IITM BS Data Visualization Design (BSCS4001): Syllabus and Tips

Data Visualization Design (BSCS4001) is a 4 credit level 4 elective in the IITM BS in Data Science. It teaches you how people read charts and maps, how to choose the right visual form for your data, and how to tell a story with it. The course page lists no prerequisite. Like every degree level course, you can take it only after you enter the degree level.

Data Visualization Design at a glance

The instructor is Prof. Venkatesh Rajamanickam of the IDC School of Design, IIT Bombay. The course page calls it a "Degree Level Course" of type "Elective". The handbook table lists it as "L4_DEGREE" with the tag "BD", 4 credits and no prerequisite. The two sources agree.

The course page says 12 weeks of coursework but lists topics only for weeks 1 to 10. The last listed week includes project presentations. The assessment line on the same page does not mention a project. Check the course portal for how the presentations are graded in your term.

What you learn in Data Visualization Design

• Weeks 1 and 2: how people see. A short history of information visualisation. Then how vision, perception and thinking decide what a viewer notices in a chart and what they miss.
• Weeks 3 and 4: data first. Principles and models for describing data, and how to use visuals to analyse data and find insights.
• Weeks 5 and 6: maps. Showing data on geography, and how to simplify a map so that it carries the message.
• Weeks 7 and 8: encoding and design. Choosing how each number becomes a position, length, colour or shape. Then putting these choices together into a full visual design.
• Weeks 9 and 10: stories. Building a data story from charts, maps and diagrams, followed by project presentations and a course summary.

The page lists no textbook.

How it is assessed

The course page lists weekly online assignments, 2 in-person invigilated quizzes and 1 in-person invigilated end term exam. It does not list an OPPE.

Where it counts

It is a level 4 course tagged BD. The handbook does not spell out BD, but going by the stream rules it appears to mean the data science stream. If so, it can be one of the two level 4 or higher data science courses the BS degree level needs. Confirm this with support before you count on it. It is not part of any minor.

The handbook table (updated 18 March 2026) marks it as offered in May 2026 and January 2027, but not in September 2026. Offering also depends on how many students register.

Who finds it hard and how to prepare

This course is closer to design than to maths. There is rarely one right answer. A chart is good or bad depending on the question and the reader. If you are used to exact answers, that can feel uncomfortable at first.

• Keep a chart diary. Save charts you see in news sites and reports. Each week, write two lines on what works and what misleads, using that week's ideas.
• Remake one bad chart a week. Pick a cluttered chart and redraw it with any tool you know, such as Python plotting libraries or a spreadsheet. Compare the two versions.
• Start the project idea early. Since the last week has project presentations, choose a dataset you care about by the middle of the term.
• Practise explaining choices. For every chart you make, write one sentence on why you chose that chart type and those colours.

What to take before and after

The visual storytelling module of Tools in Data Science (BSSE2002) is a good warm-up. For other level 4 data science options, see the DS degree level electives list. If you like the user side of design, Design Thinking for Data-Driven App Development (BSMS4002) is another option.

Common questions

Is Data Visualization Design a coding course?

The page's goals include using visualisation tools and building visualisations, but it does not name any tool or programming language. You can practise with whatever you already know.

Can I count this course towards my BSc?

Yes. The BSc level has 8 elective credits, and the handbook's fee table shows level 4 credits as one way to fill them.

Is this the same as the visualisation part of Tools in Data Science?

No. Tools in Data Science (BSSE2002) is a 3 credit diploma course with one module on visual stories. BSCS4001 is a full 4 credit course on how visualisation works and how to design it.

Do I need an art or design background?

No prerequisite is listed. The course starts from how people perceive visuals and builds up from there.