Develop career-ready skills in data, AI, and machine learning

Data science is the process of collecting, managing, analysing, and interpreting data to identify patterns, answer questions, make predictions, and support better decisions. On this BSc (Hons) Applied Data Science degree at the University of Lincoln, you'll learn how data is processed and analysed, how computational and statistical techniques can uncover insights, and how those insights can be applied in real organisational contexts.

You'll develop practical skills across data analysis, programming, data engineering, machine learning, artificial intelligence, data visualisation, and cloud computing. You'll also explore how data is stored and managed, how analytical algorithms are developed and optimised, and how organisations can use data responsibly and securely. he course has a strong focus on applying what you learn. You'll work with real-world case studies, practical projects, and applied assessments designed to help you develop the technical, analytical, communication, and professional skills needed to work with data in the workplace.

The curriculum has been developed alongside data apprenticeship provision, helping to bring industry priorities into your learning. You'll also have opportunities to gain professional experience through an optional placement year, undertake shorter work experience or research projects, and access additional professional certifications in areas including Data, AI, Security, and Cloud.

Why study Applied Data Science at Lincoln?

Focus on applying data science in the real world
Develop practical skills that can be used to address organisational and business challenges, rather than studying data science purely as an academic subject.

Build skills across the data science pipeline
Learn how to source, process, clean, analyse, model, interpret, and communicate data

Develop strong computing skills
Explore programming, databases, data engineering, cloud computing, algorithms, software development, and security alongside data analysis.

Explore machine learning and AI
Learn about predictive analytics, machine learning, artificial intelligence, optimisation, automation, computer vision, and Natural Language Processing.

Work on projects throughout your degree
Project-based learning at each level allows you to apply your knowledge to practical problems and build evidence of your skills.

Understand responsible use of data
Explore data governance, security, ethics, bias, compliance, and the regulations that influence how organisations use data.

Develop business and professional skills
Learn to communicate findings effectively and understand how data can be used to improve organisational processes, operations, and decision- making.

Gain additional professional certifications
You may have the opportunity to access certifications in areas such as Data, AI, Security, and Cloud, including Microsoft Fundamentals and Pearson IT Specialist certifications.

Gain valuable industry experience
You can apply for an optional sandwich placement year, with support available throughout the process.

What you'll learn

You'll develop a broad understanding of how data is collected, managed, analysed, and applied to real-world problems. Rather than focusing on one stage of the data process, the course is designed to help you understand the wider data landscape and develop the technical skills needed to work across it.

Data analysis and interpretation

You'll learn how to work with different types and sources of data, including databases, operational systems, web services, open data, government data, and other forms of structured and unstructured information.

You'll develop skills in:

  • Sourcing and preparing data
  • Data cleaning and processing
  • Statistical and mathematical analysis
  • Data interpretation
  • Data visualisation
  • Evaluating complex datasets
  • Identifying patterns in real-world data
  • Using evidence to support decision-making Programming and computing

You'll develop the computing knowledge needed to work effectively with data at scale. This includes areas such as:

  • Programming
  • Algorithms and computational methods
  • Database systems
  • Data storage and processing
  • Data warehousing
  • NoSQL and real-time data approaches
  • Cloud technologies
  • Software development practices
  • Testing and source control
  • Data and information security

You'll explore the advantages and limitations of different technologies and learn how to select appropriate tools for different data science problems.

Machine learning and artificial intelligence

You'll explore how analytical algorithms can be designed, implemented, evaluated, and optimised. Topics include:

  • Predictive and advanced analytics
  • Machine learning
  • Artificial intelligence
  • Statistical and mathematical modelling
  • Simulation
  • Optimisation
  • Automation
  • Computer vision
  • Natural Language Processing

You'll consider both the capabilities of these technologies and the practical constraints involved in deploying them, including computing resources, organisational requirements, and the selection of appropriate models and tools.

Responsible data science

Working with data involves important ethical, legal, and professional responsibilities. You'll explore how data governance, security, ethics, compliance, and regulation influence data science practice. You'll consider issues including:

  • Data privacy and security
  • Bias and prejudice in data and analysis
  • Responsible use of artificial intelligence
  • Data governance
  • Regulatory requirements
  • Ethical decision-making
  • Communicating data responsibly

This can help you understand not just what you can do with data , but how you should use it responsibly.

Learning through practical application

Teaching will combine lectures, seminars, tutorials, practical workshops, and online resources. Real-world case studies and employer-led projects will help you connect theory with practical data science challenges. You'll be assessed through a combination of coursework, presentations, project reports, posters, and in-class tests, with an emphasis on demonstrating your ability to apply your knowledge.

Support and student experience

Moving into a technical degree can feel challenging, particularly when you’re learning new mathematical and programming concepts at the same time. The course is designed to build your knowledge progressively, giving you opportunities to practise skills and apply them before moving on to more advanced areas.

Teaching includes lectures, seminars, tutorials, practical workshops, and online learning resources. You’ll also work individually and collaboratively, helping you develop the communication and teamwork skills needed beyond university.

You’ll have access to on-campus computing facilities, high-performance CPU and GPU resources, library and learning resources, and careers support. The course also provides opportunities to learn from academic research, industry engagement, alumni, and placement experiences, helping you understand how Data Science is used beyond the classroom.

Careers and future opportunities

Data Science graduates can work wherever organisations need people who can understand complex information, identify patterns, and use evidence to support decisions. Depending on your interests, potential career paths include:

  • Data scientist
  • Data analyst
  • Business analyst
  • Machine learning engineer
  • Data and business intelligence specialist
  • Demand and forecasting analyst
  • Statistical analyst
  • AI-related roles
  • Data science consultant
  • Research and analytical roles

You could work across sectors including:

  • Technology
  • Healthcare
  • Finance and banking
  • Engineering
  • Manufacturing
  • Agriculture and agri-tech
  • Business and consultancy
  • Education
  • Government and public services

The University has identified strong links with regional industries including agri-tech, healthcare, and manufacturing, where organisations increasingly use data-driven approaches to improve processes and decision-making.

Gain experience before you graduate

Employers increasingly value graduates who can demonstrate how they have applied their knowledge. You’ll have opportunities to develop this experience through projects, employer engagement, professional certifications, internships, research activity, and an optional placement year. The University’s Careers and Employability service will also work with academics to embed career development within the programme, while employers, industry delegates, placement students, and alumni can contribute to the student experience through talks and other activities.

Continue your studies

The degree can also provide a foundation for postgraduate study and research in areas such as Data Science, mathematics, computer science, artificial intelligence, and related disciplines.

Is this course right for you?

This course could be a good choice if you:

  • Are interested in how organisations use data to solve problems and make decisions
  • Want to develop practical skills in data analysis, programming, and computing
  • Are interested in machine learning, artificial intelligence, or data engineering
  • Enjoy solving problems and working with information
  • Want to learn through practical projects and real-world applications
  • Want to develop technical and professional skills that can transfer across industries
  • Are looking for opportunities to gain industry experience through a placement year
  • Want the flexibility to pursue different careers across data, technology, business, and analytics.

If you're more interested in the practical and computing side of data science, rather than a predominantly mathematical approach, BSc (Hons) Applied Data Science is designed with you in mind.

The University also offers a separate BSc (Hons) Data Science with a greater emphasis on the mathematical elements of the discipline, making the distinction between the two pathways particularly important when choosing the course that best matches your interests.

Fees and Funding

University Study is a major investment, so it’s important to understand the costs and support available. A full breakdown of the fees associated with this programme can be found below. Eligible students may be able to access scholarships and bursaries to help with study costs.

Fees