MSc Digital and Technology Solutions (Data Analytics)
Degree Apprenticeship
Overview
Grow and retain specialist data science talent in your organisation with our Masters-level Digital and Technology Solutions Specialist Degree Apprenticeship. Maximise the potential of the Apprenticeship Levy for a cost-effective way to address the emerging demand for big data analytics.
This cutting-edge two-year course is taught via a unique blend of immersive teaching weeks, online study and a hackathon-style bootcamp which simulates real-world environments.
The assignments and assessments for all modules are contextualised to the workplace environment, allowing you to develop your people whilst simultaneously impacting positively on your organisation.
Suitable for
The Masters is suitable for a number of full-time employees working in relevant roles, including new hires, graduates and current employees which already hold a bachelors degree, and can write and execute Python code at an intermediate level.
Modules
Year two
- Deep Learning and Applications
- Advanced Time Series Analysis
- Machine Learning Bootcamp
- Major Project
Year one
- Exploratory Data Analysis
- Machine Learning Techniques
- Data Engineering and Big Data
BSc (Hons) Data Science Degree Apprenticeship
Overview
Develop, reward and retain data science talent within your organisation with our Data Scientist Degree Apprenticeship. If you’re looking to grow your internal Data Science capabilities, this degree apprenticeship is a cost-effective way of using the Apprenticeship Levy to develop the data science knowledge and expertise to drive your organisation forward.
This cutting-edge course is taught as a blend of immersive teaching weeks, online study and a hackathon-style bootcamp which simulates real-world environments.
Depending on your business requirements you may also be interested in our Masters level Digital and Technology Solutions Specialist Degree Apprenticeship.
Suitable for
The Bachelors Degree Apprenticeship is suitable for new hires, graduates and current employees which are currently working in relevant roles.
No programming experience is necessary to undertake the programme as candidates will learn Python programming during the course.
Modules
Year one
- Introduction to Data Science and Programming
- Computer and Network Technology
- Workplace Skills and Learning
Year two
- Enterprise Analytics
- Computational Concepts and Algorithms for Data Science
- Mathematics and Statistics
- Software Tools and Programming for Data Science
- Data Engineering
- Data Application Programming
Year three
- Principals of Data Science
- Principals of Artificial Intelligence and Machine Learning
- Machine Learning and Data Engineering Bootcamp
- Time Series Analysis
Year four
- Data Visualisation
- Deep Learning Techniques and Natural Language Processing
- Apprenticeship Final Project (including End Point Assessment (EPA))
Introducing K.A.T.E.®
Online modules will be delivered via Canvas, Anglia Ruskin University’s digital learning platform; and K.A.T.E.® (Knowledge Assessment Teaching Engine), Cambridge Spark’s AI-powered learning and development platform, which provides instant feedback on code quality within an industry-simulated environment.
K.A.T.E.® develops learners ability to embed their newly-learnt technical skills through instant feedback upon project submissions, personalised content reccomendations, adaptive learning exercises, and metrics to diagnose and effectively benchmark their code – effectively building up their skills to produce production-ready code, whilst reinforcing industry best practices.
Learn more and start your application
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FAQs
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There is a recognised significant skills gap in Data Science-based systems specialists in the industry, nationally and internationally. This is despite data scientist roles growing over 650% since 2012, with Machine Learning Engineers, Data Scientists, and Big Data Engineers ranking among the top emerging jobs*.
*(U.S. Bureau of Labor Statistics).Employers have highlighted the importance of data science and its potential to revolutionise a number of industries, from social sciences, physics and engineering to market analysis and banking, while creating significant employment opportunities for data analysts, machine learning specialists and data specialists.
