DSC2007 : Industry Practice of Data Science and AI
- Inactive for Year: 2026/27
- Module Leader(s): Dr Paul Goodman
- Lecturer: Dr Tatiana Alvares-Sanches, Mr Graham Cole
- Owning School: Computing
- Teaching Location: Newcastle City Campus
Semesters
Your programme is made up of credits, the total differs on programme to programme.
| Semester 2 Credit Value: | 20 |
| ECTS Credits: | 10.0 |
| European Credit Transfer System | |
Aims
This module develops your ability to work collaboratively on a substantial data science and artificial intelligence project addressing real or realistic organisational problems. You will study approaches for understanding stakeholder and business needs, designing data-driven solutions, and developing and evaluating computational prototypes within team-based project environments. The emphasis is on integrating technical, analytical, organisational, and communication skills from across the programme while managing collaborative workflows and presenting outcomes to different audiences.
Outline Of Syllabus
Topics covered by this module include:
Working with external organisations and stakeholders
Understanding business problems and designing appropriate project deliverables
Innovation, design thinking, value propositions, and business models
Business model canvases and their application within data science and AI projects
User and stakeholder insight collection and approaches to organisational innovation
Development of prototypes using appropriate computational and analytical techniques
Evaluation of prototypes and communication of recommendations to clients and stakeholders
Deployment of minimum viable products and prototype systems
Operational, organisational, and deployment considerations for data-driven solutions
Teaching Methods
Teaching Activities
| Category | Activity | Number | Length | Student Hours | Comment |
|---|---|---|---|---|---|
| Guided Independent Study | Assessment preparation and completion | 1 | 30:00 | 30:00 | Preparation and completion of formative assessment following workshops |
| Structured Guided Learning | Lecture materials | 20 | 1:00 | 20:00 | Reading through lecture materials – preparing / follow up |
| Scheduled Learning And Teaching Activities | Lecture | 10 | 1:00 | 10:00 | Lectures |
| Guided Independent Study | Assessment preparation and completion | 1 | 38:00 | 38:00 | Preparation and completion of summative group presentation |
| Guided Independent Study | Assessment preparation and completion | 1 | 45:00 | 45:00 | Preparation and completion of summative group report |
| Guided Independent Study | Directed research and reading | 20 | 1:00 | 20:00 | Wider reading as per provided reading list |
| Scheduled Learning And Teaching Activities | Workshops | 10 | 3:00 | 30:00 | Workshops |
| Scheduled Learning And Teaching Activities | Workshops | 1 | 7:00 | 7:00 | Module wrap-up workshop |
| Total | 200:00 |
Teaching Rationale And Relationship
This module includes an encounter with the leading edge of industry, practice and society.
Assessment Methods
The format of resits will be determined by the Board of Examiners
Other Assessment
| Description | Semester | When Set | Percentage | Comment |
|---|---|---|---|---|
| Report | 2 | M | 50 | Maximum 2500 words. Group report on business understanding and technical solution including project timeline. Submission to be accompanied by an appendix of one page on their individual and team contributions. |
| Oral Presentation | 2 | M | 50 | ~20 minute group presentation + 5 mins questions. Each group member to speak for 3 mins minimum. Audience will be both to the assessment team and peers. |
Formative Assessments
Formative Assessment is an assessment which develops your skills in being assessed, allows for you to receive feedback, and prepares you for being assessed. However, it does not count to your final mark.
| Description | Semester | When Set | Comment |
|---|---|---|---|
| Portfolio | 2 | M | Group submission of the various canvasses (project plan, value proposition canvas, business model canvas, MVP architecture) from the in-module workshops, upto 6 pages. |
Assessment Rationale And Relationship
The group project report assesses students’ ability to develop, justify, and evaluate a data-driven solution to a real or realistic organisational problem within a collaborative project environment. Students are required to demonstrate understanding of the client or stakeholder context, explain the development of their proposed solution and minimum viable product, and reflect on technical, organisational, ethical, and project management considerations associated with the work undertaken. The report assesses students’ ability to apply computational and analytical approaches, work effectively with data, contribute within a team setting, and critically evaluate the effectiveness and practical implications of proposed solutions. (MLO1, MLO2, MLO3, MLO5)
The group presentation assesses students’ ability to communicate and justify project outcomes to both technical and non-technical audiences. Students are required to present their understanding of the problem context, explain their proposed solution and development process, discuss benefits, limitations, risks, and future opportunities, and respond appropriately to questions relating to the project. The assessment also evaluates collaborative working, professional communication, and audience awareness within a team environment. (MLO3, MLO4, MLO5)
The formative portfolio activities support the development of project planning, innovation, and stakeholder-focused design skills through the submission of workshop-based materials such as project plans, value proposition canvases, business model canvases, and minimum viable product architectures. These activities enable students to document and reflect on the progression of their project work while receiving feedback throughout the module.
The assessment structure supports the development of collaborative, technical, organisational, evaluative, and communication skills appropriate to realistic data science and AI project environments, enabling students to integrate knowledge and practices developed across the programme.
Alternative assessment:
For students with a Student Support Plan (SSP) who have alternative assessment as a reasonable adjustment and/or students with supported Personal Extenuating Circumstances (PEC), it may be necessary to set an alternative assessment as presented below. Due to the professional requirements of some programmes, alternative assessments may not be available even where students are eligible.
Alternative arrangements for the group presentation may include an individual presentation to the teaching team, submission of a recorded presentation, and/or an individual reflective report addressing both the technical solution and the student’s contribution and progression within the project.
Reading Lists
Timetable
- Timetable Website: www.ncl.ac.uk/timetable/
- DSC2007's Timetable