Everything you need to know...
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What is the fee?
Home: £12,440 for the course
International/EU: £20,100 for the course -
How long will I study?
2 Years
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Where will I study?
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When do I start?
September 2026
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Placement year available?
Yes
Course summary
- Learn how to use software such as SAS, R and Python.
- Gain the skills and knowledge to statistically model data.
- Learn how to use the Bloomberg portal to access live industry data.
- Develop an understanding of investment skills and risk management.
- Understand portfolio management to achieve financial goals.
Our Data Analytics with Banking and Finance course shows you how to address business challenges by using analytics tools to manipulate and investigate live industry datasets. You’ll further develop your skills in areas such as investment management, finance stability, sustainability and strategy.
Come to an open day
Find out more at our postgraduate open days. Book now for your place.
How you learn
This course focuses on developing core competencies in data management and analytics while integrating key financial principles. You’ll use industry-standard software and packages – including the Bloomberg portal – to access live industry data for further analysis. Through this dataset, you’ll be tackling real-world challenges as part of the course.
The combination of teaching methods applied across the course will allow you to develop a range of skills – from practical implementation to problem-solving activities and teamwork.
You’ll also develop your research skills so you can undertake a significant piece of work related to the discipline. You get to choose your dissertation project – which allows you to further specialise in an area you might like to pursue as a career – while being supported by a dedicated academic supervisor.
You learn through:
- Lectures
- Hands-on tutorial sessions and seminars
- Regular feedback
- Teamwork
- Group/project-based learning
- Critical thinking and problem-solving
- Practice-based applied learning
- Discussions
- Self-study
Key themes
The course starts by teaching you core skills across data analytics, including your skills in programming across languages such as R and Python. Using SAS, you’ll also develop an understanding of statistical modelling – covering areas such as supervised and unsupervised machine learning, and principal component analysis (PCA). The aim is to reduce large volumes of data into more digestible insights.
You’ll then progress your understanding of investment management and financial stability, creating and critically evaluating investment opportunities and strategies. You’ll examine and manage their risks using financial derivatives – asset exchanges and contract agreements such as futures, options and swaps. This is all underpinned by exploration of regulatory financial policies and strategies for managing environmental and social risks.
You’ll practise these skills through hands-on projects, use of the Bloomberg portal for live data, and your research-led dissertation project – preparing you for diverse roles in the finance sector.
Applied learning
Work Experience
You’ll have the opportunity to source a work placement for up to 12 months, where you’ll apply academic theory and your skills in a real-world setting. This hands-on experience will enhance your professional development and help you to make informed career choices after graduation. Throughout your placement, you’ll be supported to reflect on your experience and contribution to the organisation you work for. You'll also share your progress and achievements with your Placement Academic Supervisor as part of your final assessment.
Work placements are competitive and will require you to make formal applications to employers and be successful in securing an opportunity. The application process for placements takes place while you are a student with us. To support you in applying for placements, you’ll complete an additional placement preparation program that introduces you to the UK employment landscape and prepares you for the recruitment and assessment activities you will experience during that process. We also maintain a large database of placement offers that you can search to find opportunities most relevant to your course that you can apply for.
Students from this course have been on work placements with companies such as:
- HSBC
- Lloyds Banking Group
- DB Cargo
Networking Opportunities
You’ll have numerous networking opportunities and ways to develop your career, from career fairs and workshops to employer presentations and visits. You’ll also be able to seek guidance from professional advisers.
The course provides a unique blend of academic and practical exposure by integrating guest lecture talks and networking opportunities within the curriculum. These offer insights into the practical application of cutting-edge technologies and best practices.
Course leaders and tutors
Modules
Important notice: The structure of this course is periodically reviewed and enhanced to provide the best possible learning experience for our students and ensure ongoing compliance with any professional, statutory and regulatory body standards. Module structure, content, delivery and assessment may change, but we expect the focus of the course and the learning outcomes to remain as described above. Following any changes, updated module information will be published on this page.
You will be able to complete a placement year as part of this course. See the modules table below for further information.
Year 1
Compulsory modules
This module explores the application of statistical ideas and techniques in the analysis of data. This includes sophisticated data mining methods such as supervised and unsupervised.
You’ll study topics such as:
- The modelling cycle
- Statistical test and confidence intervals
- Data Mining Methodologies such as CRISP-DM and SEMMA
- Data Preparation and Manipulation
- Unsupervised learning and Dimension reduction techniques
- Cluster Analysis (variable and observation)
- Principal Components
- Rule association
- Supervised learning techniques
- Simple and Multiple Regression
- Logistic Regression
- Application of Regression and Logistic Regression to data mining
- Decision trees
- Evaluation of statistical modelling and data mining techniques
This module gives you a thorough understanding of financial stability, regulation, and sustainability. You’ll explore the key principles, challenges, and practices that shape financial systems. The course will help you develop the critical thinking and analytical skills needed to assess how financial policies and regulations impact stability and sustainability in the world of finance, banking and the general economy. By the end of the module, you’ll be able to evaluate the effects of financial policies on stability, manage environmental and social risks, and assess sustainability reporting frameworks.
You’ll study topics such as:
- Key macroeconomic indicators for financial stability
- Macroprudential regulation and managing systemic risk
- Understanding international banking regulations
- Managing environmental risks with sustainable finance
- Corporate governance and social responsibility
- Climate change and transition risks for finance
- Sustainable and impact investing strategies
- The role of international financial institutions
- Financial crime regulations
This module covers programming in Python and R, including key concepts of modern programming languages, such as object-oriented.
You’ll study topics such as:
- Fundamental programming concepts, such as variables, data types, operators, expressions, control structures, and loops
- Functions, methods, parameters, and arguments to organise and reuse your code
- Design and develop programmes using an algorithmic approach
- Data structures, such as lists, dictionaries, sets, and strings, to store and manipulate data
- Principles of object-oriented programming and implement classes, objects, methods, and inheritance
- Libraries and frameworks to create GUI, databases, or networking applications
This module gives you a solid understanding of investment management, focusing on concepts, theories, and practices in global financial markets. You’ll learn how to evaluate investment opportunities, create investment strategies, and manage risk using derivative instruments. By the end of the module, you’ll be able to assess investment opportunities, build and apply investment strategies, and manage risk through derivatives.
You’ll study topics such as:
- Investment analysis and building portfolios
- Alternative investments like hedge funds and private equity
- Managing bond investments and interest rate risks
- Equity valuation and fundamental analysis
- How behavioural finance and psychology affect investors
- Financial derivatives: futures, options, and swaps
- Risk management and hedging with derivatives
- How to evaluate and report investment performance
Module aim:
The aim of this module is to enhance students’ professional development through the completion of, and reflection on meaningful work experience.
A work experience will provide students with opportunities to experience the realities of professional employment and experience how their course can be applied within their chosen industry setting. The placement will:
Allow student to apply the skills, theories and behaviours relevant and in addition to their course.
Enable students to enhance their interpersonal skills in demand by graduate employers – communication, problem solving, creativity, resilience, team work etc.
Grow their student network and relationship building skills.
Provide students with insights into the industry and sector in which their placement occurs.
Help student make informed graduate careers choices.
Indicative Content:
In this module, students will undertake a work experience (minimum duration and expectations as per HESA regulations – clarified on assignment brief/Blackboard) which is integrated, assessed and aligned to their studies and appropriate for their level of study.
Their personal Placement Academic Supervisor (PAS) will be their key point of contact during their work experience and will encourage and support students to reflect on their experience, learning and contribution to the organisation they work for.
To demonstrate gains in professional development, students will be required to share their progress, learning and achievements with their Placement Academic Supervisor and reflect on these for the summative piece of work.
Final year
Compulsory modules
This module will apply the technical knowledge and understanding developed across the course into an original research project. This will include critical and ethical analysis of literature, synthesising the findings and tailoring them to the specific context of their research projects using a suitable research methodology.
You’ll study topics such as:
- Critical and ethical review of the literature
- Selection and application of appropriate research tools, techniques, or methods
- Design and development of the artefact/prototype
- Testing and user evaluation
- Critical reflection – evaluating the project deliverables and project success/failure
- Legal, social, and ethical considerations in the design and development of computer-based systems
- Sustainable development and deployment
This module develops skills to design and conduct rigorous research projects in computing.
You’ll study topics such as:
- Identify research problems: Explore current challenges and opportunities in computing to uncover relevant research areas
- Formulate research questions: Craft precise questions, aims, and objectives aligned with identified problems
- Review literature and artifacts: Critically analysing existing research to synthesize knowledge and identify gaps
- Propose research methods: Evaluate and select appropriate research techniques specific to your computing area
- Communicate research proposals: Craft comprehensive proposals that meet professional, legal, and ethical standards
Future careers
The course prepares you for computing employment by integrating technical content that’s aligned with industry demands, ensuring relevance. We continuously adapt to industry advancements, collaborating with subject matter experts and industry connections to keep up to date with the latest industry trends and requirements.
This course prepares you for a career in fields such as:
- Marketing and customer analysis
- Investment analysis
- Digital analysis
- Data science
- Credit risk analysis
- Fraud analysis
- Big data architecture
- Business intelligence development
Previous graduates of this course have gone on to develop successful careers in senior roles and worked for companies including:
- Bank of England
- OCF
- HSBC
- INC Research
- Axis Bank
Equipment and facilities
You’ll learn across our Extended Campus of flexible physical and digital spaces – which support applied learning, working, teaching and collaboration. On campus the Computing Department will be your home space, with areas to engage in course activities and meet students, staff and employers.
On this course you’ll work with technologies such as:
- Bloomberg Portal
- SAS
- R Studio
- Python
Where will I study?
You study at City Campus through a structured mix of lectures, seminars and practical sessions as well as access to digital and online resources to support your learning.
City Campus
City Campus is located in the heart of Sheffield, within minutes of the train and bus stations.
City Campus map | City Campus tour
Adsetts library
Adsetts Library is located on our City Campus. It's open 24 hours a day, every day.
Learn moreLearn more about your department
Computing facilities tour
Take a look around the facilities and equipment in the Department of Computing at Sheffield Hallam University.
Entry requirements
All students
Normally an undergraduate degree at 2:2 or above, in a related field.
If English is not your first language, you will need an IELTS score of 6.0 with a minimum of 5.5 in all skills, or equivalent.
Additional information for EU/International students
If you are an International or non-UK European student, you can find out more about the country specific qualifications we accept on our international qualifications page.
For details of English language entry requirements (IELTS), please see the information for 'All students'.
Fees and funding
Home students
Our tuition fee for UK students starting full-time study in 2026/27 is £12,440 for the course. The tuition fee displayed above is for the full course. For this work experience route, your fees will be payable over two years, divided into two annual payments based on credits studied. The fee includes dedicated employability support to help you prepare for and secure work experience. It does not guarantee you a placement and if a placement is not secured the work experience fee will still be charged. If a placement is not secured you will transfer to the standard version of the course to complete your remaining credits, where the balance of your course fees will be due in year one in line with completing the course.
If you are studying an undergraduate course, postgraduate pre-registration course or postgraduate research course over more than one academic year then your tuition fees may increase in subsequent years in line with Government regulations or UK Research and Innovation (UKRI) published fees. More information can be found in our terms and conditions under student fees regulations.
International students
Our tuition fee for International/EU students starting full-time study in 2026/27 is £20,100 for the course. The tuition fee displayed above is for the full course. For this work experience route, your fees will be payable over two years, divided into two annual payments based on credits studied. The fee includes dedicated employability support to help you prepare for and secure work experience. It does not guarantee you a placement and if a placement is not secured the work experience fee will still be charged. If a placement is not secured you will transfer to the standard version of the course to complete your remaining credits, where the balance of your course fees will be due in year one in line with completing the course.
Scholarships and financial support
Find information on scholarships, bursaries and postgraduate student loans.
International scholarships up to £3000 ›
Alumni scholarships up to £2000 ›
Postgraduate loans for UK students ›
Additional course costs
The links below allow you to view estimated general course additional costs, as well as costs associated with key activities on specific courses. These are estimates and are intended only as an indication of potential additional expenses. Actual costs can vary greatly depending on the choices you make during your course.
General course additional costs
Additional costs for School of Computing and Digital Technologies (PDF, 600.1KB)Legal information
Any offer of a place to study is subject to your acceptance of the University’s Terms and Conditions and Student Regulations.
