Module Details |
The information contained in this module specification was correct at the time of publication but may be subject to change, either during the session because of unforeseen circumstances, or following review of the module at the end of the session. Queries about the module should be directed to the member of staff with responsibility for the module. |
Title | INTELLIGENT SYSTEMS | ||
Code | CKIT533 | ||
Coordinator |
Dr F Grasso Computer Science Floriana@liverpool.ac.uk |
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Year | CATS Level | Semester | CATS Value |
Session 2021-22 | Level 7 FHEQ | Whole Session | 15 |
Aims |
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1 . To provide students with a comprehensive understanding of intelligent systems techniques. 2. To enable students to evaluate modern techniques of artificial intelligence and machine learning for intelligent system projects. 3. To provide students with the knowledge and skills required to develop and deploy expert systems and artificial intelligent tools. |
Learning Outcomes |
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(LO1) An ability to analyse and evaluate intelligent systems techniques. |
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(LO2) A comprehensive understanding of the differences between intelligent system applications and conventional computer applications. |
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(LO3) A critical ability to deploy appropriate software tools and skills for the design and implementation of intelligent systems. |
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(LO4) An in depth understanding of the practical application of the fundamental principles of intelligent systems. |
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(LO5) An ability to analyse intelligent system problems and formulate appropriate solutions. |
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(S1) Communication skills |
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(S2) IT skills |
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(S3) Communication and collaboration online participating in digital networks for learning and research. |
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(S4) Problem solving/critical thinking/creativity |
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(S5) Team (group) working respecting others, co-operating, negotiating / persuading, awareness of interdependence with others |
Syllabus |
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Week 1: Introduction to Intelligent systems: |
Teaching and Learning Strategies |
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Teaching Method 1 - online Learning |
Teaching Schedule |
Lectures | Seminars | Tutorials | Lab Practicals | Fieldwork Placement | Other | TOTAL | |
Study Hours |
60 |
60 | |||||
Timetable (if known) | |||||||
Private Study | 90 | ||||||
TOTAL HOURS | 150 |
Assessment |
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EXAM | Duration | Timing (Semester) |
% of final mark |
Resit/resubmission opportunity |
Penalty for late submission |
Notes |
CONTINUOUS | Duration | Timing (Semester) |
% of final mark |
Resit/resubmission opportunity |
Penalty for late submission |
Notes |
Report: Group Work on Intelligent Systems Application Standard UoL penalty applies for late submission. This is not an anonymous assessment. Assessment Schedule (When) :Week 8 | Two weeks: 1500-2000 | 16 | ||||
Case Study Analysis: Reinforcement Learning Standard UoL penalty applies for late submission. Assessment Schedule (When) :Week 6 | One Week: 750-1000 w | 10 | ||||
Case Study Analysis: Artificial Neural Networks Standard UoL penalty applies for late submission. This is not an anonymous assessment. Assessment Schedule (When) :Week 5 | One Week: 750-1000 w | 10 | ||||
Case Study Analysis: Fuzzy Expert Systems Standard UoL penalty applies for late submission. This is not an anonymous assessment. Assessment Schedule (When) :Week 4 | One Week: 750-1000 w | 10 | ||||
Individual presentation: Expert systems Standard UoL penalty applies for late submission. This is not an anonymous assessment. Assessment Schedule (When) :Week 3 | One week: 20 Minutes | 7 | ||||
Individual presentation: Comparison of intelligent and conventional systems Standard UoL penalty applies for late submission. This is not an anonymous assessment. Assessment Schedule (When) :Week | One week: 20 minutes | 7 | ||||
Moot/debate: 8 discussion questions Standard UoL penalty applies for late submission. This is not an anonymous assessment. Assessment Schedule (When) :Whole session | Weekly Discussion Qu | 40 |
Recommended Texts |
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Reading lists are managed at readinglists.liverpool.ac.uk. Click here to access the reading lists for this module. |