Data scientists are in high demand across sectors such as healthcare, finance, marketing, and transport. This course provides essential training in mathematics, data analysis, and computing, addressing real-world problems from research and industry. Students develop transferable skills for careers in business or education, enhance critical thinking for problem-solving, and gain expertise in modern computational methods and software. Opportunities for industry-relevant experience, including placements, are available, subject to conditions.The curriculum includes foundational modules in the first year (e.g., calculus, programming, and statistics) and advanced topics in the second year (e.g., artificial intelligence and data science). The final year covers big data, machine learning, and a dissertation, with an optional master's extension. Assessment involves exams, essays, group projects, presentations, and reports to evaluate student progress effectively.
Year One In your first year, you will be taught the fundamental skills and concepts needed to begin your journey as a data scientist. You’ll be familiarised with the mathematical, statistical and computational foundations, and you will apply those principles in regular laboratory sessions which help solidify your understanding. You will also begin developing the professional skills you will need in your day-to-day career on graduation: working as part of a team, the ethical and legal issues around data structure and models. Modules Calculus - 20 credits Algebra - 20 Credits Programming: Concepts and Algorithms - 20 Credits Working with Data - 20 Credits Programming: Professional Practice - 20 Credits Probability and Statistics - 20 Credits Year Two In year two, you will develop more advanced knowledge and skills to do with data science, linear statistical models and artificial intelligence, amongst others. Modules Artificial Intelligence - 20 Credits Linear Algebra and Differential Equations - 20 Credits Advanced Algorithms - 20 Credits Data Science - 20 Credits Linear Statistical Models - 20 Credits Data Science Group Project - 20 Credits Placement Year There’s no better way to find out what you love doing than trying it out for yourself, which is why a work placement* can often be beneficial. Work placements usually occur between your second and final year of study. They’re a great way to help you explore your potential career path and gain valuable work experience, whilst developing transferable skills for the future. If you choose to do a work placement year, you will pay a reduced tuition fee* of £1,250. For more information, please go to the fees and funding section. During this time, you will receive guidance from your employer or partner institution, along with your assigned academic mentor who will ensure you have the support you need to complete your placement. Final Year The final stage of the BSc (Hons) in Data Science covers advanced topics in data science including Big Data management and visualisation methods, machine learning algorithms, Artificial Neural Networks and advanced statistical methods. Modules Data Visualisation - 20 Credits Statistical methods for Data Science - 20 Credits Machine Learning - 20 Credits Project Discovery - 20 credits Dissertation and Project Artefact - 20 credits Optional Modules Additional Year The additional fourth year master's option will deepen your knowledge and expertise*. This year provides insight into more advanced topics in data science and can act as a stepping stone to postgraduate research or further study. We regularly review our course content, to make it relevant and current for the benefit of our students. For these reasons, course modules may be updated. Before accepting any offers, please check the website for the most up to date course content. For full module details please check the course page on the Coventry University website. *For further information please check the course page on the Coventry University website
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