The top 20 Visualization courses you need to take

1. Visual Design (Part Time)

Gain the vocabulary and tools to tackle diverse design challenges on the job. Kickstart your portfolio and create beautiful, responsive designs for the web. This course is offered in person and live online, in a remote classroom setting...

2. Data Visualization

You will start by building data visualizations and dashboards, considering your audiences to be as effective as possible. Then, you’ll move into drafting presentations using storytelling techniques, visualizations, and animations to provide data-driven recommendations...

3. Data Visualization

Discover how data visualization can communicate insights far more effectively than text or tables. In this course, you’ll learn how to build data visualizations programmatically using Python, and how you can use visualization to both discover and convey trends in your data...

4. Information Visualization

This specialization provides 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.\n\nThe specialization is characterized by two main complementary features: (1) providing a strong understanding of visual perception and the theory of visual encoding to design and evaluate innovative visualization methods; (2) providing the necessary skills to develop advanced web-based applications for visual data analysis.\n\nThe specialization is organized around four courses that cover fundamentals, applied perception, advanced visualization method and interactive visualization.\n\nThe specialization is meant to prepare students to work on complex data science projects that require the development of interactive visual interfaces for data analysis. The courses can also be taken individually to improve relevant skills in visualization. For instance, the course on applied perception provides unique skills to evaluate and design innovative visualization in all sorts of scenarios...

5. Visual Perception

The ultimate goal of a computer vision system is to generate a detailed symbolic description of each image shown. This course focuses on the all-important problem of perception. We first describe the problem of tracking objects in complex scenes. We look at two key challenges in this context. The first is the separation of an image into object and background using a technique called change detection. The second is the tracking of one or more objects in a video. Next, we examine the problem of segmenting an image into meaningful regions. In particular, we take a bottom-up approach where pixels with similar attributes are grouped together to obtain a region. Finally, we tackle the problem of object recognition. We describe two approaches to the problem. The first directly recognize an object and its pose using the appearance of the object. This method is based on the concept of dimension reduction, which is achieved using principal component analysis. The second approach is to use a neural network to solve the recognition problem as one of learning a mapping from the input (image) to the output (object class, object identity, activity, etc.). We describe how a neural network is constructed and how it is trained using the backpropagation algorithm...

6. Learn Visual Basic with Visual Studio

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With this course, you can learn to be a master of the visual basic programming language! Not to be underestimated, visual basic is an entry level to professional level programming language designed and maintained by Microsoft. In this course, you'll become proficient in the basics of both visual basic and the IDE visual studio, with little to no experience with programming assumed. This courseis focused on using console applications to teach the basic principals of programming and visual basic...

7. Data Visualization with Tableau

In 2020 the world will generate 50 times the amount of data as in 2011. And 75 times the number of information sources (IDC, 2011). Being able to use this data provides huge opportunities and to turn these opportunities into reality, people need to use data to solve problems.\n\nThis Specialization, in collaboration with Tableau, is intended for newcomers to data visualization with no prior experience using Tableau. We leverage Tableau's library of resources to demonstrate best practices for data visualization and data storytelling. You will view examples from real world business cases and journalistic examples from leading media companies.\n\nBy the end of this specialization, you will be able to generate powerful reports and dashboards that will help people make decisions and take action based on their business data. You will use Tableau to create high-impact visualizations of common data analyses to help you see and understand your data. You will apply predicative analytics to improve business decision making. The Specialization culminates in a Capstone Project in which you will use sample data to create visualizations, dashboards, and data models to prepare a presentation to the executive leadership of a fictional company...

8. SAS Visual Business Analytics

Using SAS Visual Analytics, you will learn to access and manipulate data, analyze data with a variety of interactive reports and graphics, and design and share dashboards to visualize your data. SAS Visual Analytics is a useful skill in a variety of careers, including business analyst, researcher, statistician, or data scientist.\n\nThe Macquarie Business School at Macquarie University is proud to partner with global analytics leader SAS in offering SAS Certification as part of their Global MBA program. The Global MBA SAS Partnership includes the opportunity for professionals certified through the SAS Certified Specialist: Visual Business Analyst program to gain credit when studying for Macquarie University’s Global MBA through the Generate Insights unit. Find out more about the benefits of the partnership here!...

9. Building Data Visualization Tools

The data science revolution has produced reams of new data from a wide variety of new sources. These new datasets are being used to answer new questions in way never before conceived. Visualization remains one of the most powerful ways draw conclusions from data, but the influx of new data types requires the development of new visualization techniques and building blocks. This course provides you with the skills for creating those new visualization building blocks. We focus on the ggplot2 framework and describe how to use and extend the system to suit the specific needs of your organization or team. Upon completing this course, learners will be able to build the tools needed to visualize a wide variety of data types and will have the fundamentals needed to address new data types as they come about...

10. Data Analysis and Visualization

By the end of this course, learners are provided a high-level overview of data analysis and visualization tools, and are prepared to discuss best practices and develop an ensuing action plan that addresses key discoveries. It begins with common hurdles that obstruct adoption of a data-driven culture before introducing data analysis tools (R software, Minitab, MATLAB, and Python). Deeper examination is spent on statistical process control (SPC), which is a method for studying variation over time. The course also addresses do’s and don’ts of presenting data visually, visualization software (Tableau, Excel, Power BI), and creating a data story. Material features online lectures, videos, demos, project work, readings and discussions. This course is ideal for individuals keen on developing a data-driven mindset that derives powerful insights useful for improving a company’s bottom line. It is helpful if learners have some familiarity with reading reports, gathering and using data, and interpreting visualizations. It is the second course in the Data-Driven Decision Making (DDDM) specialization. To learn more about the specialization, check out a video overview at https://www.youtube.com/watch?v=Oi4mmeSWcVc&list=PLQvThJe-IglyYljMrdqwfsDzk56ncfoLx&index=11...

11. Data Visualization with R

In this course, you will learn the Grammar of Graphics, a system for describing and building graphs, and how the ggplot2 data visualization package for R applies this concept to basic bar charts, histograms, pie charts, scatter plots, line plots, and box plots. You will also learn how to further customize your charts and plots using themes and other techniques. You will then learn how to use another data visualization package for R called Leaflet to create map plots, a unique way to plot data based on geolocation data. Finally, you will be introduced to creating interactive dashboards using the R Shiny package. You will learn how to create and customize Shiny apps, alter the appearance of the apps by adding HTML and image components, and deploy your interactive data apps on the web. You will practice what you learn and build hands-on experience by completing labs in each module and a final project at the end of the course. Watch the videos, work through the labs, and watch your data science skill grow. Good luck! NOTE: This course requires knowledge of working with R and data. If you do not have these skills, it is highly recommended that you first take the Introduction to R Programming for Data Science as well as the Data Analysis with R courses from IBM prior to starting this course. Note: The pre-requisite for this course is basic R programming skills...

12. Data Visualization with Tableau

Dive deep into the compelling world of data visualization with this beginner-friendly course, illuminating the art of transforming data into insightful visuals using Tableau. Arranged in four comprehensive modules, this course outlines a clear learning trajectory, transitioning from foundational concepts to advanced visualization techniques. In the initial module, the focus is on grasping the essentials of Tableau, the cornerstone of effective data visualization. Here, you'll acquaint yourself with Tableau's fundamental tools and features, setting a solid base for your data storytelling journey. The subsequent module propels you into the world of data transformation. Dive deep into Tableau's core functionalities, from understanding the dynamics of Marks Cards and Legends to the significant roles of Green and Blue pills. This phase empowers you to mold raw data into compelling visual stories. Progressing further, the third module introduces you to the vast spectrum of Tableau charts. From basic bar charts to complex visualizations, you'll learn to select the apt visual medium, ensuring your data narratives resonate and captivate. Concluding your journey, the fourth module immerses you in advanced Tableau techniques and dashboard design. By leveraging sophisticated features and crafting interactive dashboards, you'll be able to present your insights with greater impact. By the end of the course, not only will you have a portfolio of compelling data visualizations to showcase, but you'll also possess a profound understanding of data visualization principles and a robust proficiency in Tableau...

13. Overview of Data Visualization

In this project, you will develop an understanding and appreciation for data visualization. You will review the benefits of data visualization as you examine existing examples of data that is displayed in a variety of visual formats. In addition, you will gain some hands-on experience in building your own data visualization examples by aggregating data and generating simple charts in Google Sheets. Note: This course works best for learners who are based in the North America region. We’re currently working on providing the same experience in other regions...

14. Visual Analytics with Tableau

In this third course of the specialization, we’ll drill deeper into the tools Tableau offers in the areas of charting, dates, table calculations and mapping. We’ll explore the best choices for charts, based on the type of data you are using. We’ll look at specific types of charts including scatter plots, Gantt charts, histograms, bullet charts and several others, and we’ll address charting guidelines. We’ll define discrete and continuous dates, and examine when to use each one to explain your data. You’ll learn how to create custom and quick table calculations and how to create parameters. We’ll also introduce mapping and explore how Tableau can use different types of geographic data, how to connect to multiple data sources and how to create custom maps...

15. Create a Standout Visual Résumé with Visual Thinking

Re-think the résumé! Whether you are actually seeking a new job or just need a better way to explain to your mom what it is you do for a living this class will help you come up with fun interesting and impactful charts and visuals that communicate your professional or personal journey. If you have avoided updating your résumé like the rest of us join visual thinker and designer Catherine Madden to learn how to make it a more fun and creative experience. Follow a series of exercises to learn how to break down the traditional résumé into simple charts and visuals consider different types of content that showcase what makes you unique and decide on the appropriate format. This class builds on the foundational visual thinking concepts from Catherines first class on drawing data but will get more specific about execution with three different tools: Hand Drawn Illustrated charts using Adobe Draw...

16. Data Analysis and Visualization Foundations

Deriving insights from data and communicating findings has become an increasingly important part of virtually every profession. This Specialization prepares you for this data-driven transformation by teaching you the core principles of data analysis and visualization and by giving you the tools and hands-on practice to communicate the results of your data discoveries effectively.\n\nYou will be introduced to the modern data ecosystem. You will learn the skills required to successfully start data analysis tasks by becoming familiar with spreadsheets like Excel. You will examine different data sets, load them into the spreadsheet, and employ techniques like summarization, sorting, filtering, & creating pivot tables.\n\nCreating stunning visualizations is a critical part of communicating your data analysis results. You will use Excel spreadsheets to create the many different types of data visualizations such as line plots, bar charts, pie charts. You will also create advanced visualizations such as treemaps, scatter charts & map charts. You will then build interactive dashboards.\n\nThis Specialization is designed for learners interested in starting a career in the field of Data or Business Analytics, as well as those in other professions, who need basic data analysis and visualization skills to supplement their primary job tasks.\n\nThis program is ACE® recommended—when you complete, you can earn up to 9 college credits...

17. Data Visualization & Dashboarding with R

This Specialization is intended for learners seeking to develop the ability to visualize data using R. Through five courses, you will use R to create static and interactive data visualizations and publish them on the web, which will you prepare you to provide insight to many types of audiences...

18. The Art of Visual Storytelling

The ability to shoot and edit video is rapidly becoming a sought after skill. Many businesses seek people who can bring more than just a single skill to the table, and video creation can be a key one. In this hands-on specialization, you will do more than just understand the concept of creating a professional video, you will actually produce one for your portfolio!\n\nComponent courses are broken down into the Stages of Video Production: Pre-Production, Production, and Post-Production. In Pre-Production, you will learn how to generate ideas, write proposals, scripts, and draw storyboards. In Production, lessons include basic camera functions, composition, depth of field, getting the exposure right, and shooting for the edit. You will also learn how to light and frame an on-camera interview and how to record professional audio. In Post-Production, you learn editing basics using non-linear editing programs like Adobe Premiere, how to create aesthetic graphics, and how to avoid copyright issues.\n\nAmong those who would benefit from this course are teachers producing video content for their students, real estate agents using video to showcase homes for sale, small-business owners/entrepreneurs generating video for a website, non-profit staff creating video for fund-raising efforts, and amateur vloggers looking to produce more professional content...

19. Advanced Data Visualization with R

Data visualization is a critical skill for anyone that routinely using quantitative data in his or her work - which is to say that data visualization is a tool that almost every worker needs today. One of the critical tools for data visualization today is the R statistical programming language. Especially in conjunction with the tidyverse software packages, R has become an extremely powerful and flexible platform for making figures, tables, and reproducible reports. However, R can be intimidating for first time users, and there are so many resources online that it can be difficult to sort through without guidance. This course is the third in the Specialization "Data Visualization and Dashboarding in R." Learners come into this course with a foundation using R to make many basic kinds of visualization, primarily with the ggplot2 package. Accordingly, this course focuses on expanding the learners' inventory of data visualization options. Drawing on additional packages to supplement ggplot2, learners will made more variants of traditional figures, as well as venture into spatial data. The course ends make interactive and animated figures. To fill that need, this course is intended for learners who have little or no experience with R but who are looking for an introduction to this tool. By the end of this course, students will be able to import data into R, manipulate that data using tools from the popular tidyverse package, and make simple reports using R Markdown. The course is designed for students with good basic computing skills, but limited if any experience with programming...