Singapore University of Social Sciences

Web Informatics Programming

Web Informatics Programming (ICT341)

Applications Open: 01 October 2020

Applications Close: 30 November 2020

Next Available Intake: January 2021

Course Types: Modular Undergraduate Course

Language: English

Duration: 6 months

Fees: To be confirmed

Area of Interest: Science & Technology

Schemes: Lifelong Learning Credit (L2C)

Funding: To be confirmed

School/Department: School of Science & Technology


Synopsis

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 throughan 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 January

Topics

  • The importance of Web content analysis
  • Varieties of Web content, including social media posts and system logs
  • Data Pipeline for processing Web content
  • Survey on implementations and systems of Data Pipeline
  • Challenges in data collection
  • Approaches to collect varieties of Web content
  • Issues with structured and unstructured data
  • Methods to index web content
  • Factors in Web content analysis and visualization
  • Systems for analyzing and visualizing web content for Web intelligence
  • Case study of Web content analysis in the business domain
  • Case study of Web content analysis in the system administration domain

Learning Outcome

  • Apply Web and data programming
  • Discuss the challenges in Web content analysis
  • Construct the data pipeline for Web content analysis
  • Propose and apply an integrated solution consisting of Web and data programming
  • Formulate strategies to collect, index and analyze Web content
  • Implement Web content analysis platform for business and operational requirements
  • Set Up a working Web content analysis solution in a case study
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