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Best Data Visualization Courses 2020

Emma Butler
May 17, 2019
Emma Butler

Google’s Chief Economist, Hal Varian claims that “the sexiest job in the next 10 year will be in statistician.” But it’s not the statistician who will have the coveted, pivotal, and crucial job in the future; it’s “Data Powered-Storytellers” (people who know how to create data visualizations). With more and more big data from the internet (90% of data was created within the last two year alone and 2.5 billion GB is produced everyday), it is more important than ever that we can explain, analyze, digest, and compare data in a manageable way to anyone who needs access and understanding of their complex data. The next step is to learn how to be on top of the curve and learn data visualization in order to be the workplace hero you’ll need to be in the upcoming changing years.

Here’s list of the best data visualization courses for anyone at any skill level. Whether you know Python, HTML, JavaScript, CSS or do not have any background at all in computer programming (and have no intent to learn), there is course for you. So whether you’re a seasoned developer or someone who doesn’t go anywhere near the tech team, it is essential you learn good data visualization skills to be the best asset you can to your team or company. More data is being produced everyday and soon it will be insurmountable; you need to learn how to understand and present it in an interesting and exciting way to use your data at its full potential. No more wasted time on analyzing complex data.


A Non-Coder’s Guide to Data Visualization:

Data Visualization: A Practical Approach for Absolute Beginners

Provided by Microsoft

This course is recommended for non-coders who are interested in data visualization. Don’t worry if you aren’t a numbers person; this course will teach you how to turn all those numbers into readable, colorful, visuals that will wow your bosses and be incredibly easy to understand.  Unlike some of the other courses mentioned below, this course will not teach/integrate Python or any other form of programming language. Powered by Microsoft, Data Visualization: A practical Approach for Absolute Beginners, is a new course taught by Pete Harris and Ben Olsen, both Senior Content Developers at Microsoft. A suggested time frame is spending a 2-3 hours on the course for 4 weeks. The course is free, however, if you want to receive a certificate after completion and have your exams graded, the program costs $99.00.


How to use an Easy Universal Platform for Data Visualizations (Non-Coders)

Data Visualization with Tableau Specialization

This course is offered to beginners as well, but it uses Tableau, an easy to use “drag and drop” platform that integrates with almost any database while still enforcing your security protocols. Trends indicate that more data science jobs are putting “mastering of Tableau” on their requirements for job applicants. The colorful, exciting and unique visuals can be made in just minutes by simply importing your data. Tableau is perfect for the non-coder but also gets more and more advanced with coding by integrating R, a popular programming language for data analysts and statisticians. No prior experience with Tableau is needed. This course averages 4 months for completion. Offered on coursera, this course costs $43.00 per month (the faster you finish it the less you have to pay).


Data Visualization for the True Creative (who may or may not know how to code)

Data visualization and D3.js

For a little more in depth course on visualization for the creative minds out there, understanding D3.js is a must. D3.js (Data Driven Documents) is a JavaScript Library that allows for animated, live and interactive graphs, maps, charts, and flows. Any interactive map that you see on a website is D3.js. But this course doesn’t merely stop at learning the basics of D3.j’s; this free course is offered on Udacity.com, and specializes on color theory, design principles, animation, and storytelling. This course is definitely engineered to anyone wanting to be more innovative and expressive, yet still highly effective with their data visualization tools. You do need a basic understanding of HTML, CSS, and JavaScript, or at least fundamental knowledge in programming principles.


Data Visualization for the Want-To-Be-Coder

Learn Python for Data Analysis and Visualization

When you look up Data Visualization, a common language you’ll see associated with it is Python. Python is great for data visualization because it offers Matplotlib and Seaborn, both of which are great plotting libraries (which makes for visualizations that can be live or highly customized). But Python’s power extends beyond data visualization. It’s a super easy to learn language (the most popular at universities and colleges) and allows for easy web application building and automation. Even if you have no idea what I’m talking about, this course teaches everything about Python so no prior knowledge whatsoever is required. This course teaches Python alongside data analysis and visualization techniques.  By the end of the course, you should have a sufficient skill level of Python, have experience working with JSON, HTML and MS Excel Worksheets and use matplotlib and seaborn modules. On sale at the time of posting, this course is 94% off the originally priced $194.99 and now is at $10.99. This course has 21 hours of online lectures with additional worksheets and data sets.


For the Analytical Mind (Basic Code)

D3.Js Data Visualization Fundamentals

Color theory and animations may not be your thing and if you are here to learn about data visualization but would rather focus on subjects like scales, axis and interactivity, this course is for you. This Pluralsight course is marked as a beginner course, but may be more of an intermediate course compared to the other courses listed above. You must be familiar with the basics of HTML, CSS, and JavaScript. In this course you will work with CSV, JSON data and Web API. With close to a 5 star rating, this course is 4 hours 35 minutes long and is taught by Ben Sullins who has more advanced courses on Tableau and other data visualization techniques.

A Thorough and Comprehensive Course on Data Analyzing and Visualizing

How to Process, Analyze and Visualize Data

This course is engineered for people already familiar with Python but want a deeper dive into data cleaning, analysis and visualization.  You will learn how to take raw data, extract meaningful information, use statistical tools, and make visualizations. It’s a more cut and dry course that doesn’t dive into D3.js, color theory or narrative, but you will still be able to create meaningful presentations of data.

This course was taught in a winter session (Independent Activities Period) at MIT and the 6 lecture days were spread out across 4 weeks. Now it is offered for free online.

 

A Deep Dive into Python and Complex Visualization Tools

Data Visualization with Python

If you’re already an intense coder and ready to get intricate and complex with your data visualizations, then this IBM course is right for you. This Coursera course expands upon your knowledge of Python, using namely Matplotlib, Seaborn, and Folium visualization libraries, to create clear presentable data. This course also covers advanced visualization tools such as waffle charts and word clouds and ultimately learn how to design and present geospatial data. This course takes 7 hours to complete but has a recommended time of 15 hours total in terms of studying. At the time of publication, this course has a discount for $39.00 opposed to $43.00 per month.


A Course for the Experienced Developers and Coders

Data Visualization for Developers

This course is specifically designed for developers to learn more about data visualization and is the shortest of courses on this list with a duration of only 1 hour 55 minutes. Coding languages such as HTML, CSS, JavaScript, Python are mandatory to this program. Some key topics this course will cover are Business Intelligence, Visualization Architecture, and Hands-On Visualization. This course costs $35.00 per month.


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