Our mission is to cultivate the ability to turn raw, imperfect data into honest insight — to curate with rigour, visualize with judgement, and communicate what the data does and does not say, clearly and responsibly, across science, industry, and society.
Data Curation and Visualization is a rigorous study of how raw, imperfect data is transformed into reliable evidence and communicated with clarity. The course delves into the acquisition, cleaning, and integration of real-world datasets, including data lifecycle management and governance, handling of missing values and outliers, wrangling and multi-modal integration, the grammar of graphics, statistical and multivariate visualization, time-series, geographical and text data, and interactive dashboards built with Python and Tableau. It challenges participants to curate data with discipline while critically examining what a visualization reveals, what it conceals, and how honestly it represents the underlying data.
Lectures
Projects
End Semester
Laboratories
| # | Topic | |
|---|---|---|
| 1 | Monday (Laboratory) | 14:00 - 17:10 |
| 2 | Thursday | 15:00 - 16:40 |
| # | Assessment | Marks | Topics |
|---|---|---|---|
| 1 | Test 1 | 15 | Up to Topics Covered on 3rd September 2026 |
| 2 | Test 2 | 15 | Up to Topics Covered on 8th October 2026 |
| 3 | Projects | 30 | 10 Projects |
| 3 | End Semester | 40 | End Semester (Theory + Practical) |
Associate Professor