Data Science MSc

Data Science, in particular coupled with Artificial Intelligence, promises to provide the tools for enhanced technologies, business models and decision making across a large number of fields, from industrial automation, manufacturing, transport, banking, cybersecurity to health and social care. Through working on real-world datasets and industry-simulated projects, you'll master the necessary skills and knowledge to apply the latest in advanced Data Science tools and techniques such as Data Engineering and Deep Learning.

The course is co-designed and co-delivered by Cambridge Spark, a training provider that specialises only in Artificial Inteligence and Data Science'. The course is delivered online and includes a two-week hackathon-style bootcamp.
Data has fast become one of the world’s most valuable resources, and the World Economic Forum estimates that by 2025 there will be 463 exabytes of data created globally every day. Moreover, according to the 2019 report, “Dynamics of data science skills,” demand for data scientists and data engineers has tripled over the past five years, rising 231%. Meanwhile, average salaries for these roles are £64,376, up 22% over the same period. And if the growth of data science proceeds as estimated, these figures are set only to increase further.

Employers have highlighted the importance of data science and its potential to revolutionise many 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.

It is unsurprising then that this fast-growing universal industry creates exciting jobs every day across the globe, and with a Data Science MSc from ARU, you could be well on your way to a rewarding and in-demand career in the world of data science.

Modules

Exploratory Data Analysis

This module provides a sound basis in data analysis. You will be introduced to feature engineering and selection, including variance thresholding, correlation and checking for multicollinearity. You'll be introduced to the principal component analysis (PCA) including making sense of high dimensional data, dimensionality reduction, intuition linear algebra background and algorithm, using Pandas and Scikit-learn.

Machine Learning Techniques

Machine learning is a sub-discipline of Artificial Intelligence that deals with teaching the computer to act without being programmed. In this module you will learn about the tools and algorithms that can be used to create machine learning models. You’ll examine big data and their economic, legal and ethical aspects, along with data acquisition and pre-processing methods that are used to make these suitable for machine learning algorithms. You will also look into how large data sets should be divided into a training set and a test set.

Data Engineering and Big Data

Data engineering is a process to design, build and manage the information or "big data" infrastructure. It gives an understanding of how to develop the architecture that helps analyse and process data in the way the organisation needs it. You will examine the entire data lifecycle, including data creation, modelling, representation, analysis, maintenance and disposal. As the majority of data is stored in databases, this module will provide an introduction to various types of databases and discuss the methods to ensure clean, reliable, and performative access to data.

Deep Learning and Applications

Deep learning and its applications have revolutionised numerous fields in recent years. This module explores the two main areas of neural networks and deep learning. You'll start analysing the structure of neural networks, from the theoretical aspects to the practical implementations. You will then move to training a neural network using Keras. Then, you will explore the convolutional neural networks (CNNs) and introduce deep learning from the convolutional operator and stacking convolutional layers to regularisation, batch normalisation and data augmentation.

Advanced Time Series Analysis

The module will provide an introduction to the emerging techniques which allow data scientists and practitioners to study and investigate nonlinear time series. It will offer a collection of tools designed to dive deep down into underlying structures of data, allowing future data scientists to detect whether stochastic or deterministic dynamics most likely drive observed complexity. In other words, this module will teach you how to become a 'data detective' accumulating hard empirical evidence supporting your modelling approach.

Machine Learning Bootcamp

The module builds on previous knowledge gained in the course. It aims to test, through real life scenarios, as part of practical projects, concepts of artificial intelligence and machine learning techniques that enable a system to learn from data rather than through explicit programming. These techniques are becoming essential in business operation innovation and more generally in generating more efficient workflows.

Major Project

This module supports you in the preparation and submission of a Master’s Stage Dissertation. The topic may be drawn from a variety of sources including: school research groups, previous/current work experience, the company in which they are currently employed, a lecturer suggested topic or a professional subject of their specific interest (if suitable supervision is available). The chosen topic will require you to identify / formulate problems and issues, conduct literature reviews, evaluate information, investigate and adopt suitable development methodologies, determine solutions, develop hardware, software and/or media artefacts as appropriate, process data, critically appraise and present your findings using a variety of media.

Assessment

This course is assessed through a variety of methods, including time constrained assessments, coursework assignments and a project.

The dissertation project and module case studies assess your ability to analyse situations, identify key issues, select, synthesise and apply techniques and skills from different modules and to be able to evaluate the appropriateness of their solutions when compared to industrial practice.

The dissertation artefact will be based on a real-world scenario related to or part of an actual piece of project work in a company.

Dr Domenico Vicinanza

Having received his MSc and PhD degrees in physics, Domenico worked as a scientific associate at CERN for seven years. His research there mainly focused on the development of an innovative time-of-flight detector for one of the biggest High-Energy Physics experiments for the Large Hadron Collider in Geneva.
As a music composer and researcher in auditory display, Domenico worked with organisations like CERN and NASA, creating music from scientific data.

How techniques you will learn are making an impact

Using extraction and modelling techniques that are taught in the Data Science MSc, Domenico and other academics used an imaging tracking system to study the movement of cloud formations predicted by NASA's Pleiades supercomputer, and then filtered this data to extract patterns.

They then mapped these patterns to musical intervals, creating the melodies and short extracts have been used to produce the ringtones, while the text alert melodies are based on the central processing unit capacity of Pleiades.

The research involved was part of the celebration of NASA’s Pleiades supercomputer and its role in the successful Mars InSight mission.

Read the press release 

Our Data Science MSc is studied 100% online and includes a two-week hackathon-style bootcamp in year two

Modules will be delivered via Cambridge Spark's innovative AI-powered learning platform K.A.T.E.® (Knowledge Assessment Teaching Engine), which provides instant feedback on code within an industry-simulated environment.

You'll also use Canvas for instant access to study materials, forums, and support from tutors and classmates, as well as enabling easy submission of your assignments. Canvas can be accessed from your phone, pc or tablet at home or on the move.

On successful completion of your studies, you’ll be invited to attend a graduation ceremony on campus. If attending the ceremony in person is not possible then we’ll arrange to have your certificate sent to you.

To help you land your dream job, our Employability Service will work with you throughout your time at ARU and after you graduate.

We offer:

• careers advice, including one-to-one online and telephone appointments with our experienced advisers
• help with your CV, job searches, applications and interview preparation
• an online portal packed with useful careers resources
• our Employability Programme, which helps you hone the skills employers say they want in graduates.

Fees

The full tuition fee for this course is £14,500.

The tuition fees you pay each year for the full Data Science MSc will be £7,250. The course is studied over 2 years.

Accredited Prior Learning may reduce the tuition fees. This will be confirmed once your application has been submitted.

Funding

Your course can be partially funded by the Postgraduate Student Loans now available (subject to eligibility).

We offer payment by instalments, so you can spread the cost of studying with us.

For military students: You can use your ELCs towards this course. Anglia Ruskin University is a recognised ELCAS provider (number 1007). Please contact your Learning Centre for details of ELC, eligibility and how to apply.

For more information on how you fund your studies please see our funding page.

Our online Data Science MSc course gives you the chance to grow your skillset and become part of a fast-growing industry that is shaping the future. 

As data and artificial intelligence become crucial tools in the technological and analytical developments at the heart of business, industry and society, data scientists have the power to harness these tools through skilled insight to pioneer bright solutions. And while there is a rising demand for data scientists across industries, there remains a shortage of required technical talent in the job market. 

A Data Science MSc will perfectly position you to take advantage of this skill gap and enable you to make the most of these opportunities. On this course, you’ll develop your analytical faculties in the fields of data, AI and information technology, using industry-based tools and techniques to lay the groundwork for a vibrant career.

Data science is becoming an increasingly vital tool for businesses and organisations in private and public sectors. And as it becomes more widely utilised, career opportunities are opening in fields as diverse as retail, ecommerce, health care and education, to name just a few. 

And those with the right skills have the power to transform industries. With the analytical and practical knowledge you’ll master as part of our Data Science MSc, you can build a dynamic and futureproof career at the forefront of advancement in your industry, using data to drive practical and effective solutions. 

Amongst the most common careers for data science graduates are Machine Learning Engineering and Big Data Engineering, but opportunities are not limited there. And with an MSc from ARU, you could be well on your way to a promising career in a thriving sector.

The ability to analyse and process data is at the heart of this discipline. 

And as part of our online data science degree, you’ll learn how to master complex data analysis to solve problems, strategize and drive decision making. 

You’ll also study machine learning, a branch of artificial intelligence which uses data to develop intuitive computer systems which drive their own improvement and learn how machine learning models are developed and implemented through the use of tools and algorithms. 

Through this course, you will also gain a deeper understanding of the role of data science in social progress, examining the issues of ethics and legality in relation to this growing field of AI. The course will also give you the chance to explore data engineering and ‘big data’ infrastructures – how these are constructed to store and utilise information, and the technical skills required for this type of data handling. 

You’ll also gain hands on experience with neural networks and develop software skills through the use of programmes such as Keras, and in your second year, you will also have the opportunity to put your skills into practice in a simulated environment thanks to the two-week Bootcamp co-ordinated by Cambridge Spark. The Bootcamp uses real life scenarios and data examples to recreate realistic Data Science environments. 

With your Master’s Stage Dissertation, you’ll also have the chance to explore topics of your choosing in greater depth, whilst honing your research, investigative, evaluative and problem solving skills.

And because this course takes place 100% online, our distance learning format will teach you a number of highly valuable soft skills such as time management, independence and organisation, thanks to the uniquely flexible mode of learning. 

Our innovative online Data Science MSc is designed and delivered in collaboration with Cambridge Spark, leading pioneers in education technology. You’ll also benefit from our exceptional course tutors, who offer a range of industry knowledge and expertise to guide you through your studies. 

Like all of our distance learning courses, this two-year degree, which takes place 100% online, is designed for full flexibility to allow you to juggle your commitments alongside your studies whilst creating an immersive virtual learning environment through our teaching platforms. These include Cambridge Spark’s own K.A.T.E.®, the Knowledge Assessment Teaching Engine, and Canvas, our online Learning Management System.

You’ll also have the opportunity to experience our unique Bootcamp programme towards the end of your two-year course – a hack-a-thon style event allows you to work on real-world datasets and simulations to grasp the practical applications of the skills you’ll have developed on this course, offering a unique development opportunity to solidify your learning in a simulated environment. 

Apply today and take your first step into the future with a degree in Data Science. 

Find out more about this course and distance learning on our blog: 

• 5 Ways Data Science is Changing the World 

• Can Distance Learning Replace Traditional Classes? 

• Want to Steer Your Career In Tough Times? Try Distance Learning