The importance of data visualization has become apparent in the current era of ‘big data’ that we live in. Effectively visualizing data can lead to recognizing key information quicker and demonstrating impact more effectively.

This four-week online certificate course will focus on building skills and strategies to better visualize and analyze data using a variety of tech tools. It will feature live interactive guest expert presentations with leading M&E practitioners, software developers, and data scientists. It will also include a unique hands-on learning environment with animated videos, technology demos, practical activities, networking events, immersive simulations and more.

Effective data visualization requires both critical thinking skills and technical skills. During this course, we’ll walk you through the step-by-step design process, which encompasses both skillsets.

You’ll learn:

What data visualization is and why our brains respond so well to graphics;
Which up-and-coming trends in the data presentation field and in software development worth paying attention to;
How to design charts that fit your unique stakeholders’ information needs and interests;
Which dissemination format is best for your project–like static graphs within reports, handouts, presentations, or infographics, or interactive graphs within dashboards, websites, animated videos, and GIFs;
Chart choosing tips, like which layouts are best for showcasing time series data, part-to-whole relationships, geographic patterns, or nested data;
Strategies for displaying qualitative and text-based data, like sentiment analysis, color-coding, timelines, calendars, and diagrams;
How to select and use software tools–Excel, R, Tableau, mapping programs, and more–that are best suited to your chart type of choice; and
Which default settings in your computer program need to be adjusted to ensure that your graph follows best practices. For example, you’ll learn how to write titles, subtitles, and annotations that capture your desired takeaway messages; how to highlight your key findings with color; and how to ensure that your visualizations are readable for viewers with colorblindness.

Participants will create data visualizations and get feedback from the course’s experts, facilitators, and fellow participants. For example, during Week 1, you’ll consider your audience’s information needs, the dissemination format for your visualization, what types of data wrangling techniques are needed to get your dataset ready to visualize, and key data responsibility issues. During Week 2, you’ll learn to select the best chart types for your dataset–beyond the overused pie chart and bar chart–and you’ll begin prototyping your visualization. During Week 3, we’ll dive even heavier into tools, and you’ll hear from experts about Tableau, R, and more. During Week 4, you’ll continue editing your visualization to ensure that it follows best practices in alignment, color, text, and more.

Your viewers will understand your data at a glance and retain information for the long run. We hope to see you online in November!

For a more detailed syllabus, please click here.

TC311: Technology for Data Visualization and Analysis