Program Overview

Course Information

Course Description

The course objective is to enable students to create visualizations of complex data sets and to apply common strategies for understanding the content of media (e.g., text, music, images, etc.).

Course Details

• Course Title: Social data analysis and visualization
• Language of Instruction: English
• ECTS Points: 5
• Course Type: MSc Offered as a single course, Programme specific course (MSc) in Business Analytics, Human-Centered Artificial Intelligence, and Transport and Logistics. Elective course (B Eng) in IT and Economics, Computer Engineering, and Software Technology.
• Schedule: Spring F3A (Tues 8-12)
• Location: Campus Lyngby
• Scope and Form: Lectures, exercises, and final project
• Duration: 13 weeks
• Type of Assessment: Evaluation of exercises/reports
• Grading: Based on an overall evaluation of exercises (50%) and final project report (50%).
• Aid: All aids with access to the internet
• Evaluation: 7-step scale, internal examiner
• Previous Course: 02822
• Not Applicable Together With: 02822/02467
• Academic Prerequisites: 02101/02100. Practical programming experience is recommended (e.g., in Python/Java/JavaScript/C/C++).
• Department: Department of Applied Mathematics and Computer Science

Learning Objectives

A student who has met the objectives of the course will be able to:

• Access and assess types of available online data for data visualization.
• Use state-of-the-art tools to filter, clean, and organize large, complex datasets.
• Apply standard tools from high-level programming languages (e.g., Python, MatLab, R) to evaluate data visualization methods for exploration of single variable data.
• Assess and apply data visualization methods for data exploration of multiple variable data.
• Use visualization techniques to evaluate and identify limitations of summary statistics.
• Use basic principles of displaying visual information to create explanatory visualizations.
• Apply specialized visualization software to build custom visualizations.
• Analyze cases of narrative data visualization to extract the underlying principles used to construct this type of visualization.
• Build a narrative data-visualization.

Content

The course is based on mastering tools for analyzing data sets generated from online social interactions. It is structured around short lectures combined with exercises and a high degree of independent project work.

Last Updated

02 May 2025