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MSc Data Science and Analytics

Turn big data into even bigger insights and gain the skills to drive your data analytics career forward on this 100% online degree. Please note this degree is currently subject to approval.

Start Dates: January, May, September

Duration: 1 year full-time, 2 years part-time

Study Mode: Online

Fees: £11,520 (regional discounts available)

About the programme

Global data is growing at rapid speed and so is the need for professionals who can cut through the noise. Unlock the power of data with our online MSc in Data Science and Analytics. Blending hands-on practical training with academic theory taught by some of the world’s leading academics, you’ll be equipped with the skills to turn complex datasets into insights that drive innovation across sectors including retail, finance, healthcare, tech and government.

From day 1, you’ll work with cutting-edge technologies like Hadoop, Spark, Tableau, Python and R and acquire skills in quantitative analysis, data visualisation, big data processing, machine learning and more, leaving you ready to make an impact and shape your future in an increasingly data-driven world.

Modules

All learning is delivered online to fit around your work and personal commitments. You’ll complete eight core modules and a final dissertation, combining theory and practice to prepare you for a career as a data expert.

This module gives you the opportunity to reflect on the concepts, theory and appropriate use of large-scale storage and processing infrastructures, before designing and planning your own solutions. You’ll also review, design and plan various analytic methods, techniques and algorithms used to generate insight from data, before reflecting on their ability to deliver accurate predictions.

How do you turn data into valuable insights? On this module, you’ll learn how to design and implement effective visualisation methods, algorithms and techniques to generate value and insight from data, leaving you ready to critically reflect on current data visualisation methods. 

What can we learn about digital information from the way it’s handled? This module identifies what existing research has to say about the governance of digital information. You’ll consider the legal, social and ethical concerns of using digital systems and critically reflect on the implications of adopting digital technologies in the modern working environment. 

This module equips you with an understanding of innovation in digital business. You’ll gain the skills needed to implement digital business improvement and change while critically evaluating theory and practice. 

This module teaches you how to design and implement methods to prepare data using advanced statistical techniques. You’ll then be able to apply these methods to real data to generate insight and design your own data management frameworks. 

Bring your knowledge to life through your very own research project. Choose an area of study, formulate research in response to a problem area, using your critical thinking, evaluation and practical skills to shape your research. 

What insights can we draw from the data around us? On this module you’ll consider and reflect on distributed data analysis methods before designing and implementing your own data analytics solution using statistical learning and distributed computing technologies.

This module gives you the opportunity to evaluate data quality, critically compare current statistical analysis methods for data exploration and create your own tailored analysis plans for data preparation, exploration and management. 

Demonstrate the knowledge and skills you’ve gained on this degree programme through a dissertation. You’ll propose, present and evaluate the solution to a research problem or question within a specific field of study, applying the appropriate research and data collection methods to form a complete report. 

Entry requirements

To join this programme, you’ll need:

  • A 2:2 or above UK Honours degree (or international equivalent) from a scientific, engineering, or a numerate subject.

All modules and assessments are delivered in English, so you’ll need to meet our English language requirements. We accept a range of qualifications, including:

  • IELTS: 6.5 overall (minimum 6.0 in all areas)
  • Pearson (PTE): 59 overall (59 in all subscores)
  • BrunELT: 63% overall (minimum 58% in all areas)
  • TOEFL iBT: 90 overall (minimum 20 in each section)
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Power your future in data

Global excellence: Join a top-ranking department led by faculty who are recognised among the world’s top 2% of scientists. 

Industry-relevant curriculum: Designed with input from industry professionals, learn the skills employers need.

World-class technical training: Put theory to practice with tools including Hadoop, Spark, Tableau, R, Python, and SAS.

Tailored academic support: Get access to mentoring, guidance and employability services from day 1.

Start your degree journey

In-demand data skills that drive innovation

Data science 

Explore key concepts from the disciplines that define modern data science. 

Data analysis

Learn how to turn a critical understanding of data into clear insights for industry innovation.

Strategic tools

Apply data science tools and techniques to problems in social, business and scientific domains.

Digital problem-solving

Address industry challenges with applied data science and evaluate its effectiveness. 

Technical research

Conduct, report on and evaluate research related to problems and challenges in data science.

Professional agility

Demonstrate professional competence in data science and analytics.

Unlock opportunities in data

Led by industry-leading academics, this degree programme prepares you for a rewarding career with leading employers like Accenture, AstraZeneca, AXA Insurance, British Airways, PayPal, Experian, Capgemini, FICO, GE Healthcare, HSBC and more.

As a Brunel online graduate, you’ll be prepared to step into roles including:

  • Data scientist
  • Analytics consultant
  • Business analyst
  • Clinical data scientist
  • Forecast analyst
  • Customer insight analyst
  • Quantitative analyst 
  • Developer 
  • Enterprise architect 
  • Web analyst

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