Core Module Information
Module title: Artificial Intelligence

SCQF level: 09:
SCQF credit value: 20.00
ECTS credit value: 10

Module code: SET09822
Module leader: Ben Paechter
School School of Computing
Subject area group: Software Engineering

Module Code: SET08122
Examples of Equivalent Learning Industry implementation of equivalent algorithms and data structures. Learning involving programming of non-trivial algorithms and data structures.

Description of module content:

The module is partly based on the first three sections of “Artificial Intelligence: A Modern Approach” (3rd edition) by Russell
and Norvig. The indicative content from the book is as follows:
Introduction: What is AI? History of AI and the state of the art.
Agents : An introduction to agents, their behaviors and structure
Searching: Problem solving by searching, heuristics, local search and optimisation and adversarial search
Constraint satisfaction problems: defining and solving CSPs
Logic: Propositional logic, first-order logic, knowledge representation
In addition to this the module will feature introductions to other AI techniques including neural networks, machine learning and nature inspired methods.

Learning Outcomes for module:

LO1: Critically reflect on how AI concepts can underpin problem solving tasks
LO2: Apply the fundamental concepts and origins of artificial intelligence to solve example problems
LO3: Choose, compare and implement AI based solutions to problem solving tasks making use of appropriate software tools and libraries.
LO4: Solve example problems using AI techniques
LO5: Evaluate the effectiveness and appropriateness of specific AI techniques for specific applications

Full Details of Teaching and Assessment
2020/1, Trimester 1, ONLINE,
Occurrence: 001
Primary mode of delivery: ONLINE
Location of delivery: WORLDWIDE
Member of staff responsible for delivering module: Ben Paechter
Module Organiser:

Learning, Teaching and Assessment (LTA) Approach:
You will be supported by the Global Online team who will provide general overall support, and by the module teams who will provide module-specific online material and discussion forums using a variety of communication technologies such as Moodle and Skype (LO 1, LO2, LO3, LO4, LO5).

You will be encouraged to develop your learning through peer and tutor interaction through electronic communication. Self-study readings, supported by online discussions forum hosted through the VLE, will develop skills as independent learners (LO 1, LO2, LO3, LO4, LO5).

Material for practical exercises will be made available online with a support forum.

In addition to this, online students are provided with online support in the form of:
• Dedicated online administrators who will keep track of student progress and will help you if you are having any problems.
• A dedicated interactive database of frequently asked questions specific to the online learning environment.
• A regular ‘virtual office hour’ will be held where module staff will be available for contact with you.

Formative Assessment:
Formative feedback on practical work will be provided through the online discussion forum and ‘virtual office hour’. Reflective Exercises will enable you to apply theory to practice – this is not assessed, but it will support your personal and professional development.

Summative Assessment:
Summative assessment will be in the form of four parts totalling 100% of the final mark: There will be a series of end-of-section online quizzes that will provide formative assessment throughout the course. These quizzes form 10% of the overall assessment (covering LOs 1 - 5). Two artificial intelligence tasks and associated lab reports will each be worth 30% of the final mark (covering LOs 1 - 5). The assignments will be submitted in weeks 10 and 13. At the end of the module an online class test (covering LOs 1 - 5) will be undertaken for the remaining 30% of the final mark.

Student Activity (Notional Equivalent Study Hours (NESH))
Mode of activityLearning & Teaching ActivityNESH (Study Hours)
Online Guided independent study 188
Online Tutorial 12
Total Study Hours200
Expected Total Study Hours for Module200

Type of Assessment Weighting % LOs covered Week due Length in Hours/Words
Class Test 10 1,2,3,4,5 12 HOURS= 02.30
Class Test 30 1,2,3,4,5 13 HOURS= 02.00
Laboratory report 30 1,2,3,4,5 10
Laboratory report 30 1,2,3,4,5 13
Component 1 subtotal: 100
Component 2 subtotal: 0
Module subtotal: 100

Indicative References and Reading List - URL:
Contact your module leader