Data Analytics MSc - January 2022

This programme will also be available starting in January, and we will be accepting applications shortly.

Data plays an increasingly important role in modern life, yet the talent to extract information and value from complex data is scarce.

This course is for you if you want to use your mathematical and numerical skills to build your career. During the course you will develop an informed and critical appreciation of scientific and industrial developments in data science and analytics.

What you’ll learn

You’ll gain a thorough grounding in the fundamental concepts to understand the data lifecycle, including problem formulation, data collection and cleaning, exploratory data analysis and visualisation, statistical inference and decision making. A range of methods will be covered including algorithmic and computational modelling and statistical machine learning.

You’ll also undertake a research project on a subject of your choice, where you’ll apply the knowledge you’ve gained to produce high quality independent work.

Modules

• Statistical Machine Learning,
• Specialist Research Skills and Techniques,
• Algorithmic and Computational Mathematics,
• Understanding Data,
• Probabilistic Modelling,
• Data Science Programming,
• Artificial Neural Networks,
• Network Science
• Research Project (60 credit module)

• We expect applications from graduates of Mathematics, Statistics, Computer Science, Engineering, Physics or Data Science or related disciplines, with a qualification equivalent to a UK BSc with Honours at 2:2 or higher. Evidence of knowledge of Mathematics and Programming should also be provided when the degree is not in Computer Science (i.e. transcript of degree programme or work experience). When a transcript is provided, the Mathematics and Programming grades should be equivalent to UK 60% or higher. Candidates may be interviewed prior to the offer decision.

As well as:  

• Two professional references – at least one must be from an academic referee
• A completed application form.

For International Students:

• An official academic transcript, with an official English translation, of your university grades to date
• Applicants whose first language is not English will be required to provide evidence of an English language qualification. Find out more about our English language requirements
• For more information about qualifications view our Aston in your future webpage. 
• Pre-sessional English language programmes are available for good applicants whose English qualification falls just short of these requirements. Information on visas for international students

Applicants with extensive work experience:

We recognise the value of extensive professional experience. If you do not have the academic qualifications, but have extensive and relevant professional experience and a proven ability to succeed, we would welcome your application.

The information contained on this website details the typical entry requirements for this course for the most commonly offered qualifications. Applicants with alternative qualifications may wish to enquire with the relevant admissions teams prior to application whether or not their qualifications are deemed acceptable. For less commonly encountered qualifications this will be judged on a case-by-case basis in consultation with the academic admissions tutor.

 
Our Data Analytics masters course combines tutorial-based teaching with self-directed study, so you’ll be equipped with the relevant learning materials and then given regular tutorials where you have the opportunity to discuss and demonstrate what you’ve learned alongside potential applications. 
 
The learning hours include one hour of face-to-face tutorial time per week, per module, along with online activities, reading, independent study, and opportunities to reflect on assignment feedback.  
 

The taught modules will be assessed via coursework, and the project via a combination of dissertation and viva examination. 
 

Tuition fees are reviewed annually and may increase in subsequent years in line with inflation linked to the Retail Price Index (RPI) to take account of the University’s increased costs of delivering the Programme. When undertaking a placement year a placement year fee applies.

More information on fees

Scholarships

You can find out more about our Postgraduate scholarships for International students here. If you are a UK or EU student, please email seaspgtaught@aston.ac.uk for information on funding.

Our graduates leave with the in-depth knowledge and skills they need to develop careers across the field of data science.

Students on similar programmes have gone on to roles including: finance and investment analysts and advisers; IT business analysts, architects and systems designers; management consultants and business analysts; as well as programmers and software development professionals at some of the world’s most prestigious companies.

International students

Aston University is a diverse, close community and welcomes international students on many of our postgraduate programmes. Students from over 120 different countries chose to study with us every year and Aston is not only a great place to study, based in the centre of Birmingham it’s also a great place to live.

Post-study work visa

Aston University welcomed the creation of a new immigration route which will enable international students to remain in the UK for two years after they have completed their studies to find work. The new post-study work visa will apply to international students starting undergraduate and postgraduate courses from 2020. Click here for more information on post-work visas

Why study Data Analytics at Aston? 

In the information age we live in, understanding data and how to use it is increasingly important. The skills and knowledge you gain are in high demand across many sectors, which will offer you many potential opportunities.  

What will I be doing on the Data Analytics course at Aston? 

You’ll develop an informed and critical appreciation of scientific and industrial developments in data science and analytics through a combination of modelling, computation and hands-on project experience.