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Module Catalogue

WM275-15 Machine Intelligence

Department
WMG
Level
Undergraduate Level 2
Module leader
Manoj Babu
Credit value
15
Module duration
14 weeks
Assessment
60% coursework, 40% exam
Study locations
  • University of Warwick main campus, Coventry Primary
  • Distance or Online Delivery

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Introductory description

Machine intelligence is revolutionizing industries by helping machines to perform complex tasks that are difficult. It is principally a way of training computers to learn, predict and perceive the future. This module will introduce concepts and methods used for implementing intelligent agents. It will cover the fundamental concepts of machine intelligence including problem solving through machine learning. It will also provide a fundamental understanding of libraries in python programming language essential for data analysis.

Module web page

Module aims

This module aims to provide a strong fundamental understanding of Artificial Intelligence and essential software libraries to implement the algorithms.

Outline syllabus

This is an indicative module outline only to give an indication of the sort of topics that may be covered. Actual sessions held may differ.

  1. Introduction to Machine intelligence,
  2. Intelligent Agents,
  3. Problem Solving,
  4. Introductory machine learning algorithms.
  5. Fundamental data analysis skills

Use of software libraries essential to perform the above listed tasks

Learning outcomes

By the end of the module, students should be able to:

  • Critically analyse the behaviour of an intelligent agent and learning algorithms. [ CITP, 2.2.1]
  • Appraise different forms of learning techniques. [ CITP, 2.2.1, 2.1.9 ]
  • Devise and determine the use of appropriate data analysis techniques to obtain insights from data. [CITP 2.1.9, 2.1.12] [AHEP:4, C3]
  • Evaluate and employ software libraries to perform data analysis tasks. [CITP 2.2.1, 2.3.2]

Indicative reading list

View reading list on Talis Aspire

Subject specific skills

This module contributes to the following Knowledge (K) and Skills (s) in the ST0119 occupational standard:
K13: Principles of data analysis for digital and technology solutions.
K5: A range of digital technology solution development techniques and tools, ( through the use of Python programming language and libraries associated with data analysis.)
S11: Determine and use appropriate data analysis techniques. (This module specifically focuses on the fundamentals of Diagnostic or Predictive Analysis to assess a digital and technology solutions.)

Transferable skills

Technology literacy;
Critical thinking;
Self-learning;
Python programming.

Study time

Type Required
Lectures 10 sessions of 1 hour (7%)
Seminars 5 sessions of 1 hour (3%)
Practical classes 5 sessions of 1 hour (3%)
Online learning (scheduled sessions) 10 sessions of 1 hour (7%)
Online learning (independent) 10 sessions of 1 hour (7%)
Private study 50 hours (33%)
Assessment 60 hours (40%)
Total 150 hours

Private study description

  • Online forum for discussing queries with course peers and tutor.
  • Exploring design of agents for various applications.
  • Practice python programming

Costs

No further costs have been identified for this module.

You must pass all assessment components to pass the module.

Assessment group D
Weighting Study time Eligible for self-certification
Assessment component
Post Module Assignment 60% 36 hours Yes (extension)

A project where the apprentice designs an intelligent agent or implements machine learning algorithms for one of the use cases defined. The project will include programming and written components.
Reassessment component is the same
Assessment component
Assessment of Fundamentals 40% 24 hours No

A locally timetabled exam administered in-person using QMP to test the understanding of fundamentals of agents, machine learning algorithms and data analysis practices
Reassessment component is the same
Feedback on assessment

Feedback will be given as appropriate to the assessment type:
– verbal formative feedback on lab activities.
– written summative feedback on module assessments.

Past exam papers for WM275

Courses

This module is Core for:

  • Year 3 of UWMS-H65E Undergraduate Digital and Technology Solutions (Cyber)
  • Year 3 of DWMS-H655 Undergraduate Digital and Technology Solutions (Cyber) (Degree Apprenticeship)
  • Year 3 of UWMS-H65B Undergraduate Digital and Technology Solutions (Data Analytics)
  • DWMS-H652 Undergraduate Digital and Technology Solutions (Data Analytics) (Degree Apprenticeship)
    • Year 3 of H652 Digital and Technology Solutions (Data Analytics) (Degree Apprenticeship)
    • Year 4 of H652 Digital and Technology Solutions (Data Analytics) (Degree Apprenticeship)
  • Year 3 of UWMS-H65C Undergraduate Digital and Technology Solutions (Network Engineering)
  • DWMS-H653 Undergraduate Digital and Technology Solutions (Network Engineering) (Degree Apprenticeship)
    • Year 3 of H653 Digital and Technology Solutions (Network Engineering) (Degree Apprenticeship)
    • Year 4 of H653 Digital and Technology Solutions (Network Engineering) (Degree Apprenticeship)
  • Year 3 of UWMS-H65D Undergraduate Digital and Technology Solutions (Software Engineering)
  • DWMS-H654 Undergraduate Digital and Technology Solutions (Software Engineering) (Degree Apprenticeship)
    • Year 3 of H654 Digital and Technology Solutions (Software Engineering) (Degree Apprenticeship)
    • Year 4 of H654 Digital and Technology Solutions (Software Engineering) (Degree Apprenticeship)