The Complete Data Visualization Course with Python, R, Tableau, and Excel

with Elitsa Kaloyanova

4.8/5

(691)

Teaching you how to master the art of creating and styling charts to achieve professional results. The course is based in four different technologies – Excel, Tableau, Python, and R – to complete your data visualization skillset.

9 hours 100 lessons

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Course Overview

The Data Visualization course is designed for everyone looking to deepen their understanding of creating meaningful and compelling visualizations. Whether you’re coming from a business or data science-related field, knowledge in data visualization is both important and advantageous. That’s precisely why this course is centered not in just one, but four different environments: Excel, Tableau, Python, and R. Each section is dedicated to a specific type of chart – bar charts, pie charts, area charts, line charts and many more. In addition, there are lectures that specifically explore what to avoid when creating a certain graphic. You can stick with your preferred environment and follow each section. Or you could master all four environments and add indispensable skills to your data visualization toolset.

100 High Quality Lessons

16 Practical Tasks

9 Hours of Video

Certificate of Achievement

Topics covered

Dashboarddata visualizationExcelHistogramLine and Bar ChartPythonRRegression ScatterTableau

What You'll Learn

This course features four technologies through which you can learn data visualization – Excel, Tableau, Python and R. Even if you’re a complete beginner, this course will build your data viz skillset, starting with basics like the bar chart, and building up towards combination charts and dashboards.

Create basic and advanced charts

Interpret data

Select the right type of chart

Learn what not to do in data viz

Create stunning visualization

Label and style graphs professionally

Curriculum

Introduction Free

4 Lessons 27 Min

In this section, you will learn about the importance of data visualization, as well as some theoretical foundations for creating charts. We introduce popular frameworks for choosing an appropriate visualization for your data, discuss color theory, and show different approaches to selecting the colors for your graphic.
What does the Course Cover Free Why Learn Data Visualization Free How to Choose the Right Visualization - Popular Approaches and Frameworks Free Color Theory and Colors Free
Setting Up the Environments Free

11 Lessons 39 Min

Here, we set up different environments for the course. First, we will guide you through the installation process for Tableau. Then, you will get familiar with the step-by-step process of installing Anaconda and Jupyter and an introductory tour of the Jupyter Dashboard for Python. Finally, you’ll learn how to install R and R studio, explore the latter’s main features and learn how to customize its appearance.
Setting Up The Environments - Do Not Skip, Please! Free Tableau - Downloading Tableau Free Python - Why Python and Why Jupyter Free Python - Installing Anaconda Free Python - Jupyter Dashboard - Part 1 Free Python - Jupyter Dashboard - Part 2 Free Python - Installing the Seaborn Package Free R - Installing R and RStudio Free R - Quick Guide to RStudio Free R - Changing the Appearance in Rstudio Free R - Installing Packages and Using Libraries Free
Bar Chart Free

6 Lessons 51 Min

We dive straight into visualization with the bar chart! We will take a look at a data set for second-hand car advertisements and use it to create a bar chart in Excel, Tableau, Python, and R. We’ll also lift the curtain on the key elements to making an outstanding bar chart.
Bar Chart - Introduction - General Theory and Dataset Free Bar Chart - Excel - How to Create a Bar Chart Free Bar Chart - Tableau - How to Create a Bar Chart Free Bar Chart - Python - How to Create a Bar Chart Free Bar Chart - R - How to Create a Bar Chart Free Bar Chart - Interpretation & What Makes a Good Bar Chart Free
Pie Chart

7 Lessons 41 Min

In this section, we explore pie charts, which, despite criticism, are among the most popular visualizations. You will learn how to create a pie chart of engine fuel types in Excel, Tableau, Python, and R, and discover what to avoid when making a pie chart.
Pie Chart - Introduction - General Theory and Dataset Pie Chart - Excel - How to Create a Pie Chart Pie Chart - Tableau - How to Create a Pie Chart Pie Chart - Python - How to Create a Pie Chart Pie Chart - R - How to Create a Pie Chart Pie Chart - Interpretation Pie Chart - Why You Should Never Use a Pie Chart
Stacked Area Chart

7 Lessons 42 Min

Here, you will create your own stacked area chart. Once again, our data follows the automobile theme with one additional element - time series, as the chart follows the popularity of different engine fuel types across the years.
Stacked Area Chart - Introduction - General Theory and Dataset Stacked Area Chart - Excel - How to Create a Stacked Area Chart Stacked Area Chart - Tableau - How to Create a Stacked Area Chart Stacked Area Chart - Python - How to Create a Stacked Area Chart Stacked Area Chart - R - How to Create a Stacked Area Chart Stacked Area Chart - Interpretation Stacked Area Chart - What Makes a Good Stacked Area Chart
Line Chart

7 Lessons 42 Min

In this section, we continue discussing time series data. We will turn our attention to the financial world and explore the stock market returns for two major indices: S&P 500 and FTSE 100. In conclusion, you’ll find out the advantages of using a line chart and what you should be wary of when creating one.
Line Chart - Introduction - General Theory and Dataset Line Chart - Excel - How to Create a Line Chart Line Chart - Tableau - How to Create a Line Chart Line Chart - Python - How to Create a Line Chart Line Chart - R - How to Create a Line Chart Line Chart - Interpretation Line Chart - What Makes a Good Line Chart
Histogram

8 Lessons 43 Min

This section centers around the histogram – an integral part of the data analysis process. We will create a histogram of the price of California's real estate. Here, we devote an extra lecture and explore how to choose the right number of bins for your histogram.
Histogram - Introduction - General Theory and Dataset Histogram - Excel - How to Create a Histogram Chart Histogram - Tableau - How to Create a Histogram Histogram - Python - How to Create a Histogram Histogram - R - How to Create a Histogram Histogram - Interpretation Histogram - How to Choose the Right Number of Bins Histogram - What Makes a Good Histogram
Scatter Plot

7 Lessons 37 Min

In this section, you will learn how to create a scatter plot of real estate data. First, we’ll observe the relationship between California's real estate pricing and the area of properties. Then, you’ll make a scatter plot in Excel, Tableau Python, and R and finish the section with valuable tips on what makes a good scatter plot.
Scatter Plot - Introduction - General Theory and Dataset Scatter Plot - Excel - How to Create a Scatter Plot Scatter Plot - Tableau - How to Create a Scatter Plot Scatter Plot - Python - How to Create a Scatter Plot Scatter Plot - R - How to Create a Scatter Plot Scatter Plot - Interpretation Scatter Plot - What Makes a Good Scatter Plot
Combo Plots Part 1 - Regression Plot

7 Lessons 34 Min

We’ll explore a combination chart of a scatter and a regression line by using marketing data and a regression line to quantify the relationship between a company’s advertising budget and its sales. You will learn how to create a regression scatter in Excel, Tableau, Python, and R, and discover different types of relationships between features in data. the model residuals can be beneficial in model selection.
Regression Plot - Introduction - General Theory and Dataset Regression Plot - Excel - How to Create a Regression Plot Regression Plot - Tableau - How to Create a Regression Plot Regression Plot - Python - How to Create a Regression Plot Regression Plot - R - How to Create a Regression Plot Regression Plot - Interpretation Regression Plot - What Makes a Good Regression Plot
Combo Plots Part 2 - Bar and Line Chart

7 Lessons 36 Min

In this section, we’ll create a combination chart with a dual-axis. Our data centers around data science and Python programmers and comes from the annual KD Nuggets survey. We’ll get a chance to delve deeper into each of the four software, as we learn how to create combination charts.
Bar and Line Chart - Introduction - General Theory and Dataset Bar and Line Chart - Excel - How to Create a Bar and Line Chart Bar and Line Chart - Tableau - How to Create a Bar and Line Chart Bar and Line Chart - Python - How to Create a Bar and Line Chart Bar and Line Chart - R - How to Create a Bar and Line Chart Bar and Line Chart - Interpretation Bar and Line Chart - What Makes a Good Combination Chart
Advanced Topics - Dashboard in Excel

19 Lessons 87 Min

We’ll work on real-life data and create a dashboard in Excel. Our dashboard will center on creating a report for a large company operating in the FMCG sector. The star of the report will be the two custom filters, which will slice the data based on the period we’re interested in.
Dashboard in Excel - Introduction Dashboard in Excel- Getting to Know the Data Set Dashboard in Excel- Creating the Design for our Dashboard Dashboard in Excel– Creating a Drop-down List and Radio Buttons in Excel Dashboard in Excel – Using the Developer Tab and Creating Radio Buttons in Excel Dashboard in Excel – Including Additional Features to the Data Set Dashboard in Excel - Pivot Tables Dashboard in Excel - Tables – Creating LTM and YTD References in Excel Dashboard in Excel - Tables – Creating Month, Year and Selected Dates Fields in Excel Dashboard in Excel – Tables -Calculating Net Sales Dashboard in Excel – Tables -Calculating GP% and Distribution Costs Dashboard in Excel - Tables – Volume by Size Dashboard in Excel – Charts - Bar and Line Combination Chart Dashboard in Excel - Charts – Clustered Bar Chart I Dashboard in Excel - Charts – Clustered Bar Chart II Dashboard in Excel – Adding KPIs and a Slicer to the Dashboard Dashboard in Excel - Customizing the Appearance of the Dashboard Dashboard in Excel - Customizing the Appearance of the Slicer Dashboard in Excel - Interpretation
Advanced Topics - Dashboard in Tableau

10 Lessons 40 Min

In this section, we’ll rely on Tableau’s capabilities to create a dynamic report for a company based on real-world data. Our dashboard will include a custom time filter, as well as a brand filter and we’ll even devise our very own custom design template for the dashboard.
Dashboard in Tableau - Introduction Dashboard in Tableau - Loading the Data and Preparing the Sheets for the Tableau Dashboard Dashboard in Tableau - Bar and Line Combination Chart Dashboard in Tableau - Horizontal Bars Chart I Dashboard in Tableau - Horizontal Bars Chart II Dashboard in Tableau - Adding KPIs to the Tableau Dashboard Dashboard in Tableau - Creating the Tableau Dashboard and Adding a Brand Filter Dashboard in Tableau - Incorporating a Date Filter into the Dashboard Dashboard in Tableau - Styling the Tableau Dashboard Dashboard in Tableau - Interpretation

Student feedback

4.8/5

691 ratings

5 stars

603 (87%)

4 stars

75 (11%)

3 stars

9 (1%)

2 stars

2 (0%)

1 star

2 (0%)

Crystal Monnens

15.02.2023

Aside from the last two sections on dashboards, I was really disappointed. I had so many issues trying to get RStudio and Jupyter Notebook to upload files. I used the correct address on my computer and still had issues. After several attempts I abandoned the ideal all together. This course was not user friendly as I was only able to build in two of the four environments.

Carlos Luis Yanez Lopez

14.08.2022

It's amazing the way the information it is showed easyly. There are a few details that may have done better, for instance the combo chart in tableu shows the the percetenges in a wrong way, if we compare it with the theorical manner when you have to show the percetenges up to 100%. But i still understand that some things are beyond the scope of this course.

Hashem Omran

27.10.2022

I suggest taking this course after completing all courses to use it an implementing everything you learned. You can learn the basics and the story behind each chart in different environment as data scientist or Business analyst

Alexander Duncan Reynolds

20.11.2022

I'm taking a leap of faith and daring to move out of my comfort zone with this course, but I have to admit I'm finding the presentation very informative. Awesome.