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Academic Handbook BSc (Hons) Applied Digital and Technology Solutions (online)

NCHNAL6125 Data Science Synoptic Project Descriptor

Course Title Data Science Synoptic Project Faculty EDGE Innovation Unit (London)
Course code NCHNAL6125 Teaching Period This course will typically be delivered over a 40-week period.
Credit points 60 Date approved March 2021
FHEQ level 6
Compulsory/ Optional  Compulsory
Prerequisites None

Course Summary

The project will demonstrate a high-level of technical and analytical skill, aligned to achieving organisational goals and enabling effective institutional change. The project may focus on any element of the data science workflow and will culminate with a dissertation. The dissertation will combine technical research with organisational needs and project management and will enable the student to deepen his or her understanding of a particular area of data science. 

Course Aims

  • Give students the opportunity to carry out independent research and in-depth analysis in data science.
  • Train students to write up their findings and ideas clearly, coherently and to a high-professional standard.
  • Train students to present their own arguments logically and competently, to engage specialist and non-specialist stakeholders.

Learning Outcomes

On successful completion of the course, students will be able to:

Knowledge and Understanding

K1c Reflect, in depth, on the body of academic knowledge in a particular specialist field of data science.
K2c Understand how to systematically apply critical analysis and the appropriate data science methodologies to achieve a successful outcome.

Subject Specific Skills

S1c Apply project delivery techniques and appropriate tools to plan, organise and manage resources to successfully run the project.
S2c Communicate and disseminate project findings through high impact, creative storytelling, tailored to specialist and non-specialist audiences.

Transferable and Professional Skills

T1c Use academic and industry-specialist literature to build an argument and carry out sophisticated analysis of the chosen topic.
T2c Present findings concisely and clearly.
T3ci Make meaningful conclusions on the basis of a long period of independent study.
T3cii 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

The formal taught contact hours on this course are formed predominantly by online supervisory tutorials, typically 12 x 1 hour.

Students are expected to carry out independent research into the topic. Readings should include a mix of books, journal articles, policy papers and other relevant documents, depending on the topic and the approach taken in the dissertation.

Course information and supplementary materials are available on the University’s Virtual Learning Environment (VLE).

Students are required to attend and participate in all the formal and timetabled sessions for this course. Students are also expected to manage their directed learning and independent study in support of the course.

The course learning and teaching hours will be structured as follows:

  • independent learning and teaching ( 40 weeks x 7.5 hours  ) = 300
  • Private study ( 7.5 hours per week) = 300

Total = 600 hours Assignments (see below) will be completed as part of private study



Students will be formatively assessed during the course by means of a project plan review. This will not count towards the final degree but will provide Students with developmental feedback. 


AE Assessment


Weighting Online submission Duration Length
1 Exam 20 yes 2 hours  
2 Dissertation 50% Yes 7,500 words

+/- 10%

3 Presentation 30% Yes 15mins +/-


The summative assessment will be assessed in accordance with the assessment aims set out in the programme specification.


Students will receive formal feedback in a variety of ways: written (via email or VLE correspondence) and indirectly through online discussion groups. Students will also attend a formal meeting with their Mentor. These reviews will monitor and evaluate the student’s progress.

Feedback is provided on summative written assignments which will be handed back to the students.

Indicative Reading

Note: Comprehensive and current reading lists for courses are produced annually in the Syllabus or other documentation provided to students; the indicative reading list provided below is used as part of the approval/modification process only.


  • Walliman, N., (2004), Your Undergraduate Dissertation: The Essential Guide for Success, London: Sage.
  • Swetnam, D., (2001), Writing Your Dissertation: How to Plan, Prepare and Present Your Work Successfully, Begbroke: How To Books Ltd.


Students are encouraged to consult relevant journals on their relevant specialism.

Electronic Resources

Students are encouraged to consult relevant electronic resources on their relevant specialism. 

Indicative Topics

  • How to solve a technological problem based on an organisation’s problem
  • Managing technology projects to a successful outcome
  • Using real-world data and scenarios
Title: NCHNAL6125 Data Science Synoptic Project Course Descriptor

Approved by: Academic Board

Location: Academic Handbook/Programme specifications and Handbooks/

Undergraduate Online Programmes/Applied BSc (Hons) Digital & Technology Solutions/Course Descriptors

Version number Date approved Date published Owner Proposed next review date Modification (As per AQF4)

& category number

3.0 December 2022 January 2023 Dr Yu-Chun Pan June 2026 Category 3: Change to English Proficiency Learning Outcome

Category 1: Corrections/clarifications to documents which do not change approved content or learning outcomes

2.1 August 2022 August 2022 Scott Wildman June 2026 Category 1: Corrections/clarifications to documents which do not change approved content or learning outcomes
2.0 January 2022 April 2022 Scott Wildman June 2026 Category 3: Changes to Learning Outcomes
1.0 March 2021 Scott


March 2026
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