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Curricular information is subject to change
On successful completion of this module the learner will be able to:
- Understand the typical recommender system architecture and recommendation tasks.
- Understand core algorithms driving common recommender systems including the pros and cons of each.
- Learn about different approaches to evaluating recommender systems, using a variety of metrics and methodologies.
- Learn about more contemporary recommender systems research covering a variety of more advanced topics.
|Student Effort Type||Hours|
|Autonomous Student Learning||
Proficiency in the Java Programming Language is required. There is a significant software engineering effort required and so students must be comfortable and proficient in developing complex programs using advanced tools and techniques.
|Description||Timing||Component Scale||% of Final Grade|
|Continuous Assessment: In-class test||Throughout the Trimester||n/a||Alternative linear conversion grade scale 40%||No||
|Continuous Assessment: Practical projects||Throughout the Trimester||n/a||Alternative linear conversion grade scale 40%||No||
|Continuous Assessment: Practical report||Throughout the Trimester||n/a||Graded||No||
|Resit In||Terminal Exam|
• Feedback individually to students, post-assessment
• Group/class feedback, post-assessment
Post-assessment, feedback will be provided to students in class. Individual feedback is also available to students. During practical sessions, a teaching assistant and demonstrators will be available to provide assistance and feedback to students on their work.
|Practical||Offering 1||Week(s) - 20, 21, 22, 23, 24, 25, 26, 29, 30, 31, 32, 33||Thurs 10:00 - 11:50|
|Lecture||Offering 1||Week(s) - 20, 21, 22, 23, 24, 25, 26, 29, 30, 31, 32, 33||Wed 14:00 - 15:50|