Undergraduate Course: AI Large Practical (INFR09018)
|School||School of Informatics
||College||College of Science and Engineering
||Availability||Available to all students
|Credit level (Normal year taken)||SCQF Level 9 (Year 3 Undergraduate)
|Home subject area||Informatics
||Other subject area||None
||Taught in Gaelic?||No
|Course description||The AI Large Practical gives students the experience of building a moderately large system, exemplifying a proposed solution to some AI problem. It also gives experience in running experiments, and reporting and analysing results.
Students will have experience in:
- Designing a well structured system
- Implementing such a system
- Designing and running experiments
- Reporting and analysing results
Information for Visiting Students
|Displayed in Visiting Students Prospectus?||No
Course Delivery Information
|Delivery period: 2013/14 Semester 1, Not available to visiting students (SS1)
||Learn enabled: No
|Course Start Date
|Breakdown of Learning and Teaching activities (Further Info)
Lecture Hours 10,
Supervised Practical/Workshop/Studio Hours 5,
Feedback/Feedforward Hours 10,
Programme Level Learning and Teaching Hours 2,
Directed Learning and Independent Learning Hours
|Breakdown of Assessment Methods (Further Info)
|No Exam Information
Summary of Intended Learning Outcomes
|Students should learn how to:
- Design and implement a complex system.
- Consider alternative designs, both for internal properties, and as ways of tackling a given problem.
- Read technical papers, and explain their relevance to the chosen approach.
- Design and carry out appropriate experiments, and explain the methodology involved.
- Write a scholarly report, suitably structured and with supporting evidence.
|Written Examination 0|
Assessed Assignments 100
Oral Presentations 0
No formal written examination; the assessment is based on practical work and a written report submitted at the end of the project period.
||- Gentle introduction to the issues and requirements of the more demanding fourth-year project.
- Experience of reading published papers and identifying their essential content.
- Exercise of reporting on modest pieces of scientific work: students have to explain what they did, and why, and what conclusions they reached, and why, and they have to do this clearly and convincingly.
- Experience of writing programs to investigate specific questions: students must write well-structured, well-documented programs because they too are acts of scientific communication.
Relevant QAA Computing Curriculum Sections: Artificial Intelligence
||Not yet available
Tutorial opportunities: 12
Timetable laboratories: 0
Non-timetabled assessed assignments: 52
Private study/Other: 32
|Course organiser||Mr Vijayanand Nagarajan
Tel: (0131 6)51 3440
|Course secretary||Miss Claire Edminson
Tel: (0131 6)51 7607
© Copyright 2013 The University of Edinburgh - 13 January 2014 4:26 am