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

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Master the art of creating compelling data visualizations: learn how to create professional charts in Python, R, Tableau, and Excel

10 hours of content 29930 students

Start for Free

What you get:

10 hours of content
6 Interactive exercises
157 Downloadable resources
World-class instructor
Closed captions
Q&A support
Future course updates
Course exam
Certificate of achievement

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

A course by Elitsa Kaloyanova

Start for Free

What you get:

10 hours of content
6 Interactive exercises
157 Downloadable resources
World-class instructor
Closed captions
Q&A support
Future course updates
Course exam
Certificate of achievement

Start for Free

What you get:

10 hours of content
6 Interactive exercises
157 Downloadable resources
World-class instructor
Closed captions
Q&A support
Future course updates
Course exam
Certificate of achievement

What You Learn

Gain a solid understanding of data visualization fundamentals and theory
Learn how to create professional and aesthetically pleasing charts in Python, R, Tableau, and Excel
Understand how to select the right type of chart depending on the problem at hand
Develop expertise in interpreting data and communicating your findings through data visualizations
Boost your resume and career prospects with highly sought-after data visualization skills
Enhance your project portfolio with compelling data visualizations and impress recruiters and hiring managers

Top Choice of Leading Companies Worldwide

Industry leaders and professionals globally rely on this top-rated course to enhance their skills.

Course Description

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.

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1.1 What does the Course Cover

5 min

1.2 Why Learn Data Visualization

6 min

1.4 How to Choose the Right Visualization - Popular Approaches and Frameworks

7 min

1.6 Color Theory and Colors

9 min

2.1 Setting Up The Environments - Do Not Skip, Please!

1 min

2.2 Tableau - Downloading Tableau

2 min

Curriculum

1. Introduction

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
5 min
Why Learn Data Visualization
6 min
How to Choose the Right Visualization - Popular Approaches and Frameworks
7 min
Color Theory and Colors
9 min
2. Setting Up the Environments

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!
1 min
Tableau - Downloading Tableau
2 min
Python - Why Python and Why Jupyter
5 min
Python - Installing Anaconda
4 min
Python - Jupyter Dashboard - Part 1
3 min
Python - Jupyter Dashboard - Part 2
6 min
Python - Installing the Seaborn Package
1 min
R - Installing R and RStudio
3 min
R - Quick Guide to RStudio
8 min
R - Changing the Appearance in Rstudio
2 min
R - Installing Packages and Using Libraries
4 min
3. Bar Chart

7 Lessons 52 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
2 min
Bar Chart - Excel - How to Create a Bar Chart
11 min
Bar Chart - Tableau - How to Create a Bar Chart
10 min
Bar Chart - Python - How to Create a Bar Chart
11 min
Bar Chart - R - How to Create a Bar Chart
14 min
Bar Chart - Interpretation & What Makes a Good Bar Chart
3 min
Bar Chart Homework Read now
1 min
4. 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
4 min
Pie Chart - Excel - How to Create a Pie Chart
5 min
Pie Chart - Tableau - How to Create a Pie Chart
5 min
Pie Chart - Python - How to Create a Pie Chart
7 min
Pie Chart - R - How to Create a Pie Chart
10 min
Pie Chart - Interpretation
2 min
Pie Chart - Why You Should Never Use a Pie Chart
8 min
5. Stacked Area Chart

8 Lessons 43 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
3 min
Stacked Area Chart - Excel - How to Create a Stacked Area Chart
8 min
Stacked Area Chart - Tableau - How to Create a Stacked Area Chart
6 min
Stacked Area Chart - Python - How to Create a Stacked Area Chart
8 min
Stacked Area Chart - R - How to Create a Stacked Area Chart
10 min
Stacked Area Chart - Interpretation
3 min
Stacked Area Chart - What Makes a Good Stacked Area Chart
4 min
Stacked Area Chart Homework Read now
1 min
6. Line Chart

8 Lessons 43 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
2 min
Line Chart - Excel - How to Create a Line Chart
4 min
Line Chart - Tableau - How to Create a Line Chart
8 min
Line Chart - Python - How to Create a Line Chart
8 min
Line Chart - R - How to Create a Line Chart
10 min
Line Chart - Interpretation
3 min
Line Chart - What Makes a Good Line Chart
7 min
Line Chart Homework Read now
1 min
7. Histogram

9 Lessons 44 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
5 min
Histogram - Excel - How to Create a Histogram Chart
6 min
Histogram - Tableau - How to Create a Histogram
8 min
Histogram - Python - How to Create a Histogram
6 min
Histogram - R - How to Create a Histogram
6 min
Histogram - Interpretation
2 min
Histogram - How to Choose the Right Number of Bins
5 min
Histogram - What Makes a Good Histogram
5 min
Histogram Homework Read now
1 min
8. Scatter Plot

8 Lessons 38 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
2 min
Scatter Plot - Excel - How to Create a Scatter Plot
5 min
Scatter Plot - Tableau - How to Create a Scatter Plot
7 min
Scatter Plot - Python - How to Create a Scatter Plot
9 min
Scatter Plot - R - How to Create a Scatter Plot
8 min
Scatter Plot - Interpretation
3 min
Scatter Plot - What Makes a Good Scatter Plot
3 min
Scatter Plot Homework Read now
1 min
9. Combo Plots Part 1 - Regression Plot

8 Lessons 35 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
3 min
Regression Plot - Excel - How to Create a Regression Plot
6 min
Regression Plot - Tableau - How to Create a Regression Plot
5 min
Regression Plot - Python - How to Create a Regression Plot
7 min
Regression Plot - R - How to Create a Regression Plot
5 min
Regression Plot - Interpretation
5 min
Regression Plot - What Makes a Good Regression Plot
3 min
Regression Plot Homework Read now
1 min
10. Combo Plots Part 2 - Bar and Line Chart

8 Lessons 37 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
3 min
Bar and Line Chart - Excel - How to Create a Bar and Line Chart
8 min
Bar and Line Chart - Tableau - How to Create a Bar and Line Chart
5 min
Bar and Line Chart - Python - How to Create a Bar and Line Chart
8 min
Bar and Line Chart - R - How to Create a Bar and Line Chart
5 min
Bar and Line Chart - Interpretation
3 min
Bar and Line Chart - What Makes a Good Combination Chart
4 min
Bar and Line Chart Homework Read now
1 min
11. Advanced Topics - Dashboard in Excel

20 Lessons 88 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
4 min
Dashboard in Excel- Getting to Know the Data Set
4 min
Dashboard in Excel- Creating the Design for our Dashboard
7 min
Dashboard in Excel– Creating a Drop-down List and Radio Buttons in Excel
5 min
Dashboard in Excel – Using the Developer Tab and Creating Radio Buttons in Excel
3 min
Dashboard in Excel – Including Additional Features to the Data Set
6 min
Dashboard in Excel - Pivot Tables
3 min
Dashboard in Excel - Tables – Creating LTM and YTD References in Excel
6 min
Dashboard in Excel - Tables – Creating Month, Year and Selected Dates Fields in Excel
4 min
Dashboard in Excel – Tables -Calculating Net Sales
7 min
Dashboard in Excel – Tables -Calculating GP% and Distribution Costs
3 min
Dashboard in Excel - Tables – Volume by Size
5 min
Dashboard in Excel – Charts - Bar and Line Combination Chart
7 min
Dashboard in Excel Homework Read now
1 min
Dashboard in Excel - Charts – Clustered Bar Chart I
5 min
Dashboard in Excel - Charts – Clustered Bar Chart II
4 min
Dashboard in Excel – Adding KPIs and a Slicer to the Dashboard
3 min
Dashboard in Excel - Customizing the Appearance of the Dashboard
2 min
Dashboard in Excel - Customizing the Appearance of the Slicer
4 min
Dashboard in Excel - Interpretation
5 min
12. 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
3 min
Dashboard in Tableau - Loading the Data and Preparing the Sheets for the Tableau Dashboard
3 min
Dashboard in Tableau - Bar and Line Combination Chart
5 min
Dashboard in Tableau - Horizontal Bars Chart I
2 min
Dashboard in Tableau - Horizontal Bars Chart II
2 min
Dashboard in Tableau - Adding KPIs to the Tableau Dashboard
3 min
Dashboard in Tableau - Creating the Tableau Dashboard and Adding a Brand Filter
4 min
Dashboard in Tableau - Incorporating a Date Filter into the Dashboard
6 min
Dashboard in Tableau - Styling the Tableau Dashboard
8 min
Dashboard in Tableau - Interpretation
4 min

Topics

Data VisualizationDashboardPythonTableauRExcelTheory

Tools & Technologies

Course Requirements

Basic prior experience with Python, R, Tableau, or Excel is required. You can complete the course by focusing on just one of these technologies.

Who Should Take This Course?

Level of difficulty: Beginner

Aspiring data analysts and data scientists
Data analysts and data scientists who have work experience and are eager to improve their data visualization abilities
Graduate students who want to learn the building blocks of professional data visualization
Everyone who wants to learn how to create good-looking data visualizations

Exams and Certification

A 365 Data Science Course Certificate is an excellent addition to your LinkedIn profile—demonstrating your expertise and willingness to go the extra mile to accomplish your goals.

Meet Your Instructor

Elitsa Kaloyanova

Senior Data Scientist at

7 Courses

3286 Reviews

53243 Students

Elitsa Kaloyanova is a Computational Biologist, with significant expertise in the fields of algorithms, data structures, phylogenetics, and population genetics. She has a solid academic background in Bioinformatics with publications on constructing Phylogenetic Networks and Trees. In 2021, she led 365’s effort to create practice exams and course exams for each course included in the program. Elitsa was able to successfully coordinate with several types of stakeholders and performed superior Quality Assurance.