10 Best Data Visualization Courses Reviewed

Pick up the skills necessary to design cool visualizations with the top online data visualization courses available today.

Our Pick: Data Visualization for Everyone (DataCamp)

Platform Rating

4.7 /5

DataCamp’s “Data Visualization for Everyone” is a short course that’ll teach you everything you need to know to get started with data visualization. While this course is beginner-oriented, DataCamp’s course catalog also contains plenty of advanced classes.

Course Instructor

Richie Cotton

Course Duration

4 Hours

Price

$25 p/m (Covers entire DataCamp library)

There is no such thing as information overload. There is only bad design.

— Edward Tufte

Today, it takes only one hour to create what was two decades ago a year’s worth of data. Unsurprisingly, the market for big data is growing exponentially, too. Indeed, it’s estimated that the demand for big data analytics will increase 4.5 times by 2025. Even amid continued COVID-19 uncertainty, big data analysis is the one thing that enterprises the world over are still investing money in. Why? Because data analytics can improve a business’s competitiveness and fast-forward innovation regardless of external circumstances. 

But big data on its own is useless. To make data work, it needs to be shared with relevant stakeholders in a format they can immediately understand. This is where data visualization comes in. One of the most important tools in a data analyst’s arsenal, data visualization can help you communicate important information in a way that’s universal, fast, and effective. 

However, you don’t necessarily have to be a data analyst or data scientist to take advantage of data visualization. Regardless of whether you work as a finance professional, marketer, or teacher, visualization tools can help you make your work more effective. For example, Florence Nightingale, a nurse best known for her work during the Crimean War, used data visualizations to help fight for better hospital conditions.

If you’d like to learn data visualization but don’t know where to start, consider enrolling in an online data visualization course. And nope, you don’t need to know how to program to make beautiful visuals from data.

What is the best course for learning data visualization?

Best Overall: Data Visualization for Everyone (DataCamp)

Best Overall: Data Visualization for Everyone (DataCamp)

Join the ranks of 12,000+ students in this DataCamp course and learn the basics of data visualization. No prior coding experience necessary!

If you want to learn data visualization but don’t know where to start, you should enroll in Data Visualization for Everyone. This superb DataCamp course will teach you everything you need to know to create your first data visualization in just four hours. Bonus points? There’s no coding involved.

This course is short, but it covers all the bases, including:

  • Choosing the right data visualization.
  • Visualizing the spread of a variable using histograms and box plots.
  • Assessing the relationship between two continuous and categorical variables via scatter plots, line plots, bar plots, and dot plots.
  • Adding color and shape to data visualizations to make them easier to understand.
  • Recognizing and avoiding common plot problems.

Even though this course features a full curriculum, you don’t have to worry about information overload. Split into bite-sized chunks of content (four chapters further divided into sub-chapters), the learning material is easy to understand, digest, and remember. 

Moreover, the course doesn’t just go over theory, either. While the program includes 14 short video lessons, the focus here is on hands-on experience. Indeed, students get to practice immediately everything they learn with more than 40 exercises. Even better, the exercises include real-world datasets like Los Angeles home prices and COVID-19 cases.

Data Visualization for Everyone is one of the best data visualization courses out there. It goes over the fundamentals of data visualization while also including plenty of practice exercises.

Best for Certification: Data Visualization with Tableau Certification (Coursera)

Best for Certification: Data Visualization with Tableau Certification (Coursera)

If your goal is to learn how to work with Tableau, UC Davis’ Data Visualization with Tableau Certification has you covered.

Designed by the University of California, Davis and available via Coursera, Data Visualization with Tableau Certification does precisely what it says: shows you how to use Tableau to generate powerful visualizations and dashboards.

What makes this data visualization training program stand out from similar courses on the market is that it dives deep into data visualization theory. In other words, with this course, students learn not only “how” to visualize data but also “why.” For example, one of the first lessons in this course looks at how the brain relates to visual design. 

That being said, there are plenty of practical elements in this course, too (not least the capstone project that involves creating a single-frame visualization or multi-frame data story for a fictional company). 

No prior experience is required to enroll in this specialization. However, students should be comfortable working with data sets. Most students complete this course in about six months by studying three hours a week. 

If you’re looking to learn Tableau, Data Visualization with Tableau is one of the best data visualization programs for you. While you can audit course material for free, you’ll need to enroll in this program to earn a data visualization certification.

Become a Data Visualization Specialist: Concepts (LinkedIn Learning)

Best for Beginners: Data Visualization (Udacity)

The best data visualization training program for budding business leaders and data professionals alike.

For this Data Visualization nanodegree, Udacity collaborated with Tableau and a group of industry professionals to teach you how to choose the right data visualization type, create and design data dashboards, and build and animate data stories.

This nanodegree was designed with two types of students in mind: data professionals and business leaders. If you already work in data science, this program will teach you how to share your findings with others more effectively. On the other hand, if you’re a business leader, this program will show you how to use data to tell a story, and ultimately, persuade others to take action in a specific direction.

Regardless of which category you fall into, you should be familiar with data analysis. In other words, you need to have a good understanding of descriptive statistics, measures of spread, and distributions. You should also know how to analyze data in spreadsheets. If you’re not quite at the required level yet, try Udacity’s Intro to Descriptive Statistics first.

Divided into four courses, this nanodegree takes about four months to complete, provided that you spend about 5 to 10 hours a week on it. However, because the program includes four expert-reviewed projects and career coaching, the exact timeframe may vary from student to student.

With plenty of interesting and educational pre-recorded video lessons, challenging real-world projects, and career resources, Udacity’s Data Visualization nanodegree has to be one of the best ways you can learn data visualization online.

Best Overall: 2020 Complete Python Bootcamp: From Zero to Hero In Python (Udemy)

Become a Data Visualization Specialist: Concepts (LinkedIn Learning)

Find out how to tell stories with data with this learning path from LinkedIn.

Become a Data Visualization Specialist: Concepts is a learning path on LinkedIn that explores both data storytelling and data visualization. Although the two concepts are intertwined, they’re not the same. 

Data visualization is the graphical representation of collected information. On the other hand, data storytelling involves taking complicated data analyses and turning them into stories that are easily understood by an audience. 

Taught by five instructors (including two CEOs that have founded their own companies), this data visualization training program is made up of just under 14 hours of content and seven courses:

  • Courses one and two teach students how to effectively tell a story with data and leverage tables, charts, and visuals accordingly. 
  • Course three explains how to build an infographic from scratch using Adobe Illustrator, Adobe Photoshop, Adobe InDesign, and Microsoft Excel. 
  • Course four demonstrates how to “turn information into artwork.” 
  • Course five runs through data visualization best practices and common pitfalls. 
  • Course six highlights the key challenges analysts face when communicating complex information and suggests ways to overcome them. 
  • Course seven goes over data visualization tips and tricks (for example, how to choose the right visualization).

Each course comprises short video lessons (typically under five minutes long) and exercises and includes quizzes and exams that test your knowledge.

Become a Data Visualization Specialist: Concepts is one of the best data visualization courses out there. One reason for that is that it’s broken down in such a way that makes it easy for students to fit it into their busy schedules. Another is that it comes with a data visualization certificate upon completion. We also love that this path has a second part: Become a Data Visualization Specialist: Tools — accessible to anyone with a LinkedIn Learning subscription.

Data Visualization in R (DataCamp)

Data Visualization in R (DataCamp)

Learn how to visualize data using R base graphics.

R is an awesome platform for data analysis. With it, you can create pretty much any type of graph you want. DataCamp’s Data Visualization in R will show you how to do just that.

However, even though Data Visualization with R is one of the best data visualization programs with R, it’s not meant for R beginners. Rather, students are expected to be familiar with this programming language already. If you’re not but would still like to learn how to build visualizations and present data with R, check out our roundup of the best R courses.

So, what will you learn in this five “chapter” (or 15 videos and 60 exercises) program? Although R supports a number of different graphics systems, this course zeroes in on base graphics, otherwise known as traditional graphics. 

You start with an overview of base graphics before moving on to different plot types (like histograms and scatter plots). The course ends with examples and hands-on exercises in plot customization (including how to modify point shapes and sizes, add explanatory text, and use color effectively). 

If you have experience with R, it makes sense to learn how to create visualizations using this programming language. One of the best online data visualization courses for R, DataCamp’s Data Visualization in R will give you the rundown on how to use the long-established, built-in facilities in R, known as base graphics.

Data Visualization in Spreadsheets (DataCamp)

Data Visualization in Spreadsheets (DataCamp)

Another DataCamp course, this one teaches you how to visualize data with Google Sheets.

Raina Howley, a Microsoft Excel consultant, lecturer, and author, is the instructor of DataCamp’s Data Visualization in Spreadsheets. Throughout the program, she teaches you how to tell compelling stories with your data using Google Sheets.

To be more specific, if you enroll in this course, you’ll learn how to prepare your data, target certain data using Google Sheets functions like Validation and VLookup, and create standard and advanced charts. You’ll also design a dashboard, among other things. Pretty cool, right?

In total, the program takes about four hours to complete, which is standard for a DataCamp course. However, students should have intermediate knowledge of spreadsheets. If you don’t, you can always take DataCamp’s Intermediate Spreadsheets beforehand.

Although Google Sheets is not as popular as Excel, it nonetheless has a broad user base. If you use this free Excel alternative, you may want to know how to use its full capability to create beautiful charts and graphs — and this is where DataCamp’s Data Visualization in Spreadsheets will come in handy. With an expert instructor and plenty of practice questions, you’ll be making your first data visualization in Google Sheets in no time.

Data Visualization with Python (Coursera)

Data Visualization with Python (Coursera)

Master Python’s data visualization libraries with an industry behemoth.

Offered by IBM on Coursera, Data Visualization with Python promises to show you how to take seemingly meaningless data and, using Python, present it in a way that makes sense to people.

This data visualization training program covers several data visualization libraries in Python, most notably matplotlib. However, the program also takes a look at Seaborn, a visualization library based on matplotlib that’s useful for generating regression plots, and Folium, a Python library used for visualizing geospatial data. 

At the end of the three-week course, students have to complete a peer-graded assignment. Because the assignment has questions that are not part of the program, it’s quite challenging but a good way to prepare for real-world projects. 

This course is intended for intermediate users with some knowledge of Python. Completing this course also counts towards a few other Coursera Specializations, including IBM Data Analyst Professional Certificate, IBM Data Science Professional Certificate, and Applied Data Science Specialization. In total, the course takes about 18 hours to finish. 

Those with experience in Python will love Coursera’s Data Visualization with Python. With this course, you can learn the best techniques to analyze and visualize data with Python programming language.

Data Visualization and Communication with Tableau (Coursera)

Data Visualization and Communication with Tableau (Coursera)

Duke University’s Data Visualization and Communication with Tableau is equally as demanding as it is enjoyable.

Data Visualization and Communication with Tableau by Duke University will teach you both how to use Tableau and how to research and present data effectively.

Course material consists of video lessons, readings, interviews from people in the industry, quizzes, and assignments that feature real-world data. While the course takes about 25 hours (or 5 weeks) to complete, there’s a ton of great information here. As such, to truly soak it all in, you may want to take your time — and even repeat certain sections. 

You don’t need to know how to use Tableau to get started with this course. However, prior experience with the interactive data visualization software will make it easier to get to grips with the concepts and ideas explored in this course. 

If you’re only interested in learning how to use Tableau, this course isn’t for you. However, if you want to learn Tableau while also sharpening your analytical and communication skills, you’re in for a treat.

Data Visualization with Advanced Excel (Coursera)

Leverage Excel’s powerful tools and become a data visualization master.

If you Google “data visualization with Excel,” one of the first results you’ll see will be PwC’s Data Visualization with Advanced Excel. That’s not surprising considering how popular this program is on Coursera. Indeed, 65,000 students have already enrolled in this course, and judging by the reviews (the course averages a 4.8 out of 5.0-star rating), most of them loved it. If you want to improve your Excel skills, you’ll likely enjoy this course, as well.

The course, which even total beginners will be able to follow, demonstrates how to use PowerPivot (a feature within Excel) to design databases and data models. Note that for this course, you need to have Microsoft Excel 2013 or higher. 

On average, most students finish this course in about 15 hours or 4 weeks. During those four weeks, they learn advanced Excel functions and three different analytical methods (scenario analysis, sensitivity analysis, and simulation). They also get to create detailed graphs and charts and perform various scenario and simulation analyses. Finally, students are given a chance to create their own functional dashboards in Excel, too.  

PwC’s Data Visualization with Advanced Excel is a great course that’ll show you the myriad of data visualization tools that exist in Excel. Still not sure whether this course is for you? In follow-up studies, about 1 in 4 students said they received a tangible career benefit from this course and around 1 in 6 were awarded a pay increase or promotion.

Learn Data Visualization with Python (Codecademy)

Learn Data Visualization with Python (Codecademy)

Creating exciting graphs and charts with Python is easy thanks to this Codecademy course.

If you know basic Python (i.e., you can write functions, call methods and objects, and use lists and loops), you could learn how to create visualizations after just six hours of study. How? By enrolling in Codecademy’s Learn Data Visualization with Python.

This Codecademy course is split into two parts. The first part focuses on the plotting library matplotlib. Here, students learn how to design line graphs, bar charts, and pie graphs. This is also where they gain knowledge on how to add error bars, labels, and styling to graphs. At the end of the first part, students get to practice making line graphs. 

The second part takes a look at Seaborn, a Python data visualization library based on matplotlib. This is where students master choosing color schemes for their graphs. At the end of the second part of the course, students have to visualize World Cup data with Seaborn. Students that get to the end of this course earn a certificate of completion. 

If you already have a Codecademy subscription and know how to code in Python, enrolling in Learn Data Visualization with Python is a no-brainer. However, even if you don’t have a subscription, a Codecademy membership might still be worth it, especially if you want to improve your coding skills (or even learn coding from scratch).

What is data visualization?

Data visualization is the presentation of information in a visual context, like a graph, chart, or map. 

The main purpose of data visualization is to make data (and especially data from large datasets) more understandable. After all, it’s much easier to identify patterns by looking at a chart or graph than it is by looking at a spreadsheet. 

Even if you could pull insights from data without visualization, communicating them to someone else — be it management, colleagues, or customers —  without visualization would be much more difficult.

Why is data visualization important?

The reason data visualizations are so important is that the human mind can process visual information faster than written communication. 

Thanks to data visualizations, companies, academics, and individuals can:

  • Draw insights faster.
  • Overcome ambiguity. 
  • Maintain their audience’s interest. 
  • Identify patterns, relationships, and connections.
  • Pinpoint exceptions and outliers. 

What is the best way to learn data visualization?

There isn’t just one way to learn data visualization. The fact is that there are many routes you can take to become a data visualization specialist. However, outlined below is a process that seems to work for most people.

1. Find a good course

The easiest way to learn anything today is to take a high-quality online course. While there are plenty of data visualization courses out there, you need to consider your current data analysis and coding skills before enrolling in one. 

For example, before you learn data visualization, it’s crucial that you understand data and how to present it properly. If you don’t know the difference between a median and an average, your data visualizations may be inaccurate. A good data science or data analysis course can help.

Similarly, you don’t want to waste your time on a data visualization course that relies on Python if you have no prior experience with this programming language or programming in general. Instead, you should focus on courses that feature Excel or Tableau. 

Conversely, if you know how to code, opt for a course that shows you how to present data graphically with the programming language of your choice. R and Python are especially popular for data visualizations, as is Javascript.

2. Create lots of visuals

A good data visualization course will include plenty of assignments and projects. However, once you get to the end of the course, it’s crucial that you keep practicing what you learned. Getting your hands dirty with practical projects is the only way to improve your skills and find out what works and what doesn’t. 

Don’t know where to start? Find a visual you like and try to recreate it. If that works out alright, modify it to make it your own (i.e., use your own dataset, change the shapes and colors, etc.). 

Repeat the above step and know that there’s nothing wrong with using some parts of visualizations you like in your future projects (you may even want to save some visualizations made by other people in a folder on your laptop). Eventually, you should be able to find your own style and design your own visualizations instead of just copying, or remixing, other people’s work. 

If you can’t think of any personal projects or simply need a challenge, check out Makeover Monday. Every Sunday, the site shares a data set. Then, over the next few days, data visualization enthusiasts all over the world analyze it and visualize it. Some of them then share their visualizations on Twitter with a special hashtag. On Wednesdays, the project hosts review the tagged work in a live webinar and give feedback. At the end of the week, they announce their favorite visualizations.

3. Keep learning

Taking one data visualization course won’t suddenly make you an expert in the field, no matter how many visualizations you attempt to create afterward. 

The road to becoming a data visualization specialist is a long one, but you can get there. Becoming active in online communities, reading a lot of books on the topic, and following data visualization blogs can help immensely. 

Tableau has a useful blog post listing 12 great books about data visualization as well as a blog post detailing the 10 best data visualization blogs out there. Reddit’s subreddit Data Is Beautiful is also worth checking out for inspiration. 

Your progress will likely be slow and there will undoubtedly be a lot of confusion. Try to remember that it’s all part of the process. You’re not going to design The New York Times’ worthy visualizations on your first attempt. But your mistakes and feedback from others will help you improve over time.