Academic Handbook Course Descriptors and Programme Specifications
LDSCI6208 Final Project (Computer or Data Science) Course Descriptor
| Course code | LDSCI6208 | Discipline
US credit Date approved |
Computer & Data Science |
| UK credit | 30 | 8 | |
| FHEQ level | 6 | November 2022 | |
| Core attributes | CPPC
FP |
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| Pre-requisites | This course is only available to students for whom Data Science is their main degree discipline (or for Joint Honours students, one of their two main degree disciplines). | ||
| Co-requisites | None | ||
Course Overview
This course provides students with the opportunity to apply state-of-the-art methods, tools and techniques in computer and data science by managing a software project that solves a substantial, real-world problem. The design and implementation of software artefacts is described and reflected in the dissertation. Project dissertations based solely on literature review or user/market surveys are not acceptable. The course builds upon the variety of material being taught during the programme in earlier courses.
In this course, after an initial group seminar with the course leader, students meet with an assigned supervisor to finalise the subject of their project and discuss and refine the project requirements. Once the project artefact and its accompanying report has been submitted, students defend it with a presentation and demo.
Learning Outcomes
On successful completion of the course, students will be able to:
Knowledge and Understanding
| K1c | Demonstrate a sophisticated understanding of software design principles, tools and techniques when developing software. |
| K2c | Accurately identify, analyse, and interpret software requirements to solve a computing problem; and systematically understand different design stages. |
| K3c | Demonstrate detailed critical engagement with software tools and technologies required to solve a computing problem. |
Subject Specific Skills
| S1c | Familiarity with codes of ethics (e.g. code licencing) and codes of practice (e.g. testing) for software development underpinning the development of high quality, high integrity software systems. — Ability to convey software problems and solutions to both technical and non-technical audiences. |
| S2c | Demonstrate ability to recognise the individual software components required to solve a computing problem, create them or interface with them, and design their interaction. |
| S3c | Demonstrate ability to engage in a peer review process that involves critical review of software and related documentation, coupled with positive advice for improvement and innovation. |
Transferable and Employability Skills
| T1c | Communicate persuasively across audiences and genres, conveying academic materials to both specialist and non-specialist audiences using visual, written, or verbal techniques |
| T2c &T4c | Demonstrate programming skills with a range of up-to-date, well-proven software development tools and libraries. |
| T3c | Display an advanced level of technical proficiency in written English and competence in applying scholarly terminology, so as to be able to apply skills in critical evaluation, analysis and judgement effectively in a diverse range of contexts. |
Teaching and Learning
This course has a dedicated Virtual Learning Environment (VLE) page with a range of resources to orientate the student and provide support for their directed study.
The teaching and learning activities for this course are: 14 scheduled hours.
Indicative example:
- 12 hours of seminars / workshops
- 2 hours of 1:1 or small-group meetings
- Office Hours (up to 4 short meetings)
Faculty hold regular ‘office hours’, which are opportunities for students to drop in or sign up to explore ideas, raise questions, or seek targeted guidance or feedback, individually or in small groups.
Students are to attend and participate in all the scheduled teaching and learning activities for this course and to manage their directed learning and independent study.
Indicative total learning hours for this course: 300
Assessment
Both formative and summative assessment are used as part of this course, with purely formative opportunities typically embedded within interactive teaching sessions, office hours, and/or the VLE.
Summative Assessments
| AE: | Assessment Activity | Weighting
(%) |
Duration | Length
(words) |
| 1 | Presentation | 25 | 15 min. | |
| 2 | Written Assignment | 75 | 7,000 |
Further information about the assessments can be found in the Course Syllabus.
Feedback
Students will receive formative and summative feedback in a variety of ways, written (e.g. marked up on assignments, through email or the VLE) or oral (e.g. as part of interactive teaching sessions or in office hours).
Indicative Reading
The required and recommended reading and any other resources will be agreed based on an initial discussion between the student and the supervisor.
Indicative Topics
Note: Comprehensive and current topics for courses are produced annually in the Course Syllabus or other documentation provided to students; the indicative topics provided below are used as a general guide and part of the approval/modification process only.
- Problem statement definition
- Software design and implementation
- Debugging and testing of software components
- Documentation
- Presentation and demonstration
| Title: LDSCI6208 Final Project (Computer or Data Science) Course Descriptor
Approved by: Academic Board Location: academic-handbook/programme-specifications-and-handbooks/undergraduate-programmes |
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| Version number | Date approved | Date published | Owner | Proposed next review date | Modification (as per AQF4) & category number |
| 1.1 | December 2022 | August 2023 | Dr Alexandros Koliousis | November 2027 | Category 1: Corrections/clarifications to documents which do not change approved content or learning outcomes. |
| 1.0 | November 2022 | January 2023 | Dr Alexandros Koliousis | November 2027 | |