 

  • Comfortably use formulas like SUMIFS and XLOOKUP
  • Design and audit complex, nested formulas
  • Looking up data in an instant
• Data Wrangling in Excel with Power Query

  Power Query is a Microsoft extract, transform, and load (ETL) technology that enables users to access data from structured and unstructured sources, reshape it, and load it into Excel workbooks. 

  Analysts, researchers, and project managers want to build repeatable data cleaning processes on large datasets. Rather than write complex Excel formulas or programs in Visual Basic for Applications (VBA), these users can conduct their work in Power Query with no coding required. 

  The focus of this session will be using Power Query to transform tabular data sources into tables that are ready for data analysis. By the end of the course, users will be able to pivot, filter, and merge data so that it’s ready for analysis in Excel. 

  By the end of the session you will understand:

  • How Power Query serves as an ETL tool for Microsoft Excel 
  • What makes data “tidy,” and why tidiness is desirable for data analysis 
  • The role of the M programming language in Power Query 

  And you will be able to: 

  • • Load data from Excel worksheets, workbooks and CSV files 
    • Perform common data wrangling tasks such as sorting, filtering, and aggregation 
    • Combine data from multiple sources using joins and appends 
• Mastering Pivot Tables, Dashboards + Reports

  Pivot Tables are one of the most important features in Excel. They let you create summaries and reports instantly. Excel’s new data model takes this a step further by letting you connect Pivot Tables to create a mini database.
  This course will start with Pivot Table basics. We’ll go through a fool-proof way of thinking about Pivot Tables that will allow you to build summaries across different column fields from any dataset.

  Once we know how to work with Pivot Tables we’ll about how to connect them. Ultimately, we’ll use these connections to create an interactive Dashboard. By the end of the webinar, attendees will walk away with a fully functional dashboard driven by Pivot Tables.

  By the end of the session you will understand:

  • Pivot Tables and Pivot Charts
  • Excel’s Data Model
  • Pivot Table Dashboards

  And you will be able to:

  • Use Pivot Tables to generate summary data, reports, and dashboards in seconds
  • Create connections across data with the Excel Data Model
  • Visualize data across multiple tabs
• Business Statistics in Excel

  How do you know when a relationship in your data actually means something, and when it’s a mathematical mirage? In this session, we’ll cover the basics of statistical analysis for business impact.  

  Attendees will use Excel to walk through fundamental statistics concepts, using features such as PivotTables and the Data Analysis ToolPak. They will then learn how to organize, present and draw valid conclusions from their data.  

  By the end of the session you will understand:

  • What variables are, and how to explore them given their type 
  • How the central limit theorem provides the “missing link” between descriptive and inferential statistics 
  • The roles statistics and visualizations each play in effective quantitative analysis 

  And you will be able to:

  • • Explore a dataset for potential research questions, check assumptions, and build hypotheses 
    • Test formally whether the value of one group is greater than another, on average, given their respective samples 
    • Make compelling business recommendations using inferential statistics
• Python Analytics for Excel Users

  A ubiquitous tool in the business world, Excel has its place for ad hoc data analysis and reporting. But spreadsheets have their limitations, where Python can prove a helpful addition to the analyst toolkit. Most Excel users are well-acquainted with common data processes like filtering, merging and summarizing data.  

  This introductory course is meant to showcase the fundamental principles that Excel users should know about Python. Learners will become familiar with basic programming along with the possibilities for integrating both Excel and Python to build integrated analytics products. 

  By the end of the this live, hands-on online course, you will understand:

  • How Python can assist in augmenting and automating tasks typically done in Excel 
  • The role of objects and packages in Python programming 
  • How Python differs from Excel as open source software 

  And you will be able to:

  • • Identify, install, and load the most common packages for data analysis and visualization 
    • Read, open, and write Excel files from Python 
    • Compare and contrast the syntax basics of Python vs Excel