Singapore University of Social Sciences

Web Informatics Programming

Web Informatics Programming (ICT341)

Applications Open: 01 October 2023

Applications Close: 15 November 2023

Next Available Intake: January 2024

Course Types: Modular Undergraduate Course

Language: English

Duration: 6 months

Fees: $1529.14 View More Details on Fees

Area of Interest: Science and Technology

Schemes: Alumni Continuing Education (ACE)

Funding: To be confirmed

School/Department: School of Science and Technology


ICT341 Web Informatics Programming introduces students to the challenges and importance of Web content analysis for business and operational intelligence. Both tasks require the development of a pipeline that collects, indexes, searches, analyzes and visualizes data based on web content and logs. Challenges and issues facing web content structure, collection and processing will be explained. Students will be introduced to the tools, and exercise them, to resolve the challenges and issues. Based on these, students will apply what they learnt in Web and data programming through an integrated system that supports systematic interaction with data for various decision-making tasks. Students will also be presented with cases in different domains to exercise the understanding and skills in Web informatics programming.

Level: 3
Credit Units: 5
Presentation Pattern: EVERY JAN


  • Overview of Log Data and Log Analysis.
  • Introduction to Elastic Stack.
  • Core Concepts of Elasticsearch.
  • Data Operations in Elasticsearch.
  • Data Ingestion.
  • Log Data Processing.
  • Aggregation and Analytics of Data.
  • Kibana UI and Visualization.
  • Running Elastic as Managed Service.
  • Operating and Managing Elasticsearch.
  • Monitoring an IoT Infrastructure.
  • Performing Web Content Analysis with Elastic.

Learning Outcome

  • Apply web and perform data analysis.
  • Discuss the challenges in Web content analysis and Operational Intelligence.
  • Construct the data pipeline for Web content and machine data analysis.
  • Explain and apply an integrated solution for web and data programming.
  • Formulate strategies to collect, index and analyze Web content and machine data.
  • Implement Web content and log analytics platform for business and operational requirements.
  • Demonstrate a working Web content and log analytics solution in case studies.
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