DSC8105 : Data Science and New Venture Creation Plan (Inactive)
- Inactive for Year: 2026/27
- Module Leader(s): Dr Eftychia Palamida
- Lecturer: Dr Aamir Khan
- Owning School: Â鶹´«Ã½ Business School
- Teaching Location: Â鶹´«Ã½ City Campus
Semesters
Your programme is made up of credits, the total differs on programme to programme.
| Semester 3 Credit Value: | 60 |
| ECTS Credits: | 30.0 |
| European Credit Transfer System | |
Aims
To provide students the opportunity to develop a feasible and rigorously researched business plan for a data science venture of their own design informed by data science techniques and tools related outcomes.
Based on the knowledge and skills gained in the pre-requisite modules, the students will interact with customers, suppliers, and intermediaries to validate a business opportunity through the collection and analysis of relevant primary (quantitative/qualitative data) and secondary data.
Students will develop a business plan, including the explanation and empirical support to justify a need in a target market, product and/or service design, intellectual property, strategic analysis, market entry strategy, operational design, marketing plan.
Outline Of Syllabus
NVCP Projects will be related to a real-world applied data science problem which can be tackled by appropriate methods in data science and statistics.
In every NVCP project there will be a practical component of a strong design and/or programming and/or analytic element that relates to the diverse components incorporated into a business plan.
Teaching Methods
Teaching Activities
| Category | Activity | Number | Length | Student Hours | Comment |
|---|---|---|---|---|---|
| Scheduled Learning And Teaching Activities | Lecture | 1 | 2:00 | 2:00 | Introduction to the module and requirement for the assessment |
| Scheduled Learning And Teaching Activities | Workshops | 2 | 2:00 | 4:00 | Workshops on Data Science Component – (Analytics Techniques/Tools/Platforms-Example Data Sources) |
| Scheduled Learning And Teaching Activities | Workshops | 2 | 2:00 | 4:00 | Workshops on Entrepreneurship Component – New Venture Creation Plan (Market Research and De-Risking with Secondary and Primary Qualitative/ Quantitative Data) |
| Scheduled Learning And Teaching Activities | Workshops | 2 | 2:00 | 4:00 | Workshops on Entrepreneurship Component – New Venture Creation Plan (Business Plan Sections) |
| Scheduled Learning And Teaching Activities | Dissertation/project related supervision | 6 | 1:00 | 6:00 | Supervisor meetings (4-hours of group drop-in sessions and 2-hours of individual support) |
| Guided Independent Study | Independent study | 1 | 582:00 | 582:00 | N/A |
| Total | 602:00 |
Teaching Rationale And Relationship
An initial Lecture along with workshops will be offered to support students’ involvement in the New Venture Creation Plan (MVCP) process and de-risking (entrepreneurship component) with the use a data analytics and visualisations (data science component).
Students will be assigned an individual NVCP supervisor. The NVCP supervisor will guide and support the student through the various stages of conducting their entrepreneurial project. NVCP supervision will be a combination of one to one and small group dissertation meetings. Small group NVCP meetings will also offer students the opportunity to engage in peer learning.
The teaching methods for this module are designed to align with the learning outcomes as follows:
--Lectures - Provide a foundational understanding of New Venture Creation Plan and Data Science concepts, essential for all further learning and application.
--Workshops: Provide a foundational understanding of New Venture Creation Plan and De-Risking via Qualitative / Quantitative (statistical-data science) Data, essential for all further learning and application.
--Group/Individual Supervision: Offer personalised guidance and feedback, aiding students in refining their problem-solving approaches and communication skills.
--Independent Work - Develop practical skills through self-directed study and application, fostering critical thinking, data analysis proficiency, project management, and report writing.
This structure ensures students gain both theoretical knowledge and practical expertise, preparing them to apply data science concepts in an entrepreneurial context, communicate findings effectively, and understand the commercial implications of their work.
Assessment Methods
The format of resits will be determined by the Board of Examiners
Other Assessment
| Description | Semester | When Set | Percentage | Comment |
|---|---|---|---|---|
| Oral Presentation | 3 | M | 10 | Pitch Presentation (10 min) |
| Written exercise | 3 | M | 40 | New Venture Creation Business Plan (7,000 words) |
| Written exercise | 3 | M | 10 | Business Evaluation based on De-Risking Approach (1,000 words) |
| Written exercise | 3 | M | 40 | Data Science Reflection (2,000 words) |
Assessment Rationale And Relationship
The module is based on an individual portfolio assessment that comprises of specific components.
---Pitch: The individual Presentation (Pitch-entrepreneurship component) will make students develop their skills to convince and embark knowledgeable stakeholders regarding their business idea.
---Business Plan: An individual in-depth New Venture Creation Plan (Business Plan-entrepreneurship component) allows students to develop and practice each of its integrated components by collecting and using appropriate data (Data Science component).
--Business Evaluation: The individual Evaluation of the Business Idea Viability (NVCP component) will make the students analyse and draw conclusions about the inherent, non-linear process and choices related to venture creation.
--Data Science Reflection: The individual Reflection on the use of Data Science related Tools/Techniques that have informed entrepreneurial decisions (Data Science component) will make the students analyse and make conclusions about the use and implementation of data analytics and visualisation related to entrepreneurial decisions.
Reading Lists
Timetable
- Timetable Website: