Applications of Data Science (Online)MSc

You will study topics online with academic experts, from artificial intelligence and statistical modeling to ethical data collection and legal frameworks. Graduate ready to apply key data science principles and can look forward to roles in industry, business, academia, research, or government.

Why study Applications of Data Science MSc (Online) at Birmingham?

When you choose Birmingham, you are choosing to study at an outstanding University, renowned for changing lives and transforming society. For more than a century, we have encouraged bold, independent thinking and provided a learning experience built on some of the world’s best research.

• Complete the programme in as few as 30 months, part time
• No application fees or standardised test scores required
• Flexibility to choose from three start dates per year (March, June, October)

• Built around the United Nations’ sustainability goals, the programme is designed to equip students with the data science skills to analyse, provide critical insight, and communicate conclusions to drive action.
• Study our continually updated curriculum and degree programmes that align with industry needs, helping you stay relevant in the global job market
• Discover the intersection of data science and sustainability. Explore a module dedicated to how data can be used to better understand populations, natural resources, climate change, and more.
• Become an in-demand professional in the industry

• Evaluate and classify different types of data through comprehensive understanding, to evaluate and critically select appropriate associated methods for capture, storage, and analysis
• Make sound judgements and take appropriate actions based on critical awareness and understanding of ethical and legal framework for data handling
• Form appropriate new hypotheses and/or original research questions for investigation
• Make sound judgements of the quality and robustness of data sources and the outputs of analysis based on critiques of methodology and available information  
• Successfully apply a variety of statistical, algorithmic, and graphical approaches informed by the forefront of the discipline, area of study, and professional practice
• Perform a comprehensive analysis and integration of data from different sources for combined analysis
• Draw valid conclusions on complex issues from analysis including evaluation of appropriate associated uncertainty measures and communicate those conclusions to specialist and non-specialist audiences

Economics and Finance

The assessment of the state of the economy, and policies for economic development are driven by theory and data as well as by political ideology and imperative. The module will explore methods, evaluation of models, and empirical studies in economics and in finance. Students will gain experience through practice of formulating and estimating models, interpreting results, and making qualified predictions.

This module will therefore address contributions and issues pertaining to UN Sustainable Development Goals in eradicating poverty, decent work and economic growth, and reduced inequalities.

Examples will be drawn from datasets and case studies from fields which include but are not limited to employment, productivity, activity, banking, finance, and trade. Datasets will be drawn from international and publicly available sources, and students will be encouraged to bring their own.

People and the Earth

Population, resources, climate change, and climate adaptation are hot topics around the world, the subject of global conferences and local action, intimately related to local context and regulation. The types and sources of data, the methods used to analyse them, and the ethical and legal frameworks within which data is accumulated, analysed, and disseminated are as various as the datasets and questions that data analysts may be asked to evaluate. In this module students will learn about the nature of data and how to analyse it, as well as the wider contextual frameworks.

This module could therefore address contributions and issues pertaining to UN Sustainable Goals in good health and wellbeing, gender equality, clean water and sanitation, affordable and clean energy, and sustainable cities and communities.

Examples will be drawn from datasets and case studies from fields related to the sustainable development goals. Datasets will be drawn from international and publicly available sources, and students will be encouraged to bring their own.

Medicine and Healthcare

Examples may be taken from diverse sources from population-level studies to specific technologies such as magnetic imaging. Stories of correlations between health outcomes and human behaviour and/or external factors are common; what is often less clear in the reporting is understanding of the potential impact on the individual. Confusion between correlation and cause, clarity over the strength of a correlation, and a lack of quantification of risk or benefit are common.

This module will therefore address contributions and issues pertaining to UN Sustainable Goals in good health and wellbeing and reduced inequalities.

Examples will be drawn from datasets and case studies from fields which include but are not limited to clinical trials, population health records and clinical data datasets will be drawn from international and publicly available sources, and students will be encouraged to bring their own.

Education for All

Literacy, numeracy, understanding of community and culture, life-long equitable opportunity, citizenship and skills: there is no shortage of data on education, and there is no end of debate on what an effective and desirable education system might look like, in principle and in practice. This is an opportunity for students to engage with debate and with differing perspectives, and to seek multi- and interdisciplinary insights.

This module will therefore address contributions and issues pertaining to UN Sustainable Goals in quality education, gender equality, and reduced inequalities.

Examples will be drawn from datasets and case studies from fields which include but are not limited to opportunity, participation, satisfaction and achievement in all forms of education. Datasets will be drawn from international and publicly available sources, and students will be encouraged to bring their own.

Industry 4.0 & 5.0

Data, often collected from multiple and distributed sources, is central to process optimisation, the realisation of smart factories, leading to improvements in efficiency and optimisation of resources. These are central features of Industry 4.0. Industry 5.0 will further address the minimisation of waste and of environmental impact, and flexible production systems arising from the collaboration between the skill sets of humans and advanced machines. There are clear links to employee satisfaction and human wellbeing in the development of Industry 5.0.

This module will therefore address contributions and issues pertaining to UN Sustainable Development Goals in good health and wellbeing, industry, innovation and infrastructure, responsible consumption and production.

Examples will be drawn from datasets and case studies from fields which include but are not limited to additive manufacture, safety-critical decision-making, timetabling and scheduling, health and safety, quality control and testing. Datasets will be drawn from international and publicly available sources, and students will be encouraged to bring their own.

Science and Research

Our technological society is built upon scientific methods, including the design of experiments and hypothesis testing in the physical sciences, while our understanding of people and culture is informed through carefully designed methodologies in the social sciences. One difference between the two is the permeability of the boundary that investigators can draw around the system of interest. Science of both kinds seeks to understand that which exists. Understanding is learnt and developed by people throughout their lives; curiosity, knowledge, and understanding are characteristics of humanity.

This module will therefore address contributions and issues pertaining to UN Sustainable Development in good health and wellbeing, and quality education.

Examples will be drawn from datasets and case studies from fields which include but are not limited to physical sciences including astronomy and particle physics and social sciences including psychology. Datasets will be drawn from international and publicly available sources, and students will be encouraged to bring their own.

Dissertation for Advanced Data Science

This module enables the student to demonstrate professional competence in a substantial data science task and to apply material learnt in other components of the degree programme. Projects are chosen from staff suggestions or are developed from the student's original idea. Projects may involve co-supervisors from multiple disciplines, or be completed in industry under the lead supervision of an academic member of staff.

The Institute for Data and AI is a hub for collaborative research and education at the University of Birmingham.

The Institute is developing and fostering a culture of continuous interaction to address important challenges in areas including sustainability, equality, health, and data-driven science.

Entry requirements for international applicants

Students at the University of Birmingham are from more than 150 countries. As such, we welcome postgraduate applications from candidates with a range of overseas qualifications. Search the entry requirements for your country to find the grade and qualifications we will consider.

English language requirements

If you are an international student, you will need to demonstrate you have a suitable level of English proficiency, usually through the form of an IELTS or equivalent qualification or a Presessional English course.

For this course we require IELTS 6.5 with no less than 6.0 in any band, which is equivalent to:

• TOEFL: 88 overall with no less than 21 in Reading, 20 Listening, 22 Speaking and 21 in Writing
• Pearson Test of English (PTE): Academic 67 with no less than 64 in all four skills
• Cambridge English: C1 Advanced - minimum overall score of 176, with no less than 169 in any component
• LanguageCert ESOL SELT (UKVI): B2 'Communicator' with no less than 33 in each skill

English Presessional Programmes

If you have a conditional offer for Birmingham where English is a requirement, you can take a Presessional English course as an alternative to retaking IELTS or a similar qualification. We offer on-campus courses all year round starting from September including additional online courses in the summer term.  Teaching takes place in small classes with no more than 18 students to maximise class participation.

Please note that fees are the same for UK and non-UK residents alike. The University of Birmingham is committed to providing accessible education pathways, and this fee structure enables international students to more easily access our research-informed, employability-driven programmes.

Funding options

• Employer support: Many employers offer partial or full financial support for employees pursuing a degree. Check with your manager or HR representative.
• Private education loans: If you need additional financial assistance, research other education loan lenders to determine if a private loan is best for your situation.

Postgraduate Masters Loan

To help with the cost of studies, this loan is available to all UK students. You can use this loan towards fees, maintenance or other costs at your own discretion. It’s available for all full-time, part-time and distance learning Masters programmes, as long as you don’t already have a Masters qualification (or equivalent).If you’re a student from Wales, Scotland or Northern Ireland, you can apply for Masters loans from your country’s government.

Scholarships

To help you afford your studies, we’ve put more than £33 million into student support and scholarships. We also offer a range of advice on searching for funding and managing your finances.

• Online application (no fee);
• Contact details for one referee who has knowledge of your professional or academic (if you are a recent graduate) ability;
• Please note that the contact email address of the referee must be a professional email address and not a personal one.
• Personal statement including a recommended 500 words outlining why you are interested in applying for this programme;
• Evidence of your English-language level no older than two years (if English is not your first language).

The programme is not designed for recent graduates of Computer Science but could be taken by those returning to study. This programme is specifically designed for those from a numerate discipline. However, applicants from other disciplines who have been working in a related sector involving programming and numerate skills will also be considered.

Applicants are required to have proficiency in statistics and probability as well as linear algebra. Unqualified applicants must take prerequisite courses in linear algebra or statistics to fulfil this requirement.

Statistics and Probability

• Prior introduction to probability
• Prior introduction to a high-level scientific programming language (e.g., Python or R)
• Familiarity with fundamental concepts from calculus, like derivatives and integrals
• Familiarity with basic statistical concepts and techniques, like descriptive statistics, histograms, measures of central tendency, hypothesis testing, confidence intervals, p-values, and sampling

Linear Algebra

• Proficiency in Algebra of matrices, including:
• Concepts of matrix multiplication
• Matrix inverses, bases, norms, and inner-products
• Eigenvectors

Applicants are recommended to have proficiency in programming

Programming

• Prior experience in programming languages, such as Python or Java
• Competencies and skill sets in data types, control structures, I/O functions, and basic visualization
• Prior experience with scripting, test-driven development, and version control systems

Skills Refresher Courses

If you need to build or brush up on any of the skills above, we encourage you to take the following refresher courses.

These self-paced online courses are free to audit. However, if you need to demonstrate your competency in a particular area, you may want to pursue the verified track of that course, which comes with an enrollment fee. Verified courses on edX give you access to graded feedback and the opportunity to receive a verified certificate of completion – which indicates you have earned a passing grade and thus understood the material.

Courses in Programming

• Python for Data Science
• Python Basics for Data Science
• R Programming Fundamentals

Courses in Statistics and Probability

• Statistics 1 Part 1: Introductory Statistics, Probability, and Estimation

Courses in Linear Algebra

• Linear Algebra I: Linear Equations
• Linear Algebra II: Matrix Algebra

If you take these courses before you apply to the MSc Applications of Data Science course, we encourage you to include in your application a list of the courses you have completed, along with any verified certificates you’ve earned. We also encourage admitted applicants to refresh their knowledge of these topics before starting classes.

From application through to graduation, we will support you throughout your exciting online learning journey. As an online postgraduate student, you will receive the same level of support as students studying on campus.

The online learning platform is a place to learn and engage with a local and global cohort of students, and University staff. Approachability is a core value in the support offered, with a human face available to listen and respond to feedback.

Careers and employability support and advice is available after you graduate from the programme – as well as a global alumni network with events in various countries, including China and India.

University-provided services that are available to online students include

• The Careers Network: Benefit from tailored career support services to help you explore your options, plan your next steps, and identify and apply for opportunities that are right for you.
• Graduate School careers support: Access online resources, language and skills training, personal development workshops, and Development Needs Analysis to support skills development.
• Student Help: Reach out for online assistance and information, and connect with your academic tutor throughout your studies.
• Wellbeing support: Contact the confidential service to talk to a professional counsellor or wellbeing advisor for one-to-one sessions and online counselling, or join a support group.
• Dedicated admissions support: Experience a straightforward process for admissions and enrolment, with guidance from a dedicated admissions advisor.
• Comprehensive career resources: Access career tools, such as CV templates, job boards, and workshops, all of which can help you explore career options, find relevant positions, and work towards a fulfilling career.
• Student success planning: Connect with a dedicated student success advisor who will assist with programme planning and registration, help you manage your time, and serve as your partner throughout the programme. 

Careers Network

Get ready for tomorrow, with advice, guidance and opportunities at every step of your studies. From developing new skills to preparing for a PhD, our Careers Network can help you gain an advantage in the job market or advance in your field.

Whatever you plan to do after your degree, the Careers Network offers a range of events and support services including networking opportunities, career coaching, one-to-one guidance, careers fairs and links with leading graduate recruiters. We also offer subject-specific careers consultants and a dedicated careers website for international students.

As one of the largest providers of distance learning in the UK, we offer you a prestigious online education that matches the on-campus experience, taught by our same expert professors and lecturers.

Programmes are designed to encourage participation and connectivity through the use of video lectures, case studies, interactive assignments, digital resources, and peer-to-peer social interaction.

You have the flexibility to study from wherever you are in the world, control your daily schedule, and still benefit from the academic, wellbeing, and career support as part of our global postgraduate community.