Postgraduate Course: Innovation-driven Entrepreneurship-Data Science, Technology and Innovation (CMSE11515)
Course Outline
School | Business School |
College | College of Arts, Humanities and Social Sciences |
Credit level (Normal year taken) | SCQF Level 11 (Postgraduate) |
Course type | Online Distance Learning |
Availability | Available to all students |
SCQF Credits | 10 |
ECTS Credits | 5 |
Summary | This course provides an on-line enabled curriculum for students from MSc Data Science, Technology and Innovation (DSTI) programme. It may be open to students from other programmes (MSc and PhD students across the University) in related areas. This course teaches some of the generic understanding of entrepreneurship and innovation, as well as specialised topics related to Data-driven innovation and entrepreneurship. It raises the student's awareness of setting up and running a new venture, and more broadly, encourages students to be an innovative thinker in a variety of organisational contexts. The primary focus is on the development of an opportunity evaluation for a venture exploiting a data-driven idea and/or technology both for commercial and social purposes. |
Course description |
Entrepreneurship has become one of the most powerful and influential forces of change in the world. We are living in a data-driven society where entrepreneurship and innovation driven by data has led to radical social and economic changes. Companies like Apple, Facebook, and Google, all derive their success in part due to the innovative application of novel technology and use of data. However, advanced technology and data alone is not sufficient to guarantee either user adoption or commercial success. Many ideas and technologies are abandoned or ignored despite presenting apparently significant advantages over incumbent systems.
This course introduces students to the theory and practice of entrepreneurship and innovation. It focuses specifically on how and why some innovations are successfully commercialised, with particular emphasis on the role of the innovator-entrepreneur. The course makes specific reference to data-driven innovation and entrepreneurship.
Outline content:
1. Design thinking, Data-driven innovation and entrepreneurship
2. Business models and business model innovation
3. Opportunity discovery and evaluation
4. Finance and funding landscape,
5. Entrepreneurial growth and strategies
6. Entrepreneurial leadership, entrepreneurial ecosystems
Student learning experience:
This course utilises multiple learning modes, including: independent reading, primary research, video-lectures and interviews, online discussions, case studies, and exposure to practice. This course involves a unique collaboration between Edinburgh Innovations and the Business School to bring in industry relevant learning experiences. Students who participate in and engage with every mode of study are most likely to gain the best value of learning from the course.
|
Entry Requirements (not applicable to Visiting Students)
Pre-requisites |
|
Co-requisites | |
Prohibited Combinations | |
Other requirements | None |
Information for Visiting Students
Pre-requisites | None |
High Demand Course? |
Yes |
Course Delivery Information
|
Academic year 2023/24, Available to all students (SV1)
|
Quota: None |
Course Start |
Semester 2 |
Course Start Date |
|
Timetable |
Timetable |
Learning and Teaching activities (Further Info) |
Total Hours:
100
(
Lecture Hours 2,
Seminar/Tutorial Hours 10,
Dissertation/Project Supervision Hours 2,
Online Activities 12,
Programme Level Learning and Teaching Hours 2,
Directed Learning and Independent Learning Hours
72 )
|
Assessment (Further Info) |
Written Exam
0 %,
Coursework
100 %,
Practical Exam
0 %
|
Feedback |
Formative: All students will be given one formative (non-marked) feedback opportunity in time to be useful in the completion of summative assessment. This will be a section of the draft project report (more specification to be provided). Students are asked to take in and reflect on formative feedback to improve for the summative assessment.
Summative: An Individual project report (1000-1500 words) will be assessed on the quality of documentation, research and evaluative analysis. A video (2 min) will be assessed on the clarity of the opportunity idea and the value it generates. Videos that demonstrate significant additional creativity will receive a higher mark. |
No Exam Information |
Learning Outcomes
On completion of this course, the student will be able to:
- Recognise and critically assess an entrepreneurial opportunity in a market (and/or social) space relevant to Data Science, Technology and Innovation
- Critically analyse and consider different business situations where innovative and entrepreneurial opportunities are present or possible
- Research a business start-up opportunity and marketplace to evaluate the attractiveness and/or feasibility of an opportunity
- Communicate ideas and demonstrate interpersonal skills
- Understand and apply the course concepts in the contexts of Data Science, Technology and Innovation, and venture creation and development
|
Reading List
Core texts:
"The new business road test: what entrepreneurs and executives should do before launching a lean start-up"
"Lean analytics: Use data to build a better start-up faster"
"Data-driven business transformation: how businesses can disrupt, innovate and stay ahead of the competition" |
Additional Information
Graduate Attributes and Skills |
The course will introduce students to:
- Meaningful Interpersonal Interaction
- Effective Emotional Intelligence
- Personal and Professional Competence
- Intellectual Curiosity
The course will develop and assess:
- Authentic Leadership
- Ethical, Responsible and Sustainable Business Behaviour
- Appropriate Communication
- Understand and Make Effective Use of Data
- Creative and Entrepreneurial Practice
- Academic Excellence |
Keywords | Entrepreneurship,Innovation,Data |
Contacts
Course organiser | Dr Fumi Kitagawa
Tel: (0131 6)50 8068
Email: |
Course secretary | Ms Ashley Harper
Tel: (0131 6)51 1025
Email: |
|
|