Data Scientist Level 6 Apprenticeship (BSc Data Science)
The Data Scientist Degree Apprenticeship (BSc Data Science) is a structured undergraduate programme. Data science has increasingly become more relevant and important in today’s world. Insight driven businesses are said to be growing at an average of more than 30% per year and so there is an increasing demand for professionals who are adept in data science. Data Scientist Degree Apprenticeship (BSc Data Science) provides a broad understanding of aspects of Information Systems coupled with in-depth development of data science knowledge base and skillsets. The distinguishing aim of the programme is to support students to acquire the skills and knowledge needed as technology professionals in the data science sphere. The programme covers a range of subjects that will develop and hone the skillsets and knowledge base that are needed for a career in the sector and has been put together to incorporate the essential knowledge required for a well-rounded education in data science.
Who the apprenticeship is for?
The overarching aim of the Data Scientist Degree Apprenticeship (BSc Data Science) programme is to support students to acquire the skills and knowledge needed as technology professionals in the Data Science sphere. The programme covers a range of subjects that will develop and hone the skillsets and knowledge base that you need for a career in the sector. The programme has been put together to incorporate the essential and relevant knowledge that is required for a well-rounded education in Data Science. On successful completion of the programme you would be equipped with the relevant skill sets needed for successful professional careers in industry or academia.
The programme typically opens doors to careers in roles such as Data Scientist, Informatics and Data Engineer. According to the iFATE standard, “Data Scientists have an impact at a strategic and operational level by building and maintaining strong collaborative relationships with key stakeholders, subject matter experts and colleagues at all levels. They engage with the wider Data Science community to share ideas, techniques and experiences. They can work in any sector, public or private, and will often work in a multi-disciplinary team with domain experts, Data Architects, Data Engineers, Analysts, and Technology Professionals”.
Entry requirements
All applicants need to be employed by an organisation in a role that provides them with the experience and exposure to a range of relevant business areas. This will ensure that apprentices can complete all elements as required by the standard.
The entry requirement for the Data Scientist Degree Apprenticeship (BSc Data Science) at DMU are the standard entry requirements normally 112 UCAS points from at least two A-levels or equivalent Five GCSEs at grade C or above, or including Mathematics and English BTEC requirements although other relevant qualifications or experience may also be considered. Apprentices without level 2 English and maths will need to achieve this level within 12 months of the commencement of the programme and prior to the End Point Assessment.
Delivery model
There are 19 modules and the End Point Assessment in the Data Scientist Degree Apprenticeship (BSc Data Science). At the end of the Apprenticeship both the academic and work-based experience will be assessed. The following table outlines what each of these modules are when during the programme they will be taken.
Level 4
| Module code | Module title | Credit value | Core/Optional |
|---|
|
IMAT1xxx
|
Foundation of Python Programming
|
15
|
Core
|
|
IMAT1xxx
|
Data Analytics and Statistics 1
|
15
|
Core
|
|
IMAT1xxx
|
Work Based Learning 1
|
15
|
Core
|
|
IMAT1xxx
|
Information Systems Analysis
|
15
|
Core
|
|
IMAT1xxx
|
Data Analytics and Statistics 2
|
15
|
Core
|
|
IMAT1xxx
|
Computer Ethics
|
15
|
Core
|
|
IMAT1xxx
|
Programming in Python 2
|
15
|
Core
|
|
IMAT1xxx
|
Database Design
|
15
|
Core
|
Level 5
| Module code | Module title | Credit value | Core/Optional |
|---|
|
IMAT2XXX
|
Information and Database Development
|
15
|
Core
|
|
IMAT2XXX
|
Integrated Project
|
15
|
Core
|
|
IMAT2XXX
|
Management Decision Making
|
15
|
Core
|
|
IMAT2XXX
|
Advanced Data Analytics
|
15
|
Core
|
|
IMAT2XXX
|
Data Visualisation
|
15
|
Core
|
|
IMAT2XXX
|
Analytics and Business Modelling
|
15
|
Core
|
|
IMAT2XXX
|
Work Based Learning 2
|
15
|
Core
|
|
IMAT2XXX
|
Introduction to Information Security
|
15
|
Core
|
Level 6
| Module code | Module title | Credit value | Core/Optional |
|---|
|
IMAT3XXX
|
Project (1 & 2)
|
30
|
Core
|
|
IMAT3XXX
|
Data Science with Python
|
15
|
Core
|
|
IMAT3XXX
|
Information Security Management and Governance
|
15
|
Core
|
End Point Assessment*
| Module code | Module title | Credit value | Core/Optional |
|---|
|
EPA
|
Endpoint Assessment
|
60
|
Core
|
*This will take place 6 months after 36 months of study. The EPA also runs after the Project module
The modules on the programme will be delivered in block mode, each of the modules will be covered over a week of teaching. There may be engagements and supports outside the teaching week particularly for lab/work-based modules. There would also be preparatory work and post-work both before and after the week of teaching. Academic support would also be available prior and after the week of teaching for apprentices to get help and advice as required. The support would include access to the virtual learning environment, to discussion boards, access to the teaching staff and to the Centre for Learning and Study Support (CLaSS).
Duration
The typical registration for the Data Scientist Integrated degree programme is 36 months (+ 6 months End Point Assessment) and as this is an integrated apprenticeship, the End Point Assessment is undertaken in the final semester of the programme. The End Point Assessment is a must pass module and apprentices need to pass it to get their degree as well as apprenticeship.
Final degree award
Bachelor of Science (Honours), Data Science
Assessment
Assessment methods and assessment criteria are vested in the individual modules constituting the programme. Each module specification defines the assessment methods and reassessment details which are appropriate to the aims and objectives and the teaching and learning strategy of the module: the choice of the most suitable coursework is dependent on the subject and content of the module. Some modules adopt a combination of a time-constrained phase test and other coursework assessment. Other module assessment methods include reports, posters and presentations. Wherever feasible, student assessment work is submitted to Turnitin. In block mode, for instance, time constrained phase tests may be organised online using MS-Teams outside the one-week contact.
Knowledge and Understanding is assessed on the programme through a series of Knowledge, Skills and Behaviour. For successful completion of the Apprenticeship the EPA must be taken and passed.
Successful completion of the EPA will consist of 60 credits and signify the completion of the apprenticeship as well as the full Degree. As this is an integrated apprenticeship the EPA would be delivered by DMU but assessed by independent assessors (not involved in the on-programme delivery) and will be completed in the final semester of the programme as part of the other final semester modules. The apprenticeship will typically take 36 months.
For more information, contact us by completing our online enquiry form.