In this age and times of Technology and Big Data, Data visualization is increasingly becoming an absolute must-learn skill. As organizations become more and more data driven, not only do we need to interpret large amounts of data, but also be able to analyze, explain, digest and compare complex data in a manner that it is accessible to anyone who needs understanding of that data.
Also because of the way our human brain processes information, visually-displayed data in the form of charts or graphs etc is easier to understand than sets of spreadsheets and reports. A well thought out visualization peels back the layers surrounding a raw dataset. All businesses these days are therefore leveraging Data Visualization to analyse information faster, recognise patterns and trends, and find valuable insights. Organizations of all sizes are looking for Data Visualization experts. So the ability to work with data is not just a bonus skill, but an essential one, in fact it is the highest ROI skill in current times.
Data Visualization is not just limited to the field of data scientists and data analysts, in all careers whether finance, marketing, tech, design, etc. there is a need for data communicators who can visualize data and convey results effectively to both technical and non-technical people.
So this is the best time to learn data visualization and be on top of the curve. Online courses offer an effective medium to learn the right skills and increase your employability. We’ve rounded up this list of Best Online Data Visualization courses, certifications, classes, training programs and tutorials that you can take this year. All of these are available online, some are free while some are available at minimal costs. These cover Data Visualization with Tableau, Python, R, d3.js, Excel etc.
1. Data Visualization with Tableau Certification by UCDavis (Coursera)
This Tableau training for Data Visualization has been developed by University of California in collaboration with Tableau and offered via Coursera platform. It is one of the best combinations of theory and practical training in Tableau that starts with the fundamental concepts of data visualization, and various tools that Tableau has to offer and builds from there to finally creating multi-frame data stories in Tableau.
This data Visualization training program leverages Tableau’s library of resources to teach learners the best practices for data visualization and data storytelling. It comprises of following 5 courses:
- Fundamentals of Visualization with Tableau – This course introduces learners to data visualization and the Tableau interface. It also covers how to prepare and import data into Tableau.
- Essential Design Principles for Tableau – This course teaches how to analyze and apply essential design principles to your Tableau visualizations.
- Visual Analytics with Tableau – This course delves into the tools Tableau offers in the areas of charting, dates, table calculations and mapping.
- Creating Dashboards and Storytelling with Tableau – This course teaches how to create dashboards to identify the story within your data, and how to use Storypoints to create a powerful, impressive and effective story for your audience.
- Data Visualization with Tableau Project – This is a capstone project where learners are required to create a single-frame viz or multi-frame data story that is then shared on Tableau Public.
This is a beginner level Data Visualization using Tableau certification program, and is an excellent fit for anyone who is comfortable working with data and datasets and wants to get started with learning data visualization and tableau. No prior technical or analytical background is required to enrol in this specialization.
Key Highlights
- Most popular Coursera Data Visualization certificate program
- Learn to use Tableau to create high-impact visualizations of common data analyses
- Learn to generate powerful reports and dashboards to help people make decisions and take action based on their business data
- Explain the relationship between data analytics and data visualization
- Examine the similarities and differences of exploratory and explanatory analysis
- Learn to apply predicative analytics to improve business decision making
- Understand how Tableau can use different types of geographic data, how to connect to multiple data sources and how to create custom maps
- Learn advanced functions within Tableau, such as hierarchies, actions and parameters to guide user interactions
- Learn with examples from real world business cases and journalistic examples from leading media companies
Duration : Approx. 6 months, 3 hours per week
Rating : 4.6
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2. Data Visualization with Python by IBM (Coursera)
This Data Visualization online course has been created by IBM and is available on Coursera. It is rated amongst the top data visualization with Python courses with more than 85K students already enrolled in the course. It teaches learners how to leverage Python to visualize data to enable them to extract information, better understand the data, and make more effective decisions. It covers several data visualization libraries in Python, namely Matplotlib, Seaborn, and Folium that are used to present the data visually.
The course is spread over 3 weekly modules requiring approximately 18 hours of total effort to complete. These modules cover the following concepts:
- Introduction to data visualization tools
- Basic plotting with Matplotlib
- How to read csv files into a pandas dataframe and process and manipulate the data in the dataframe
- How to generate line plots using Matplotlib
- Specialized Visualization Tools like area plots, histograms, bar charts, pie charts, box plots, scatter plots and bubble plots etc. and creating them with Matplotlib
- Advanced visualization tools such as waffle charts and word clouds and how to create them
- Visualization library Seaborn and how to use it to generate regression plots
- Geospatial data and visualizing it using Folium library
- How to create Choropleth maps
- How to use Folium to create maps of different regions of the world and superimpose markers on top of a map
Upon completing this data visualization training course, learners are able to take any seemingly meaningless data set and present it in a form that others can comprehend well and make sense of. It is intended for intermediate users with some experience in Python and handling data.
This course is a part of following Data Science specializations and professional certificate programs by IBM. When you complete this course, it will be counted towards your learning in these programs.
- IBM Data Science Professional Certificate
- IBM Applied Data Science Specialization
Key Highlights
- Learn the best techniques and methods to analyze and visualize data with Python programming
- Learn the data visualization libraries in Python – Matplotlib, Seaborn, and Folium
- Learn the best practices for creating plots and visuals
- Learn with real data sets and real world examples
- Multiple hands-on exercises, assignments and graded quizzes to apply the learning
- Course content is free to audit, with an option to pay a small fee for to access graded materials and verified certificate of completion
Duration : Approx. 18 hours
Rating : 4.6
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3. Data Visualization and Communication with Tableau by Duke University (Coursera)
This Course on Data Visualization with Tableau is offered by Duke University as part of its Excel to MySQL: Analytic Techniques for Business Specialization. The goal of this course is to prepare learners to become an expert at communicating business-relevant practical implications of their data analyses. It teaches them to streamline their analysis by asking the right questions and use Tableau to convey critical findings. Students learn Storyboarding skills and how to visualize the results of data analysis or machine learning models in Tableau, so that it can be better understood by both technical and non-technical stakeholders.
Tableau is the most popular visualization tool in the market. This course explores various Tableau features that can be used to create effective visualizations that convey conclusions clearly and directly. Spread over 5 weeks, the course is approximated to require around 25 hours to complete. It includes a peer-reviewed final project that assesses a student’s learning of the subject. The topics covered in the course are:
- Creating graphs that are used in business analysis
- Transforming data in Tableau
- Designing business dashboards with Tableau
- Creating and delivering compelling business presentations
- How to craft the right questions to ensure your analysis projects succeed
- Writing calculations and equations in Tableau
- Adapting visualizations to make them maximally communicative
Key Highlights
- Understand how to structure your data analysis projects to ensure that they lead to actionable advice that can be presented to stakeholders
- Learn to communicate results and implications of your quantitative analyses visually in a way that non-technical people can understand
- Publish online business dashboards with Tableau
- Learn a set of tools and concepts that you can use to optimize your visualizations and your presentation style
- Series of practice exercises that involves doing analyses on a sample data set
Duration : Approx. 25 hours
Rating : 4.7
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4. Tableau Training and Certification Courses (Udemy)
Tableau is a very powerful Data Visualization and Analytics tool. With increasing focus on data and data-driven technologies, knowledge of tools like Tableau is becoming a must skill for anybody working in Big Data, Data Analytics or Data Science. Udemy offers a good range of courses to learn Tableau to understand, handle and interpret data better. From introductory courses well-suited for beginners to advanced ones for people already working in the field of data visualization, these Tableau tutorials can be availed at a minimal cost to learn Tableau online at one’s own pace and schedule.
Of all Udemy Tableau courses, particularly noteworthy is Tableau training series by Kirill Eremenko (a very well regarded instructor with around 1.5 million students on Udemy) and SuperDataScience Team, which includes following two courses.
- Tableau 2020 A-Z: Hands-On Tableau Training for Data Science
- Tableau 20 Advanced Training: Master Tableau in Data Science
Together these two Tableau courses have more than 270000 students enrolled with an average rating of 4.6 and favourable reviews. The series has more than 18 hours of video content and focuses mostly on the coverage of Tableau tool, rather than the theory of data visualization. Let us look at each of these courses in some detail.
Tableau 2020 A-Z: Hands-On Tableau Training for Data Science
This is the first course in the series and offers a practical step-by-step guide to learning tableau with real-life examples, data analytics exercises and assignments. It covers in detail all the features in Tableau that are used to explore, experiment with, fix, prepare, and analyse raw data and convert it into compelling data visualizations. Following topics are covered in this Tableau tutorial:
- Connect Tableau to a Variety of Datasets
- How to work with data extracts and timeseries
- How to use aggregations to summarize information
- How to create various charts, maps, scatterplots, and interactive dashboards
- How to create table calculations, treemap charts, and storylines
- Analyze, Blend, Join, and Calculate Data in order to work with and present information from multiple sources
- Export Results from Tableau into Powerpoint, Word, and other software
Tableau 20 Advanced Training: Master Tableau in Data Science
This is the second and more advanced course in the series of Tableau udemy courses by Kirill Eremenko. It dives into depth on some of the most powerful features of Tableau. It promotes learning data visualization and data mining by doing, for which it uses unique datasets and engaging exercises to solve real life analytics problems. Following topics are covered in this Tableau class:
- How to use Groups and Sets to increase your work efficiency 10x
- Everything about Table Calculations and how to use their power in your analysis
- Advanced data preparation techniques
- How to perform Analytics and Data Mining in Tableau
- How to create Animations in Tableau
- Advanced Mapping Techniques
- Create powerful storylines for presentation to Executives
Key Highlights
- Best courses to learn Tableau for Data Science
- Includes real-life data analytics exercises & quizzes
- Understand how Tableau is employed in the real world to solve actual business problems
- Learn to create bar charts, line charts, area charts, maps, scatter plots, treemaps, interactive dashboards and storylines
- Great fit for beginners or advanced professionals who want to gain right skills to leverage the full potential of Tableau
Duration : Self-Paced
Rating : 4.6
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5. Udacity Data Visualization Nanodegree Certification (Udacity)
This Data Visualization program offered by Udacity is a world-class, cutting edge training program to build data visualization and communication skills. Udacity has collaborated with Tableau, the most popular data visualization tool, along with an excellent group of industry professionals with extensive experience to create curriculum that focuses on most in-demand skills. The program teaches learners to create clear and impactful data visualizations and use their analysis to make data-driven recommendations.
A lot of focus of this Data Visualization certification program is on building storytelling skills. Since, stories offer a powerful way to draw in the audience, make sense of the data and help businesses make better decisions, this program teaches learners how to weave data into stories and visuals using various tools and techniques. Two data visualization platforms Tableau and Flourish are covered in the program.
The program comprises of four courses that cover the following topics:
- Introduction to Data Visualization
- How to select the most appropriate data visualization for an analysis
- How to create interactive and engaging Tableau dashboards
- Design and create a dashboard in an enterprise environment
- End to end process for Data Storytelling
- Advanced data visualization and storytelling techniques
- How to add interactivity and other visual elements to a story
- How to add animation and narration with Tableau Pages and Flourish
Throughout the program, students build a portfolio of high-quality projects to showcase the data visualization and storytelling skills that they learn.
This program is an excellent fit for people with data background who wish to maximize the impact of their analyses or those with business background who want to persuade others to make more data driven decisions. It requires students to have basic skills in data analysis including spreadsheets and descriptive statistics.
Key Highlights
- Learn to combine the power of data analysis and storytelling to create impactful narratives with data
- Build interactive dashboards with Tableau
- Learn to incorporate advanced animation and narration into your stories
- Hands-on projects involving creating multiple types of Dashboards like Static Dashboard, Dynamic Dashboard, and Animated Dashboard
- Learn the Flourish Studio’s Talkie feature that allows you to add narrative audio to accompany your data story
- Access to a 1-on-1 technical mentor to answer questions, review work, and provide guidance
- Access to student community for network and support
- Access to a personal career coach and career services
Duration : 4 months, 5-10 hours per week
Rating : 4.6
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6. Data Visualization with Advanced Excel by PwC (Coursera)
This course has been created by PricewaterhouseCoopers (PwC) and is part of their Data Analysis and Presentation Skills: the PwC Approach Specialization. This goal of this course is to help learners expand their analytical skills by answering questions and telling a story with their data. It uses Excel to develop data visualization skills as Excel is the most widely used software tool and is easily available to most learners.
This Data Visualization with Excel course is loaded with hands-on instruction of advanced Excel 2013 functions. It is structured as 4 weekly modules, each requiring around 4 hours of effort to complete. These modules cover the following topics:
- Week1 – This is all about linking data and data models. It covers components of data sets and relational database models and shows how to create databases and data models within Excel using PowerPivot.
- Week 2 – In this week learners will use data to perform various types of scenario and simulation analysis. They will get to practice these skills in Excel by leveraging some of Excel’s built in tools including solver, data tables, scenario manager and goal seek.
- Week3 – This week’s modules focus on data visualization. They cover the basics, outlining the theory and concepts behind data visualization. Also teach how to create detailed graphs and charts to effectively tell a story about your data.
- Week 4 – This week’s lectures use excel to build complex graphs and Power View reports and discuss how to combine them into dynamic dashboards using tools such as form control, slicers and conditional formatting.
The course contains several practice exercises and quizzes at the end of each module. The popularity of this course can be gauged from the fact that it enjoys a handsome rating of 4.8 with more than 65K students enrolled in the course.
Key Highlights
- Understand how to develop a data model using PowerPivot
- Understand the difference between effective and ineffective charting
- Learn to selecting the right type of chart to tell your data story
- Learn how to create column chart, combo chart, stacked column chart, heatmap, gantt project plan and power view reports
- Learn to create your own functional dashboard in Excel
Duration : 4 weeks, 4 hours per week
Rating : 4.8
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7. Learning Python for Data Analysis and Visualization (Udemy)
This course has been created by Jose Portilla and is available on Udemy. The goal of this course is to provide learners with a complete understanding of Python and how it can be used effectively to analyse and visualize data. This course covers NumPy, pandas, how to import and export data in Python, how to visualize that data with Python libraries and data portfolio projects. It also touches upon Machine learning with Scikit-Learn. In addition to all of this it has appendix materials including materials on Statistics, using SQL with Python and how to perform webscraping with Python.
The course includes more than 21 hours of video content in 100+ lectures, example python code notebooks, supplemental articles and reading materials, several data analysis projects that learners can use for their portfolio.
The course guides learners through several data analysis libraries in Python:
- NumPy – how to use Numpy to create and manipulate arrays with Python
- Pandas – how to use Pandas to create series, dataframes and do quick and effective analysis on data. Also covers Pandas built-in visualization tools
It also demonstrates how to create different visualizations for a wide range of data sets using following Python libraries:
- Matplotlib
- Seaborn
Students also learn to use SciPyto create distributions and solve statistical problems.
Key Highlights
- Excellent fit for learning how to program in Python and create Data Visualization with Python libraries
- Learn Data Analysis by Numpy and Pandas
- Learn how to use Python and Pandas to work with data in a variety of formats like JSON, HTML, text, csv and even Excel files
- Learn to create modern, impressive data visualizations using Matplotlib and Seaborn modules with python
- Learn to create a variety of charts, Bar charts, Line charts, Stacked charts, Pie charts, Histograms, KDE plots, Violin plots, Box plots, Regression plots, Scatter Plots, and Heatmaps
- Get access to over 100 example python code notebooks
- Build a portfolio of various data analysis projects
Duration : 21 hours on-demand video
Rating : 4.3
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8. Mastering Data Visualization in D3.js (Udemy)
D3.js is a JavaScript library for data visualization; very powerful for creating visually appealing charts, maps, flows, live and interactive graphs and other data-driven visualizations. This Udemy Data Visualization course, developed by Adam Janes, provides a comprehensive introduction to D3.js library and how to use it to design and create impressive data visualizations. It takes learners from being complete novices to D3 to being able to develop any visualization they could imagine. Not only does it teach learners to create common charts and graphs, but also provides them with tools to pick up any visualization by themselves.
This Data Visualization with D3.js course is structured into three parts:
- Part 1: Fundamentals of D3 – It covers the fundamentals of how D3 works. Learners are introduced to SVGs, data joins, scales and axes and how to create interactive visualizations by adding events to the page.
- Part 2: Visualization walkthroughs – It introduces learners to many types of visualizations and walks them through example code line-by-line. Following 12 visualizations are covered.
- Line Charts
- Area Charts
- Stacked Area Charts
- Pie Charts
- Donut Charts
- Wordclouds
- Choropleth Maps
- Node-Link Diagrams
- Tree Diagrams
- Treemaps
- Circle Packs
- Sunburst Plots
- Part 3: Complex linked views – It teaches learners to create unified web apps where many visualizations on the page communicate with each other at the same time.
This is a very hands-on course with 4 class projects (involving bar chart, updating bubble chart, interactive line chart and a data dashboard) that allow learners to consolidate their learning and practice their skills with real world data sets.
This Data Visualization class is intended for learners who already have some experience at programming on the web and want to learn about data visualization design and build complex interactive websites with D3js.
Key Highlights
- Best online course for Data Visualization in D3.js
- Understand the fundamental building blocks of D3
- Understand fundamental principles for design that help you to come up with unique visualizations of your own and articulate your design decisions to others
- Learn to choose the right visual channels for the data you’re working with to create unique visualizations
- Master advanced tools in D3, building choropleth maps, brushes, tooltips, and layouts
- Critique existing visualizations and invent better designs for displaying data
Duration : 7 hours on-demand video
Rating : 4.4
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9. Free Online Data Visualization Courses (edx)
edX offers free Data Visualization courses and training programs in partnership with top universities and global institutions to build right, most-in-demand skills in this field. These include Professional Certificates, Micromasters programs and individual courses. One can enrol in these for free, but for access to graded assignments and projects and for receiving a certificate of completion to showcase the acquired skills, one needs to pay a fee dependent on the program or course enrolled.
Most courses are self-paced, so learners can start anytime and take any amount of time to complete them. This flexibility of timelines makes these programs very attractive to professionals who want to uplevel their skills while continuing with a full-time job.
Learners can take edX Data Visualization courses to gain foundational skills in data visualization, learn to use various tools and software to perform data analyses and combine data with visuals in order to create impactful presentations that help to make sound business decisions.
Some of the top data visualization courses on edX include:
- Data Science: Visualization by Harvard University
- Visualizing Data with Python by IBM
- MATLAB and Octave for Beginners by EPFL
- Analyzing and Visualizing Data with Power BI by Davidson College
- Data Analytics and Visualization in Health Care by Rochester Institute of Technology
- Data Visualization for All by Trinity College
Let us look at two most popular courses of these in detail below.
Data Science: Visualization by Harvard University
This course by Harvard University is part of their Professional Certificate program in Data Science. It teaches the basics of data visualization and exploratory data analysis and how to apply the data visualization principles using ggplot2 (data visualization package for the statistical programming language R). This course covers the following topics:
- Principles of data visualization
- How to communicate data-driven recommendations of your analyses
- How to use ggplot2 to create custom plots
- The weaknesses of several widely-used plots and why you should avoid them
- Case studies about world health, economics, and infectious disease trends in the US
Visualizing Data with Python by IBM
This course by IBM covers how to visualize data using Python libraries that enables better understanding of the data and efficient conveying of the findings to clients, customers and stakeholders in general. It explores data visualization libraries in Python, including Matplotlib, Seaborn, and Folium for presenting data effectively. The topics covered in the course include:
- Basic visualization tools, including area plots, histograms, and bar charts
- Specialized visualization tools, including pie charts, box plots, scatter plots, and bubble plots
- Advanced visualization tools, including waffle charts, word clouds, and Seaborn and regression plots
- Creating maps and visualizing geospatial data
Key Highlights
- Become confident in working with data, creating data visualizations, and preparing reports and dashboards
- Learn to tell your story with interactive charts and maps on the web
- Learn data visualization best practices
- Complete flexibility to learn on your own time and pace
Duration : Self-Paced
Rating : 4.5
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10. Data Visualization by University of Illinois (Coursera)
This course on Data Visualization is offered by University of Illinois at Urbana-Champaign and is a part of their Data Mining Specialization. It trains the learners in the in-depth concepts, methods, and applications of pattern discovery. It teaches different visualization systems, how computer graphics is used to present data and how we observe and perceive data based on how it is presented.
The course is spread across 4 weeks, each requiring around 4 hours for completing the modules in that week. Following topics are covered in the course:
- The Computer and the Human – It covers the basic concepts of data visualization is and how it’s used, different types of visualization and how humans perceive information.
- Visualization of Numerical Data – It covers assigning data to appropriate chart elements, using glyphs, parallel coordinates, and streamgraphs, as well as implementing principles of design and color to make visualizations more engaging and effective.
- Visualization of Non-Numerical Data – It covers how to visualize graphs that depict relationships between data items.
- The Visualization Dashboard – It teaches learners to design their own visualization system for large datasets and dashboards.
Key Highlights
- Understand the general concepts of data mining along with basic methodologies and applications
- Learn to plot charts, glyphs and stacked charts
- Learn tree maps and graph visualization
- Learn principal component analysis and multidimensional scaling
- Learn to apply techniques from user-interface design to create an effective visualization system
Duration : 4 weeks, 2-4 hours per week
Rating : 4.5
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11. Information Visualization Specialization by NYU (Coursera)
This program in Information Visualization is offered by New York University, via Coursera, with the goal of imparting learners with the necessary knowledge and practical skills to develop a strong foundation in information visualization and to design and develop advanced applications for visual data analysis. It is equivalent of the Information Visualization graduate course taught at NYU Tandon School of Engineering.
This specialization does not require any previous knowledge and consists of a total of four courses – foundations, applied perception, programming with D3.js and advanced visualization techniques. These courses cover the following topics:
- Overview of what visualization is and its scope and goals
- Recognizing type of information in data so that you can find appropriate visual representations
- Fundamental graphs such as bar charts, line charts and scatter plots
- Concept of visual encoding and decoding
- Fundamental concepts of visual perception applied to visualization design
- How to use D3.js to create powerful visualizations for web
- How to create choropleth and symbol maps, node-link diagrams and tree maps
- How to link two or more views through interaction
- How to visualize specific kinds of data (beyond tabular)
- Geographical, temporal and network visualization
- How to create highly interactive multiple-view visualizations
All courses include exercises and practice assignments. There are projects requiring students to design and develop a full interactive visualization using real-world data sets. Also included are three interviews that give students an opportunity to learn with direct experience stories from practitioners and researchers.
Key Highlights
- Opportunity to take a university level graduate course in visualization
- Provides a strong understanding of visual perception and visual encoding to enable learners to design and evaluate innovative visualization methods on their own
- Develop advanced web-based applications for visual data analysis
- Learn what designs are available for a given problem and what are their respective advantages and disadvantages
- Interviews with great researchers and practitioners in the field
- Hands-on projects that enable students to demonstrate mastery of the subject
Duration : 4 months, 3 hours per week
Rating : 4.7
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12. Data Visualization Training and Tutorials (LinkedIn Learning – Lynda)
LinkedIn Learning offers a variety of Data Visualization training classes and tutorials that can help learners stay ahead of the curve. These classes have been created by experts and industry professionals with years of experience and deliver the right set of skills to combine the power of data and graphics. These help learners to develop a solid foundation for how to think about the visual interpretation and communication of data and data insights.
These resources are categorized according to level of difficulty and prerequisites. Beginners can choose introductory classes and then move on to intermediate and more advanced courses. All these can be availed for free as part of 30 day free trial on signup.
Some popular choices of Data Visualization courses on LinkedIn Learning include:
-
Tableau Essential Training
By: Curt Frye
Duration: 4h 30m
In this course you will learn to analyze and display data using Tableau Desktop 2019—and make better, more data-driven decisions for your company. Also learn how to create and manipulate data visualizations—including highlight tables, charts, scatter plots, histograms, maps, and dashboards—and how to share your visualizations. -
Data Dashboards in Power BI
By: Helen Wall
Duration: 4h 52m
This course focuses on the front end of the Power BI application—the dashboard—where users interact with charts and graphs that communicate trends in their data. It teaches how to work with data from open-source websites, create visuals such as heatmaps and sparklines, compare multiple variables with trendlines and violin plots, and build engaging maps. -
Creating Interactive Tableau Dashboards
By: Matt Francis
Duration: 3h 28m
In this course you will learn how to create compelling, informative, and eye-catching dashboards using Tableau. -
Data Visualization: Storytelling
By: Bill Shander
Duration: 1h 37m
This course teaches how to think about, and craft, stories from data by examining many compelling stories in detail. -
Python for Data Visualization
By: Madecraft
Duration: 1h 21m
This course covers how to build accurate, engaging, and easy-to-generate charts and graphs using Python libraries Pandas and Matplotlib. -
Excel 2013: Charts in Depth
By: Dennis Taylor
Duration: 3h 46m
In this course you will learn how to create different kinds of Excel charts, from column, bar, and line charts to exploded pies, and decide which type works best for your data. -
Learning Data Visualization
By: Bill Shander
Duration: 3h 50m
This course covers how to understand your data and your audience, craft the story you need to tell, and determine the best visual model and details to use for that story. -
Data Visualization: A Lesson and Listen Series
By: Bill Shander
Duration: 6h 44m
This course explores key themes in data visualization, data storytelling, and information design. -
Building a Dynamic Heat Map in Excel
By: Chris Dutton
Duration: 1h 34m
This course teaches how to create heat maps in Microsoft Excel with some advanced functions, formatting, and filters. -
R Essential Training: Wrangling and Visualizing Data
By: Barton Poulson
Duration: 4h 18m
This training provides a thorough introduction to R, with detailed instruction for installing and navigating R and RStudio and hands-on examples, from exploratory graphics to neural networks. -
D3.js Essential Training for Data Scientists
By: Emma Saunders
Duration: 4h 38m
This course teaches how to build beautiful and interactive data visualizations (including spatial maps, tree diagrams, stack charts) with D3. -
Data Visualization: Best Practices
By: Amy Balliett
Duration: 1h 15m
This class walks you through the ins and outs of creating accurate and compelling data visualizations with focus on best practices, not tools.
Key Highlights
- Master data visualization tools and techniques
- Learn how to communicate the story that data findings represent
- Discover how to select the right graphic for the right context
- Courses created and led by industry experts
Duration : Self-Paced
Rating : 4.5
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13. Data Visualization on the Browser with Python and Bokeh (Udemy)
Bokeh is a new interactive visualization library for modern web browsers. This Python library is gaining a lot of traction in the field of Data Science for its ability to quickly and easily create versatile graphics like interactive charts, plots, dashboards, and advanced data web applications.
This Data Visualization course on Udemy is a complete guide to mastering Bokeh. It provides step-by-step guidance into using Bokeh to create modern, interactive data visualizations on the browser with Python code only (no JavaScript, HTML or CSS needed). The course starts from the basics of Bokeh with plotting simple datasets to building rich, interactive data visualization web apps that plot data in real time and change based on user interaction. It covers the following topics:
- How to customize your plots by using the styling features that Bokeh offers
- How to add interactivity to your plots starting from popup windows and text boxes to drop down lists and user submitted data
- How to add sliders to your plots to filter data
- How to create dynamic graphs that stream real-time data on the browser
- How to embed Bokeh apps in other web applications
- How to deploy Bokeh apps on web servers
There are several exercises included in the course to help learners check their skills as they progress. They get access to various data samples and are provided with additional examples to cement their Bokeh skills.
Since, learners would be working on a Python library, and the course does not include any lectures on Python programming, it requires them to have a prior knowledge of Python.
Key Highlights
- Most popular Udemy course on Data Visualization with Python Bokeh
- Build advanced data visualization web apps using the Python Bokeh library
- Learn to create widgets that let users interact with your plots
- Learn how to troubleshoot Bokeh apps
- Learn to integrate and visualize data from Pandas DataFrames
- Understand how to integrate your data visualization apps with Flask apps
Duration : 6.5 hours on-demand video
Rating : 4.3
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14. Data Visualization Courses & Classes (Pluralsight)
Pluralsight has a range of Data Visualization courses in its catalogue for all skill levels. Right from mastering data visualization with R to using Python or Tableau or D3.js library for visually representing data, one can find courses for learning various tools and methods used in data visualization and analysis.
While some of these courses are targeted at developers, other take the approach of building stories and narrations around data and hence very useful for developing skills in business communications with data. Here are a few of most popular classes that learners can take:
- D3.js Data Visualization Fundamentals
By: Ben Sullins
Duration: 4h 34m
This course by Ben Sullins with a rating of 4.8 teaches how to use D3.js (specifically version 3) to make stunning data visualizations. Apart from covering theory and core concepts, it includes several functional examples of building data visualizations and business dashboards that learners a hands-on experience. - Mastering Data Visualization with R
By: Matthew Renze
Duration: 1h 43m
This course teaches how to create advanced visualizations with R. Itcovers data visualizations that involve spatial data, hierarchical data, graph and network data, and textual data; animated data visualizations; and web-based interactive data visualizations using a framework called Shiny. - Data Visualization for Developers
By: Dan Appleman
Duration: 1h 54m
This course created by Dan Appleman introduces developers to every aspect of Data Visualization from from story, to numbers, to architecture, to code. It covers the fundamentals of data visualization that every developer needs to know regardless of architecture, platform, tools, or language. - Data Visualization Using Tableau Public
By: Robert Spent
Duration: 1h 48m
This course is a highly rated course that provides a hands-on introduction to using Tableau Public to easily create data visualizations and informative infographic dashboards using Tableau Public.
Key Highlights
- Learn most sought after Data Visualization skills to advance your career
- Covers Data Visualization using Tableau, Python, R and D3.js
- Content created by experts with years of experience
- Flexible online learning from the comfort of your own home
Duration : Self-Paced
Rating : 4.5
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15. Learn Data Visualization with Python (Codecademy)
This Data Visualization course in Python, available on Codecademy, teaches how to present data graphically with Python by making use of Matplotlib and Seaborn libraries. It requires participants to have basic knowledge of Python programming including how to write functions, use lists and loops, and call methods on objects.
The course comprises of two modules:
- Introduction to Matplotlib – Matplotlib is the most popular graphing tool in Python. Here learners are taught to create graphs and charts using features of Matplotlib. It covers the following topics:
- How to create line graphs
- How to create bar charts
- How to create pie charts
- How to add error bars to graphs
- How to add labels and styling to graphs
- Introduction to Seaborn – Seaborn is an add-on to Matplotlib. In this module learners explore the various features of Seaborn and use it to create bar charts for statistical analysis. Specifically, they learn the following:
- Distributions in Seaborn
- How to style graphs more professionally
- How to create sleeker graphics
- How to choose color schemes for your graphs
Learners also work on two portfolio projects throughout the course that they can use to showcase their skills to potential employers.
Key Highlights
Duration : 6 hours
Rating : 4.4
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