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COMP6125

Course Title: 
Knowledge Discovery and Data Analytics II
Credits: 
4
Core Course: 
yes
Course Aims: 

This course will introduce students to various techniques to analyze unstructured data. There are two components of this course; the first focusses on mechanism of representing knowledge and second on algorithms and techniques that can be used on non-traditional data sources to perform the analysis. The course will equip students to identify and apply appropriate techniques while dealing with unstructured data.

Learning Outcomes: 

On successful completion of the course, students should be able to:

  1. 1)  Develop and implement an ontology

  2. 2)  Apply techniques for reasoning under uncertainty

  3. 3)  Apply the algorithms for the different techniques that work on unstructured data sources like human

    experts, documents and web forums

  4. 4)  Conceptualize and implement an analytics solution to a practical problem which requires

    unstructured data.

Syllabus: 
  1. Introduction, basic concepts and motivation

  2. Knowledge Representation-Production rules and Ontology

  3. Reasoning under uncertainty

  4. Natural Language Processing

  5. Text Mining

  6. Sentiment Analysis

  7. Web Mining

  8. Processing large amounts of data

Course Assessment: 

The coursework will consist of two (2) assignments and a project. The assignments expose students to different types of practical exercises and the project exposes students to applying their knowledge to a business problem that requires data mining and their presentation skills.
Final Written Examination (2 hours) -50%

Coursework -50%

  •   Paper Review, Discussion and Presentation – Assignment 1(20%)

  •   Analytics - Assignment 2 (15%)

  •   Project (15%)

    Students will be required to pass both the coursework and the final examination to pass the course.

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