What is data visualization?
A picture is worth a thousand words. This old saying is very apt in the case of data sets, no matter their size. We can all agree that we prefer a pie chart than to pore through the underlying data looking for patterns and conclusions.
This is nothing but a simple example of data visualization. It is the method of relaying data or information in the form of figures, bars, and charts.
Data visualization is invaluable for decision making, research, and analysis. Most data processing software regardless of simplicity has options to display data graphically.
Data is the new oil. Data visualization is no exception. Every data related discipline today can be used to launch an exciting and fulfilling career. The following courses will help you contract a solid foundation and gain a thorough understanding of data visualization and its applications.
- University of California, Davis – Data Visualization with Tableau Specialization
Offered on the Coursera platform, this is a free, self paced course, although payment is required for a certificate on completion. The time investment is likely to be approximately twenty two weeks with three to eight hours of dedicated study per week.
You will be required to know the fundamentals of computer science and basic programming.
The course uses Tableau’s vast resources showcase the methods which lead towards amazing storytelling through data and teach you how to create powerful dashboards and reports for decision making and action plans.
This includes the use of predictive analytics. Real world examples of data visualization application, especially in business will be covered.
To successfully complete the course, you have to use sample data to create data models, visualizations and dashboards and present your findings to the management of a fictional company.
- Microsoft Corporation – Data Visualization: A Practical Approach for Absolute Beginners
Offered on the edX platform, this course is for absolute beginners. It is completely free and consists of four modules. This is the most comprehensive course for application based data visualization.
Several tips, techniques, and tricks are covered enabling the student to successfully understand data and choose the best way to present it graphically for maximum impact.
No previous programming knowledge or experience is necessary. The course emphasizes regular projects and exercise, which is great for practical training.
- SuperDataScience – Tableau A-Z: Hands-On Tableau Training for Data Science
This self paced course offered on Udemy and can be accessed with nominal payment. It’s a relatively short course compared with the other options here, ending at sight hours.
The focus is on using Tableau for data visualization which means the course is geared towards decision making in business. Tableau’s features are covered in detail, and you will learn how to explore and understand data, prepare a base, and present and easily understood graphical representation.
Tableau simplifies the spotting of patterns in data such as sales trends, customer behavior, and cost variance.
This course is composed of three parts which together cover sixteen hours and requires payment for access of $300 per year.
The objective of Part 1 of the course is to enable you to create “complex exploratory plots”. So, the first necessary layers for plot making: data, geometrics, and aesthetics are covered.
The objective of Part 2 of the course is to combine statistics and visuals to make a custom plotting function for a gigantic data set. The plots will be created using R directly.
After building a strong foundation, advanced topics are introduced such as geoms, large data set operational strategies and some effective attributes of ggplot2 internals.
- PluralSight – Data Visualization Using Tableau Public
This is one of the most highly rated courses on PluralSight, not surprising since the creator worked with Microsoft for nearly ten years.
The course uses Tableau Public to build a foundation in the data visualization discipline. You can pick apart and understand data and recombine it in various ways to see if conclusions differ.
By the end, you will have created a dashboard, charted consumer spending patterns and understood the true cost of winning.
This course was created by IBM and is offered on the Coursera platform. It is a highly rated course and requires a time investment of three weeks.
An intermediate level knowledge of Python programming language will be beneficial. The key takeaway is how to take dissimilar data and rephrase it so that logical conclusions can be drawn from it.
Python data visualization libraries such as Folium, Matplotlib, and Seaborn are used to present data in a visual manner. The best industry practices in geospatial data and advanced visualizations are incorporated in the lessons.
The course requires a basic understanding of advanced mathematics and statistics and intermediate Python programming skills. Python libraries such as Matplotlib and Seaborn are used frequently throughout to extend a firm base in data visualization.
You will be using image data and time series, statistical graphics (regressions and visualizing distributions), plotting two dimensional arrays (images, pseudo color plots, and contour plots) and customizing graphics.
By the end, you will learn how to use Seaborn to build statistical plots, customize plots, plot 2D arrays and analyze images and time series.
- Pluralsight – js Data Visualization Fundamentals
The emphasis is on using data driven documents to present impactful data visualization. You will learn to practically apply color theory, human perception, effective storytelling and applying design principles to data visualization.
By the end, you will be able to work with external data sources, enhance visualization with interactivity, enhance visualization with axis and scales and mapping and charting.
- Udemy – Data Visualization with Python and Matplotlib
This course is provided on the Udemy platform. The prerequisite is at least an intermediate understanding of Python and Python’s Matplotlib library is used extensively for plotting.
The course includes 58 lectures covering all major charts in the Matplotlib library. By completion, you will be able to build properly presented and impactful graphs.
You will also be able to work with 3D and 2D graphs, bar charts, line graphs and scatter plots, use geographical data from maps and procure data from various sources for data visualization.
Even if you are not related to the tech field at all, completing a beginner level course in data visualization can add the extra something that distinguishes you from others in the job market.
Employers expect job seekers to have a firm understanding of how technology and data are driving the world. So pick one of these courses and get started!