Data Analytics
Entry requirements
A level
A Level subject/s should be in a discipline related to IT Engineering
GCSE/National 4/National 5
Also, a minimum of three GCSE passes at grade 4 or above to include English and maths.
Pearson BTEC Level 3 National Extended Diploma (first teaching from September 2016)
BTEC should be in a discipline related to IT or Computing
UCAS Tariff
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Attend an interview
About this course
Students will learn about a wide range of professional and transferable skills including professional behaviours needed in the workplace, as well as application of academic skills to the workplace. To this end the programme structure includes modules of work based leaning at level four an a project module at level five that is also work based, allowing students to connect to real life, real work situations and opportunities to enhance their understanding and professional competence, making them valuable employees. The course will benefit from links to the professional workplace including guest speakers. This specialist pathway will include the skills and knowledge needed to collect, organise, provide and study up to date data, providing analysis for the organisation. They will develop a good understanding of data structures, software development procedures and how to employ a range of analytical tools used to undertake a wide range of standard and custom analytical studies. Analytical techniques such as data mining, time series forecasting and modelling techniques will be learnt to identify and predict trends and patterns in data. Candidates will also be able to present a range of data visualisation to a range of stakeholders. On successful completion, the candidate may wish to enter into a variety of computing roles where a Data Analytics qualification is desirable. Those already in professional roles may progress into more senior positions. Students may also wish to progress into higher study at level 6, gaining a full BSc degree in a computing discipline.
Modules
Year 1: DT4001 - Computers and Security; DT4002 - Principles of Programming; DT4003 - Maths for Data Science; DT4004 - Systems Design & Development; DT4005 - Independent Work-Based Project. Year 2: DT5010 - Professional Issues; DT5011 - Managing the Security if Information; DT5012 - Agile Development; DT5013 - Further Programming; DT5014 - Supervised Professional Work Experience; DT5023 - Data Analytics; DT5024 - Artificial Intelligence
Assessment methods
Assessments will include a range of work including, portfolios, artefacts, presentations as well as reports and open book exams to support students in providing many forms of evidence for academic and professional development, and these assessment methods are reflective of real work situations.
Tuition fees
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The Uni
Swindon and Wiltshire Institute of Technology
New College Swindon
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