Sample Certificate

The MSc has a total of 90 ECTS credits and comprises of 6 taught modules at 10 ECTS credits each and a Work Based Project at 30 ECTS credits.

Award to be conferred

Master of Science in Fin-Tech: Block-Chain and Digital Currencies

 

Aims

The aim of the MSc. in “Fin-Tech: Blockchain and Digital Currencies” is to develop and enhance the skillset required for contemporary changing financial services industry.

The MSc. in “Fin-Tech: Blockchain and Digital Currencies” is an interdisciplinary programme that focuses on finance, innovation, emerging tech such as DLT and digital currencies. It is designed to appeal to graduates seeking to gain exposure to Fin-Tech – the technology enabled business model innovation in the financial sector.

More specifically, while the interest in digital currencies has skyrocketed in the past few years, academic institutions have been slow to implement academic programs that cover the need for educating specialists in the area, addressing it in its entirety (technical and financial aspects alike). This programme seeks to fill an important gap that exists today between the supply of and demand for academic knowledge in the area of Fin-Tech especially in Blockchain and Digital Currency.

Programme Learning Outcomes

Upon successful completion of the MSc in Fin-Tech: Blockchain and Digital Currencies, the student will be able to:

  • Create a critical understanding of core financial technologies and financial market and services while also enhancing the practical technical skills.
  • Develop an in-depth understanding of risks, opportunities and challenges of new markets and Fin-Tech entrepreneurship.
  • Understand the emerging technologies fundamental such as DLTs, Blockchain and Smart contracts and their application in today’s Fin-Tech.
  • Develop and Implement new strategies for organizations in new technologies in finance.
  • Apply the practical knowledge and tools in different styles of investing and financing, from the most traditional to the most innovative.
  • Develop in-depth knowledge and analytical skills in current and developing financial technologies.

Assessments

The underpinning principles which drive the assessment strategies adopted for this programme are the profile of the target students and the programme itself (its philosophy and associated learning outcomes). Assessment will normally be based on the candidate successfully demonstrating achievement of an appropriate combination of the following criteria which are aligned to the descriptors for Level 7 Master degree qualifications:

a) A systematic understanding of a substantial body of knowledge, and a critical awareness of current big-data problems and/or new insights, much of which is at, or informed by, the forefront of the academic discipline, field of study, or area of professional practice;

b) A comprehensive understanding of methods and techniques applicable to the practical work-based decision management issues which require solutions and improvements;

c) Originality in the application of knowledge, together with a practical understanding of how to establish, identify and solve decision making problems using appropriate prediction techniques and tools.

d) The ability to evaluate and criticise received analytics graphs, facts and figures.

e) The ability to make reasoned judgements whilst understanding the limitations on judgements made in the absence of complete data; and choose alternate data for missing data.

f) The ability to communicate the results of the programme of research as demonstrated in the style and overall presentation in a professional manner.

Entry Requirements

An applicant may be admitted on the basis of evidence to suggest that he/she will be able to fulfil and benefit from the objectives of the programme and achieve the standard required for the award.

A number of criteria are used in considering admissions to the programme including candidates’ language proficiency, academic and professional qualifications. And includes the following:

  • A Bachelor’s Degree qualification in any subject from a recognised institution
  • A professional qualification equivalent to a degree and a minimum of two years of working experience.
  • Mature and high potential candidates without degree or equivalent qualifications but hold Diplomas or Advanced Diplomas with more than six years of work experience of which at least two years are at supervisory – managerial level with basic IT background.
  • Mature and high potential candidates without Diploma qualifications but with more than 8 years of work experience of which at least 3 years are at supervisory / managerial levels
  • Demonstrate English Language proficiency in order to participate in the programme taught in English

Advanced Standing/ Exemptions/ Credits Transfer (APL)
Consideration for the above for students admitted onto the programme may be considered either at the beginning of a programme, or beyond the beginning of a programme, through an assessment of that student’s prior learning, whether certificated or un-certificated.   The process for making such a decision is known as the Accreditation of Prior Learning (APL) is a matter of academic judgment exercised by the appointed panel considering applications and approvals of APL.

Where cohorts of students are to be admitted with advanced standing on a regular basis, the arrangement should be subject to an Academic Progression Agreement.

Programme Structure

In designing this programme, the prior qualifications and corporate experiences of participants are taken into consideration in order to ensure a programme which builds on their prior knowledge and skills.

The MSc has a total of 90 ECTS credits and comprises of 6 taught modules at 10 ECTS credits each and a Project at 30 ECTS credits. The modules are:

  1. Fin-Tech: market and services
  2. Innovation & entrepreneurship in Fin-Tech
  3. Distributed ledger technologies and applications
  4. Blockchain, cryptocurrencies and smart contracts
  5. Regulation and digital currencies
  6. Investments and advanced asset management
  7. Plus a 30ECTS Work Based Project

The Work Based Project of between 8,000 and 10,000 words accrues 30 ECTS credits.

Mode of Delivery

Blended Delivery Mode

Self-Instructional Learning Material Face to Face Tutorials Online Discussions
Students are given a complete set of learning materials to facilitate independent study which can be downloaded from the designated Learning Portal. Face-to-Face classes conducted at a learning centre at 12 hours per module. Learners are encouraged to participate in online discussions with other learners and their tutors for at least 18 hours per module.

Fully Online Mode

Self-Instructional Learning Material Online Discussions
Students are given a complete set of learning materials to facilitate independent study which can be downloaded from the designated Learning Portal. Learners are encouraged to participate in online discussions with other learners and their tutors for at least 18 hours per module.

Location

For the Blended Mode and Face to Face Fully Taught Mode please Contact Us to find an Approved Learning Centre near you.

For the Fully Online Mode please enrol now to sign up for the next available intake.

Notional Hours

Notional hours are defined in terms of the amount of time it should take a learner to achieve the learning outcomes.  Each ECTS credit requires on average 20 notional hours of a learner’s time.

Guide to Learning Hours / Student Learning Time
This Level 7 Programme accrues 90 ECTS credits spread over 6 modules, a Reflective Log and a Work Based Project or 1,800 notional hours in total.  The programme can be completed within 10 to 15 months.

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