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Introduction
This course will benefit individuals by upgrading their technical knowledge and skills in the area of visual analytics, which can be used in Information and communications technology (ICT) sectors to aid in analyzing any kind of data.
This course aims to get learners to know the following:
• The concept of information visualization, with emphasis on human visual perception and media components (e.g., word, number, color, shape, texture, image, and graph), and the fundamental issues regarding the use of visualization techniques.
• Visualization design principles in various situations and contexts from the perspective of cognitive psychology and human visual perception.
• Coding skills and application awareness in interactive media and visual information processing.
This course is part of:
- Graduate Certificate in Information Management and Analytics
- FlexiMasters
in Information Management and Analytics
At the end of this course, learners should be able to:
• Define each step of the information visualization pipeline including data selection, representation, presentation, and interaction.
• Synthesize best design practices for information visualization and thoughtfully critique existing visualizations.
• Perform basic coding using software tools to apply visualization concepts on small practical visualization projects.
Learners will learn the following topics in the course:
• Theory of information visualization, where students learn about visual communication; emotion and cognition, cognitive science of decision making; media effect; interactivity; visual processing, and storytelling.
• Fundamental coding concepts in information visualization, where students learn how to use various software tools, such as Pandas, Matplotlib, D3, and Power BI, whist applying the design principles.
Working adults from the industry with some experience in information technology and related fields would better appreciate the course.
Good communication skills (written and spoken English) are recommended as some assessment components may require presentations and report writing.
Standard Course Fee: S$4,860
SSG Funding Support | Course fee payable after SSG funding, if eligible under various schemes | ||
Fee BEFORE funding & GST | Fee AFTER funding & 8% GST | ||
Singapore Citizens (SCs) and Permanent Residents (PRs) (Up to 70% funding) | s$4,500.00 | S$1458.00 | |
Enhanced Training Support for SMEs (ETSS) | S$558.00 | ||
SCs aged ≥ 40 years old | |||
• NTU/NIE alumni may utilise their $1,600 Alumni Course Credits. Click here for more information.
| COURSE TITLE | ACADEMIC UNIT |
| CET180 Information Discovery in the Age of the Internet | 3 |
| CET181 Information Retrieval Systems and Techniques | 3 |
| CET182 Introduction to Data Mining | 3 |
| CET184 Python for Data Analytics | 3 |
| CET185 Knowledge Management Tools | 3 |
Listed courses are:
- Credit-bearing and stackable to Graduate Certificate in Information Management and Analytics (total 9AUs) and FlexiMasters in Information Management and Analytics (total 15AUs).
- SkillsFuture Credit approved.
