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Durham University

Postgraduate Module Handbook 2021/2022

Module Description

Please ensure you check the module availability box for each module outline, as not all modules will run in each academic year. Each module description relates to the year indicated in the module availability box. Please be aware that modules may change from year to year, and may be amended to take account of, for example: changing staff expertise, disciplinary developments, the requirements of external bodies and partners, and student feedback.

Department: Computer Science

COMP42115: Natural Language Analysis

Type Tied Level 4 Credits 15 Availability Available in 2021/22
Tied to G5K709 Business Analytics

Prerequisites

  • None

Corequisites

  • None

Excluded Combination of Modules

  • None

Aims

  • To introduce students to cutting-edge techniques for automated analysis of textual data and their applications

Content

  • Preparation of textual data for machine learning
  • Advanced machine learning techniques for natural language analysis
  • Application of natural language analysis techniques within business analytics e.g. sentiment analysis, social media analysis

Learning Outcomes

Subject-specific Knowledge:
  • Upon successful completion of the module, the students will:
  • Have a critical appreciation of how natural language texts can be effectively represented for machine learning
  • Have an advanced understanding of automated natural language analysis through machine learning
  • Understand how natural language analysis can be applied effectively within business analytics
Subject-specific Skills:
  • Upon successful completion of the module, the students will:
  • Be able to prepare natural language texts for machine learning
  • Be able to train a machine learning application based on real textual data
Key Skills:
  • Effective written communication
  • Planning, organising and time-management
  • Problem solving and analysis
  • Reflecting and synthesising from experience

Modes of Teaching, Learning and Assessment and how these contribute to the learning outcomes of the module

  • Learning outcomes are met through classroom-based workshops, supported by online resources. The workshops consist of a combination of taught input, group work, case studies, discussion and computing labs. Online resources provide preparatory material for the workshops – typically consisting of directed reading and video content.
  • The summative assessment is an individual written assignment based on the development of a program to analyse a real natural language data set. This is designed to test students’ skills in problem identification, their theoretical understanding, and their ability to analyse the situation in order to categorise the potential solutions.

Teaching Methods and Learning Hours

Activity Number Frequency Duration Total/Hours
Lectures 9 1 a week 2 hours 18
Computer Workshops (max 30 students) 4 1 every two weeks 2 hours 8
Preparation and reading 124
Total 150

Summative Assessment

Component: Written Assignment Component Weighting: 100%
Element Length / duration Element Weighting Resit Opportunity
Individual written assignment based on the development of a program 1500 words 100%

Formative Assessment:

A range of formative assessment methods will be used, including case study based exercises, group presentations and group discussions, simulation exercises and business games designed to prepare students for the summative business report. Oral and written feedback will be provided on an individual and/or group basis as appropriate.


Attendance at all activities marked with this symbol will be monitored. Students who fail to attend these activities, or to complete the summative or formative assessment specified above, will be subject to the procedures defined in the University's General Regulation V, and may be required to leave the University


    If you have a query about a specific module or degree programme, please contact the appropriate department. For programmes in the Business School please see the Learning & Teaching Contact List.

    If you have a question about Durham's modular degree programmes, please visit our User Guide. If you have a question about modular programmes that is not covered by the User Guide, or a query about the Postgraduate Module Handbook, please contact us using the Comments and Questions form below.