麻豆果冻传媒

Programme structure

The programme is designed to cover three main areas.

• Data management – structuring and manipulating data for analysis purposes
• Data interpretation – methods of machine learning and statistical analysis using industry-standard software such as R, SAS and Python
• Project management – business-specific and strategic aspects of analytics

With support from the employer, apprentices are required to spend 20% of paid working hours on studies and be able to evidence this. This is a statutory requirement for apprenticeships and the funding is conditional on this being met. Off-the-job learning includes activities which have not previously been a part of the role or furthers apprentices development into new areas.

The University of 麻豆果冻传媒 Mathematics department has Statistical Analysis System (SAS) Academy status

Syllabus

Core modules

• Introduction to Statistical Data Analysis with R
• Business Analytics Strategy and Practice
• Data Management
• Data Mining and Knowledge Discovery in Data
• Final Apprenticeship Project in Data Analytics
• End Point Assessment for Digital and Technology Solutions Specialist (Data Analytics)

Options*

• Forecasting and Credit Risk Analysis
• Multivariate Analysis and Statistical Modelling
• Medical Statistics
• Programming for Analytics with SAS
• Project in Statistical Data Analysis with R
• Machine Learning and Artificial Intelligence
• The Analysis of Time Series

The programme has built-in flexibility and can be adapted to the needs of the apprentices background.

*Option modules are indicative and may change, depending on timetabling and staff availability.

Core skills 

Upon completion of the programme, apprentices will be equipped to:

• apply a range of statistical and analytical skills appropriate to a specified business problem
• critically evaluate the requirements for the solution to an analytics problem in terms of data structures and technologies, and produce appropriate solutions
• specify, design, implement and test software to meet data-specific project goals using appropriate tools including programming
• manage and critically appraise the success of a data analytics project using appropriate project management techniques and software

• function effectively as part of a project team and take responsibility for the management of aspects of a project
• ensure the ethical and legal use of data collected and analysed according to professional codes of practice
• design and maintain both technical and application documentation to a high standard
• evaluate and assess the success of a project and make recommendations for improvement.

Teaching and assessment

The course itself is specifically designed to nurture apprentices’ learning capabilities through research, and aims to train apprentices as critically reflective researchers and learners. The School is supported by an Industrial Advisory Board (IAB) for Mathematics and Computing.

Teaching is comprised of a blend of lectures, tutorials, workshops and computer labs. Total self-led learning and teaching hours per 20-credit module equals to 200 hours.

Additionally, apprentices will have an academic advisor overseeing their workplace-based activities and assessing. This will be achieved through quarterly reviews.

Throughout the programme of study apprentices will be assessed through: 

• reports
• presentations
• practical assignments.

This programme of study is an integrated Degree Apprenticeship and includes the End Point Assessment (EPA) which is assessed and graded by an assessor from an awarding university. The EPA comprises a project report and a professional discussion and must be completed over a maximum period of three months after the apprentice has met the gateway requirement.

Employer and apprentice commitments

In order to deliver the programme, the employer undertakes to:

• conduct a workplace induction and set out a contract of employment
• provide an appropriately qualified workplace mentor to support the apprentice
• attend apprentice's progress review (twice a year) 
• release apprentice for scheduled off-the-job training
• have an Apprenticeship Agreement in place from the start of the programme.

Throughout the programme, apprentices will:

• attend the workplace for the agreed pattern as set out in the employment contract 
• record all training sessions and off-the-job learning 
• attend scheduled university learning sessions and complete all assessments as required by the university and End Point Assessment Organisation
• behave in a safe and responsible manner at the workplace and university
• engage with regular progress reviews 
• complete, throughout the apprenticeship, a professional development portfolio.

Staff profiles

Fees and funding information for apprentices

Course fees

As an apprentice the cost of your learning programme is covered by your employer through their Digital Apprenticeship Service (DAS) account.

Student finance

Higher and degree level apprentices are not eligible for any element of student finance. This is because they receive a salary instead of the student loan package. However, if you are experiencing any financial difficulties, please contact the Student Advice Service on 01273 642 888.

Learning support

Apprentices studying at Higher and degree level may be able to access funding in relation to additional support but this is available through the university and not Disabled Students Allowance. Apprentices may also be able to apply for funding for work-based equipment and software. Please contact the Disability and Learning Support team on 01273 643 799.