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Introduction to Tableau

This course offers an accelerated intensive learning experience with Tableau

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Video Hours

Course Introduction

Course Overview

This course offers an accelerated intensive learning experience with Tableau. Without prior experience, students will learn to work with multiple data sources, create compelling visualizations, and roll out their data science products for continuous, scalable outputs to key stakeholders. By building insight and weaving narrative, students will be empowered to harness data in a striking way that provides value to organizations large and small. This course robustly covers 90-95% of what’s needed for the qualified associate Tableau Certificate.


Without prior experience in data visualization or science, students will learn:

  • Principles of visualization & dashboard creation
  • Leverage Tableau’s features for combining and manipulating large & various sources of data
  • Gain a deeper sense of comfort & practice by ‘learning through doing’ in frequent visualization labs
  • Complete a capstone visualization project that sparks their imagination.

Who Is This Course For?

The course is well-suited for:

  • Analysts/managers who frequently review data & share findings within an organization
  • Consultants & external advisors who frame performance indicators & metrics for key decision makers
  • Entrepreneurs growing companies where data is a central asset or offering
  • Data scientists interested in utilizing Tableau’s platform & R integration to pipeline compelling visualizations that harness advanced statistical learning algorithms


Know how to use Mac, Windows.

Familiarity with relational databases will be nice but not required:

  • Gain a greater appreciation for the logic underlying Tableau’s features
  • Utilize their capstone project to visualize ‘big data’ by accessing a variety of server- or cloud-based sources


Wes Aull

Wes Aull, CPA works as a data scientist/portfolio manager at Economic(a). His research interests include data visualization, time series & harmonic analysis, Bayesian & directional statistics, stochastic processes, and optimization problems. He earned his M.B.A. from Columbia Business School, Master’s of Professional Accounting from University of Texas-Austin, and B.S. Mathematical Economics from University of Kentucky.


Tableau Part I
Tableau WorkBook 1 Connecting to Data
Tableau Part II

Tableau WorkBook 2 Joining Data
Tableau Part III

Tableau WorkBook 3 Organizing Data
Tableau Part IV

Tableau WorkBook 4 Sorting, Filtering, & Formatting Your Data
Tableau Part V

Tableau WorkBook 5 Reference Line
Tableau Part VI

Tableau Part VII

Tableau WorkBook 7 Multiple Measures in View
Tableau Part VIII

WorkBook 8 Calculated Field
Tableau Part IX

Tableau WorkBook 9 Highlight Table
Tableau Part X

Tableau Part XI

Tableau WorkBook 11-1 Showing Distribution in Data
Tableau WorkBook 11-2 Showing Relationships in Data
Tableau Part XII

Tableau WorkBook 12 Unsupervised & Supervised Machine Learning
Tableau Part XIII

Tableau WorkBook 13-1 Visualizing Composition - Dynamic Breakdowns of the Whole (Tree Map)
Tableau WorkBook 13-2 Visualizing Composition - Dynamic Breakdowns of the Whole (Doughnut Plot)
Tableau Part XIV

Tableau WorkBook 14 Geographic Visualizations
Tableau Part XV

Tableau WorkBook 15 Making Your Views Available – Dashboards


By the end of the course, you will be able to:

  • Understand which visualizations best express a particular insight
  • Construct advanced visualizations such as tree maps, sunburst diagrams, and geo-mapped data
  • Wisely offer insight through visual dashboards constructed using principles such as the golden ratio
  • Pipeline visualizations that model large-scale data in a continuous fashion

Start Learning Today

Introduction to Tableau


This course offers an accelerated intensive learning experience with Tableau

Get Started Now
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