Our Digital Technology Solutions Specialist (Data Analytics) Master’s Degree Apprenticeship will develop the skills, knowledge and behaviours of you or your team to become successful Data Analytics Specialists.
A data analytics specialist investigates business data requirements, and applies data selection, data curation, data quality assurance and data investigation and engineering techniques. This will help the business to most effectively organise their data and will be able to provide advice and guidance to database designers and others in using the data structures and associated data components efficiently. They will undertake data processing to produce data sets for study and will perform investigations using techniques including machine learning to reveal new business opportunities. They also present data and investigation results along with compelling business opportunities reports to senior stakeholders.
Who is this programme for?
Typical job roles which suit this programme include: Big data analyst, data and insight analyst, data science specialist, data management specialist, analytics lead.
Programme content
Quantitative Data Analysis
The aim of the module is to develop knowledge and skills of the quantitative data analysis methods that underpin data science. Content covers a practical understanding of core statistical methods in data science application and research (e.g., bivariate and multivariate methods, regression and graphical models). A focus is also placed on learning to evaluate the strengths and weaknesses of methods alongside an understanding of how and when to use or combine methods.
Modern Data
The module is aimed at introducing data management and exploration. An overview of current industry-standard processes to modern data analysis will be presented. The students will learn to design and plan a predictive analytics project. Basic concepts of data management and retrieval will be discussed. Well-established strategies and approaches to data understanding, data preparation and cleaning will be presented.
Machine Learning
The aim of the module is to develop the reflective and practical understanding necessary to extract value and insight from heterogeneous data sets using statistical learning. Focus is placed on the analytic methods/techniques/algorithms for generating value and insight from the processing of heterogeneous data.
Leadership Action Sets
Leadership action sets are workshop-style activities run over the summer term with the participation of industry leaders. The aim is for apprentices to reflect on their leadership skills development. These sets are linked to the development of the e-portfolio.
High Performance Computational Infrastructure
The aim of the module is to develop knowledge and skills necessary for working effectively with the large-scale data storage and processing infrastructures that underpin data science. You will develop both practical skills and an ability to reflect critically on concepts, theory and appropriate use of infrastructure. Content here covers, highly scalable cloud computing tools (e.g., Hadoop) and in-memory approaches (e.g. Spark).
Ethics & Governance of Digital Systems
To develop a critical understanding of topics related to the handling and governance of digital information in contemporary systems contexts. Such topics will include the way that networked and intelligent systems are designed and used; the motivations for their adoption; the substantive issues arising; and approaches to their regulation and governance. Examples from the public and private sectors will be used to illustrate these developments.
Digital Innovation & Strategy
The aim of this module is to develop knowledge and skills necessary for the implementation of digital business models and technologies intended to realign an organisation with the changing demands of its business environment (or to capitalise on business opportunities).
Research Project Management
To develop and deploy the skills necessary to design a scholarly piece of research work to address an identified problem area within the chosen field of study.
Data Visualisation
The aim of the module is to develop the reflective and practical understanding necessary to visually present insight drawn from large heterogeneous data sets (e.g., to decision-makers). Content will provide an understanding of human visual perception, data visualisation methods and techniques, dashboard and infographic design. The role of interactivity within the visualization process will be explored and an emphasis placed on visual storytelling and narrative development.
End Point Assessment Project
The agreed project will present a typical business task, appropriate for demonstrating the skills and knowledge of the apprenticeship standard. The agreed project will be comparable in terms of content and complexity for all apprentices - it is the context within which the knowledge, and skills must be demonstrated that will vary. Each project will take, typically, six months to complete. The project is undertaken and completed on programme and pre-gateway to the End Point Assessment (EPA). The project itself is not part of the EPA.
Find out more about Tech Industry Gold
- Programmes accredited by Tech Partnership Degrees as Tech Industry Gold meet industry standards for quality, relevance and employer focus.
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- Employers can choose Tech Industry Gold programmes with confidence, knowing they meet industry standards for quality, relevance and employer-focus. Tech Industry Gold programmes are defined by industry to integrate the technical, business and interpersonal skills that are most valued by employers. Tech Industry Gold programmes are defined by industry to give students the best possible career prospects.Major employers are choosing digital degree apprenticeships to attract and retain top digital talent.
For more details on the Tech Industry Gold degrees and degree apprenticeships accredited by Tech Partnership Degrees, go to www.tpdegrees.com
How is this programme delivered?
You are required to dedicate at least 20% of your working hours studying towards the programme. Our teaching sessions, including lectures, labs, seminars, and tutorials, will primarily be delivered in-person, on campus. There may be instances where other forms of delivery (e.g., online) are adopted, where necessary and/or if appropriate, to enhance the teaching experience. However, you should expect to attend all teaching sessions, examinations and other relevant assessments in-person, on campus.
As our programmes are highly practical and involve group work, we believe that attending teaching sessions on campus provides the best experience, both socially and academically, for you.
Entry requirements
2:2 or above UK Honours degree or equivalent internationally recognised qualification from a scientific, engineering, or a numerate subject.
We welcome applicants with other qualifications and industrial experience (relevant to the subject area), who will be assessed on an individual basis.
Functional Skills
All apprentices are required to hold a Level 2 English and Mathematics qualification before completing the programme’s final assessment. If your apprentice cannot evidence these qualifications, our functional skills delivery partner will support your apprentice to achieve this. This will include attending additional English and Mathematics training sessions and completing four formal assessments.
Applicants will need to be able to demonstrate their eligibility for the apprenticeship according to the most recent Apprenticeship Funding Rules https://www.gov.uk/guidance/apprenticeship-funding-rules
Final degree award
When you have completed your apprenticeship, you will be awarded the degree MSc Digital & Technology Solutions.
Develop your skills and knowledge to become a successful Data Analytics Specialist