BSc Hons Accounting and Management
Queen Mary University of London's BSc-Hons- Accounting and Management program ...
London
INTAKE: September
The BSc(Hons) Computer Science and Mathematics program at Queen Mary University of London (QMUL) offers an interdisciplinary approach, combining principles from computer science and mathematics to provide students with a comprehensive understanding of computational theories and mathematical principles.
Curriculum: The curriculum integrates courses from computer science and mathematics, covering subjects such as algorithms, software development, discrete mathematics, calculus, linear algebra, probability, and computational theory. This fusion equips students with a strong foundation in both disciplines.
Research Focus: The program emphasizes research-driven learning, encouraging students to explore intersections between computer science and mathematics. Students engage in projects exploring computational models, data analysis, cryptography, or other areas that bridge the two disciplines.
Industry Engagement: Students have opportunities to engage with industry partners through internships, projects, or collaborations. This interaction provides practical exposure, allowing students to apply their interdisciplinary skills to real-world problems and understand industry demands.
Global Perspective: The program incorporates a global perspective by addressing universal principles in mathematics and computer science. Students gain insights into global challenges, enhancing their ability to apply their knowledge in diverse contexts and across international boundaries.
London
IELTS 6
£ 26250
Undergraduate Entry Requirements
Academic Qualifications: Applicants should have successfully completed their secondary education with a minimum overall score of 80% or equivalent in their respective country's grading system.
English Language Proficiency:
Students must provide:
It is important to note that meeting the minimum entry requirements does not guarantee admission, as the university considers factors such as availability of places and competition for the program. Additionally, some courses may have higher entry requirements or additional selection criteria, such as interviews or portfolio submissions.
Queen Mary University of London offers a range of scholarships and bursaries to its students.
Queen Mary Principal's Scholars Program: A scholarship program for undergraduate students who have an offer of admission from Queen Mary University of London and have achieved exceptional academic grades. The scholarship covers full tuition fees for three years of study, as well as a £2,000 annual stipend for living expenses.
Queen Mary International Excellence Scholarships: A scholarship program for international undergraduate and postgraduate students who have an offer of admission from Queen Mary University of London and have demonstrated academic excellence. The scholarship covers full tuition fees for one year of study.
Queen Mary Law Scholarships: A scholarship program for undergraduate and postgraduate law students who have an offer of admission from Queen Mary University of London and have demonstrated academic excellence. The scholarship covers full or partial tuition fees, depending on the level of academic achievement.
Queen Mary Engineering and Materials Science Scholarships: A scholarship program for undergraduate and postgraduate students studying engineering or materials science who have an offer of admission from Queen Mary University of London and have demonstrated academic excellence. The scholarship covers full or partial tuition fees, depending on the level of academic achievement.
Graduates from Queen Mary University of London's BSc(Hons) Computer Science and Mathematics program possess a unique blend of computational and mathematical skills, enabling them to pursue diverse career paths across various industries.
Data Scientist: Graduates can work as data scientists, utilizing their strong mathematical background and computational skills to analyze complex datasets, derive insights, and make data-driven decisions in sectors like finance, healthcare, or technology.
Software Developer: Graduates are well-suited for roles as software developers, leveraging their understanding of algorithms and computational models to design and create software solutions for diverse applications in technology companies or startups.
Quantitative Analyst: Graduates may pursue careers as quantitative analysts, applying their mathematical and computational expertise to analyze financial markets, develop trading strategies, and assess risks in investment banks or hedge funds.
Systems Analyst: Graduates can work as systems analysts, employing their knowledge in computer science and mathematics to evaluate and optimize computer systems and processes within organizations.
Cryptographer: Graduates with a deeper focus on cryptography can explore roles in cybersecurity or cryptography, devising secure systems and encryption methods to protect sensitive data in various industries.
Research Scientist: Graduates interested in academia or research can pursue roles as research scientists, conducting studies in computational fields, exploring new algorithms, or contributing to innovative technological advancements.
Financial Analyst: Graduates may venture into financial analysis roles, using their quantitative skills to assess financial data, conduct risk assessments, and provide insights for investment decisions in financial institutions.
Mathematical Modeller: Graduates can work as mathematical modelers, applying mathematical principles and computational techniques to model real-world problems, including simulations in scientific research or engineering.
Consultant: Graduates can become consultants, offering expertise to businesses in technology strategies, data analysis, or optimizing operational systems through their combined knowledge of computer science and mathematics.
Education: Graduates can pursue teaching or academia, utilizing their expertise to educate and inspire future generations in computer science, mathematics, or related fields.