The ability to transform complex data into visually appealing and digestible graphics is vital for all data analysts. Whether you want to enhance existing skills or start from scratch, finding the best data visualization courses will help you pick up the necessary techniques to create these oh-so-important visualizations.
In this article, we’ll explore some of the best data visualization courses available right now, and answer some frequently asked questions. We’ll cover:
- 11 of the best data visualization courses
- How to choose a data visualization course
- Data visualization courses: FAQ
- Wrap up and further reading
Ready to learn more? Then let’s jump right in.
1. 11 of the best data visualization courses
Cost: $1,900 – 2,000
Time commitment: 2 months full-time (40 hours per week), 4 months part-time (20 hours per week).
Perks: Career support, 1:1 mentoring/tutoring, and a job guarantee.
Python is used widely in data analytics, including for data visualization. CareerFoundry’s two-month specialization will teach you how to create different types of visualization using this ubiquitous programming language. The course is ideal for those with prior experience in data analytics with some basic knowledge of Python libraries like Seaborn and Pandas.
Using project-based learning, you’ll pick up various skills, including creating dashboards with multiple visualizations and how to obtain data from the web using APIs. While knowledge of Python’s core functions is necessary—such as importing libraries and setting up coding environments—you’ll learn the finer details as you progress.
Furthermore, what sets CareerFoundry apart from other data visualization courses is that it offers unrivaled career support, including interview coaching, 1:1 mentoring and tutoring, and even a job guarantee. This means if you don’t have a job within six months of completing the course, you’ll get your money back. Well worth the investment!
- Check out CareerFoundry’s complete Data Analytics Program
- Learn more about graduate outcomes
- Attend one of CareerFoundry’s online events
Cost: $8,500 – $11,300
Time commitment: 20-25 hours per week for 6 months
Perks: Highly comprehensive, offers 1:1 mentoring with industry professionals and career coaches
If you’re considering changing careers without prior knowledge of data analytics, Springboard’s Data Analytics Career Track might just be in order. This five-module course doesn’t only cover data visualization but the entire data analytics process. While it’s a more comprehensive program (with a comprehensive price tag to match!) you’ll learn everything from framing structured thinking and business analysis to connecting data with SQL and visualizing it with Python.
If you’re keen to focus on data visualization alone, this won’t be the best option to get you started. And at $8,500, it’s the priciest entry on our list. However, if you want the full program end-to-end, you may decide it’s worth the investment. It’s also worth checking out this list of the best data analytics programs.
Cost: $399/month or $1,356 for four months.
Time commitment: 4 months at 10 hours a week
Perks: Technical mentor support, expert guidance, and career services
Udacity’s Data Visualization Nanodegree program is a 4-month course going in-depth on data viz. It consists of four units: Intro to Data Visualization, Build Data Dashboards, Data Storytelling, and Advanced Data Storytelling.
Alongside the basics, you’ll learn everything from building interactive and engaging Tableau dashboards to identifying key metrics and understanding how to tell a good story with your data. In addition to the theory of data viz, you’ll also learn how to use Tableau to add interactivity (such as animations and narration) to your visualizations.
For some, the price may be too high. However, if you want practical guidance that goes beyond the basics and to learn how to leverage Tableau tools to the best of your ability, you’ll find few options this focused and comprehensive.
- Check out student success stories
- Learn about Udacity’s personalized services
- Read more about Udacity
Cost: $25/month, with regular discounts for businesses and students.
Time commitment: 2 hours
Perks: A great selection of short, punchy courses
Datacamp is a top source of short courses for those looking to dip a toe into data analytics. In particular, they have a wide selection of data viz programs focused on tools like Python, Tableau, ggplot, and R. For total beginners, though, their Understanding Data Visualization course is accessible for all and requires no prior coding experience.
The course will teach you how to choose the best visualization for a particular dataset and how to interpret common plot types, including histograms, scatter plots, line plots, and bar graphs. It also covers best practices regarding color usage and shapes and common pitfalls to avoid. While this is a short course—just 2 hours long—it manages to pack in plenty of hands-on exercises, and you’ll explore over 20 fascinating datasets ranging from global life expectancies to home prices in LA and even the greatest hip-hop songs of all time! Once you’ve completed the course, you can use your subscription to focus on a specific tool that suits your needs.
- Meet the instructor
- Browse Datacamp’s full selection of data visualization courses
- Check out pricing
Cost: $17.49/month (billed annually) or $34.99/month (billed monthly)
Time commitment: 6 hours
Perks: Content is freely accessible (but you’ll need to pay for certification)
Like Springboard’s offering, Codecademy’s Principles of Data Literacy course provides a full introduction to data analytics but at a fraction of the cost. Okay, so at 6 hours, it’s not nearly as comprehensive, but it suitably fills the market gap between free tutorial and full program, with the third module dedicated to data visualization.
The first lesson of this module, Data Visualization Basics, explores various types of graphs and how to choose the right one for your dataset. For instance, which visualization should you use for univariate, bivariate, and multivariate data? It also explores the often-overlooked issues of aesthetics and universal design.
The second lesson, Misleading and Confusing Graphs, explores common mistakes and how to avoid them, with a deep dive into how to properly use features such as axes, scaling, colors, labels, and titles. Once you’ve covered the basics, you can also explore Codecademy’s more targeted courses including data visualization with Python (8 hours) and Tableau for data viz (5 hours).
Time commitment: 2 hours
Perks: Affordable and punchy
LinkedIn Learning, formerly known as Lynda.com, offers a wide selection of data visualization courses. Though these courses are relatively short, typically lasting around two hours, they are affordably priced and provide a solid foundation to build on.
Among the courses available, Data Visualization Tips and Tricks stands out. Led by data viz expert, Matt Francis, the content is designed for experienced data scientists and analytics specialists but is software-agnostic. It covers a range of topics, from understanding the relationships between data sets, making comparisons and charting relationships, visualizing data distributions, and creating maps.
You’ll also learn how to critically analyze other people’s visualizations, ask informed questions, and evaluate data viz constructively. Want to expand your knowledge further, or into specific tools and techniques? Then your subscription will cover LinkedIn’s full selection of available courses.
Cost: $149 (or free ‘audit’ access without a certification)
Time commitment: 8 weeks, 1-2 hours per week
Perks: Self-paced, so you can feasibly complete the course in one intensive day
EdX’s Data Science: Visualization course, offered in collaboration with Harvard University, is one part of the platform’s Professional Certificate Program in Data Science. Based online, you’ll learn the fundamentals of data visualization and exploratory data analysis, focusing specifically on ggplot2—a powerful data visualization package for R.
Since it’s part of a more comprehensive program, you may benefit from some prior knowledge of R. However, the course uses simple datasets and explores engaging topics such as world health, economics, and infectious disease trends in the US. You’ll also learn to recognize how mistakes, biases, systematic errors, and other unexpected problems can lead to data that needs careful handling. So if you’re interested in expanding your R skills into data viz, this course is worth considering.
Cost: $59/month, cancel anytime
Time commitment: 14 hours
Perks: Is accepted as academic credit as part of CU Boulder’s Master of Science in Data Science degree program
Coursera’s Fundamentals of Data Visualization course, in partnership with the University of Colorado Boulder, is another mid-length course focusing on the basics of data viz. At 14 hours of learning, it is best suited to those with intermediate knowledge of Python. Topics include user-centered design, web-based visualization, data cognition and perception, and all-important design evaluation. Through practical tasks, you’ll gain hands-on experience creating visualizations, using exploration tools, and architecting data narratives.
One of the benefits of this course is that it is accepted academic credit as part of CU Boulder’s Master of Science in Data Science (MS-DS) degree program. Whether you want to take the full program or the standalone course, it should provide a solid toolkit for exploring and communicating complex data and producing visualizations using Python and the proprietary tool, Altair.
Time commitment: 300 hours, self-paced
Perks: Completely open source and community-connected
Unlike the other courses on our list, this is more of a self-guided tutorial than a face-to-face or online training program, but it’s thorough. Once you’ve learned to work with D3, APIs, and more, you’ll apply these skills across five data visualization projects. Complete these to receive your certification.
Although unlike other data visualization courses this one offers no extra perks such as mentoring or job guarantees, it is free, and you can find peer support in the FreeCodeCamp forum.
Cost: $189.99 (with regular discounts)
Time commitment: 4 hours
Perks: Self-paced videos online
MS Excel might not be as “sexy” as more modern tools like Tableau, or even programming languages like Python, but it’s still big biz in data viz! Udemy’s Data Visualization Excel Charts and Graphs course offers a comprehensive introduction to Excel’s visualization tools and techniques, along with interactive demos and exercises to keep you engaged every step of the way.
The course covers over 20 charts and graph types introduced in MS Excel 2016, including custom 3D surface contour charts and geospatial maps. Additionally, you’ll dive into a series of 12+ advanced Excel demos.
Overall, the course is an excellent option for anyone looking to expand their Excel skills. And let’s face it, whether you love MS Excel or loathe it, it is ubiquitous. Self-paced and only 4 hours long, it’s also good value for money. A prime option for those who are tight of wallet!
Cost: $59/month, cancel anytime
Time commitment: 4 months, 4 hours a week
Perks: Get a certification with the renowned John Hopkins University
While it’s not the only option, R is the core programming language for many data analysts. Coursera’s Data Visualization and Dashboarding with R Specialization provides a comprehensive introduction across five modules. Module 1 starts with an introduction to R, covering basic areas like data import, manipulation, and simple report generation. You’ll then expand your focus to the ggplot2 package, where you’ll create a variety of visualizations and refine them using vector graphics editing software.
The third module introduces additional packages and techniques to create even more complex visualizations, including spatial data and interactive and animated figures. Meanwhile, in the fourth, you’ll learn how to create interactive dashboards using Shiny, before completing the training with a hands-on capstone project. While R is a trickier language than Python, the course targets those with good basic computing skills but limited programming expertise, making it accessible even for beginner learners.
2. How to choose a data visualization course
While we’ve provided several options, choosing the right data visualization course can be overwhelming if you’re new to data analytics.
The main thing to remember is that your needs come first: no single course is objectively better than any other. When choosing the best data visualization course for your needs, ask the following questions.
What do you want to learn?
What exactly do you want to achieve through the course? For example, do you want to understand the fundamental concepts of data visualization? Or are you looking to learn about a specific data visualization tool? Determining your objectives makes it much easier to narrow the options down.
What format works best for you?
There are self-paced, instructor-led, online, and even offline courses available. Considering your preferred learning style will help you select a course that’s right for you. For a practical topic like data visualization, aim to find an option offering hands-on practice and real-world examples.
Who is the instructor?
Courses don’t necessarily need a ‘celebrity’ instructor but it’s worth looking for one taught by an experienced professional with expertise in the field. Research the instructor’s background and credentials before enrolling.
What do others say about the course?
The best marketing is word of mouth, so check out course reviews from previous learners. Sometimes reviews are offered on the course page, but it’s worth checking out the provider on sites like Trustpilot or Reddit for more honest feedback. Doing so will help you gauge the course’s quality and the needs of its typical students.
How much are you willing to spend?
Finally, cost! Only you can decide how much you’re willing to invest. While some courses may seem expensive, remember that they are often higher quality. They can also offer extras like certification, career support, and mentoring, all of which contribute to the higher price, but also a higher chance of securing a job. Always consider the long-term investment, not just the cost-price.
3. Data visualization courses: FAQ
Here are some common questions you might have before choosing a data visualization course:
Do you need math for data visualization?
Yes, having a basic understanding of math is helpful in data visualization. You don’t need to be an expert in complex mathematical concepts, but some fundamental knowledge of statistics, algebra, and geometry can be helpful when creating data visualizations. You can pick a lot of this up as you learn, though. The main thing is that you’re comfortable working with data and numerical information.
Is data visualization in demand?
Yes, data visualization is highly sought-after in many industries. It is becoming more pronounced in sectors from journalism to finance, healthcare, and government. Across the economy, there is a growing need for professionals who can analyze and present data in a compelling, easy-to-understand way.
Does data visualization require coding?
Not necessarily. There are many tools available to help you create data visualizations without coding skills. However, having some knowledge of coding using programming languages like Python and R can be very helpful when working with large datasets and complex visualizations. But even these often use libraries of pre-existing code, minimizing the amount of work you have to do.
What skills are required for data visualization?
While any good course should teach you the necessary skills you need to carry out effective data visualization, some important ones to look out for include:
- Understanding the basics principles of data analysis
- Knowledge of design principles and visual communication
- Ability to use data visualization tools and software
- Basic math and statistics
- Attention to detail and the ability to spot trends and patterns in data
- Critical thinking and problem-solving
- Excellent presentation skills
Many of these are so-called “soft” skills, meaning they don’t necessarily require complex technical know-how. The best way to perfect these skills is to put theory into practice, so always look for courses that allow you to do so.
4. Wrap up and further reading
We’ve also unpicked how to find the best program for you and answered some of your most commonly asked questions!
One way to choose the right course is to learn more about data analytics first. Why not sign up for this free, 5-day data analytics short course? You’ll get daily lessons delivered right to your inbox.
Alternatively, read up with the following introductory guides: