Data Science with specialisation in Statistics

The MSc in Data Science with Specialisation in Statistics at University College London offers a comprehensive and rigorous training for students seeking to develop advanced skills in data analysis, statistical modeling, and computational techniques. Designed for individuals aiming to excel in the rapidly evolving field of data science, this programme combines theoretical foundations with practical applications, enabling graduates to address complex problems across various industries. Students will engage with cutting-edge topics such as machine learning, data mining, Bayesian statistics, and big data analytics, emphasizing the importance of statistical inference and quantitative reasoning in extracting valuable insights from data. The curriculum includes a strong emphasis on programming skills in R, Python, and SQL, equipping students with the technical proficiency needed to manipulate large datasets and implement advanced algorithms. Through a combination of lectures, seminars, and practical projects, learners will gain hands-on experience in designing and deploying data-driven solutions. The programme also emphasizes the importance of ethical considerations and responsible data use in professional contexts. Graduates will be well-prepared for careers in data science, statistics, research, and consultancy, equipped with the analytical tools necessary to translate data into actionable knowledge. With access to UCL’s extensive academic resources and its vibrant research community, students will have opportunities for interdisciplinary collaboration and engagement with industry partners. The MSc in Data Science with Specialisation in Statistics aims to produce versatile and innovative professionals capable of contributing to the advancement of data-intensive disciplines and solving real-world problems through rigorous statistical methods and modern computational techniques.

The programme combines training in core statistical and machine learning methodology, beginning at an introductory level, with a range of optional modules covering more specialised knowledge in statistical computing and modelling. Students choosing the statistics specialisation will take one compulsory module and up to two additional modules from computer science, with the remaining modules (including the research project) taken mainly from within UCL Statistical Science.

Students undertake modules to the value of 180 credits.

The programme consists of four core modules (60 credits), four optional modules (60 credits) and a research dissertation/report (60 credits).

Core modules

• Introduction to Statistical Data Science
• Introduction to Machine Learning
• Statistical Design of Investigations
• Statistical Computing

Optional modules

• At least two from a choice of Statistical Science modules including:
• Applied Bayesian Methods
• Decision & Risk
• Factorial Experimentation
• Forecasting
• Quantitative Modelling of Operational Risk and Insurance Analytics
• Selected Topics in Statistics
• Stochastic Methods in Finance I
• Stochastic Methods in Finance II
• Stochastic Systems
• Up to two from a choice of Computer Science modules including:
• Affective Computing and Human-Robot Interaction
• Graphical Models
• Statistical Natural Language Processing
• Information Retrieval & Data Mining

Dissertation/report

All students undertake an independent research project, culminating in a dissertation usually comprising 10,000-12,000 words. Workshops running during the teaching terms provide preparation for this project and cover the communication of statistics.

Teaching and learning

The programme is delivered through a combination of lectures, tutorials and classes, some of which are dedicated to practical work. Assessment is through written examination and coursework. The research project is assessed through the dissertation and a 15-minute presentation.

A minimum of an upper second-class Bachelor's degree in a quantitative discipline from a UK university or an overseas qualification of an equivalent standard. Knowledge of mathematical methods and linear algebra at university level and familiarity with introductory probability and statistics is required. Relevant professional experience will also be taken into consideration.

The MSc Data Science with Specialisation in Statistics at University College London offers various financing options to support students financially throughout their studies. Tuition fees vary depending on the student's domicile status. For UK students, the fees are approximately £15,480 per year, while overseas students are charged around £31,280 annually. These fees are subject to annual increases and may differ for specific cohorts, so applicants are advised to consult the official university website for the most current figures.

Funding opportunities include scholarships, bursaries, and grants offered directly by UCL or external sources. UCL provides a range of scholarships specifically aimed at MSc students, including the UCL Graduate Support Scheme and department-specific scholarships that can substantially offset tuition costs. Applicants are encouraged to review the eligibility criteria and application deadlines for these awards, which often require separate applications and supporting documentation.

Additionally, students may consider federal or state financial aid options available in their home countries if applicable. The university also supports international students in applying for external scholarships and funding from organizations such as the Chevening Scholarship, Erasmus+, or government-sponsored programs, which can provide substantial financial assistance.

Students often finance their studies through a combination of personal savings, part-time work, and loans. UCL facilitates part-time employment through its career services, which help students find suitable on-campus or nearby part-time positions compatible with their academic schedules. International students should be aware of visa regulations restricting the number of hours they can work during the academic year.

Loan schemes are available through various financial institutions and may be accessible to eligible students depending on their home country or residency status. It is important for prospective students to carefully review loan terms, repayment conditions, and eligibility criteria before proceeding.

In addition, the university's International Student Support team provides guidance on financial planning and accessing available funding, as well as advice on managing living expenses in London. Students are advised to create comprehensive budgets considering tuition fees, accommodation, travel, insurance, study materials, and personal expenses to ensure smooth financial planning during their period of study.

Overall, financing a master's degree at UCL requires careful research into the available scholarships, grants, loans, and external funding sources. It is highly recommended that applicants start their funding applications early and consult the university’s official financial aid pages or contact the university’s admissions and financial aid offices directly for personalized assistance and the latest information regarding available financial support options.

The MSc Data Science with Specialisation in Statistics at University College London is a comprehensive postgraduate program designed to equip students with a robust understanding of data science methodologies, statistical theories, and practical skills essential for analyzing and interpreting complex data. The curriculum integrates core concepts from computer science, mathematics, and statistics, providing a strong foundation in programming languages such as Python and R, data management, machine learning, and statistical inference. Students will engage with a variety of coursework that emphasizes both theoretical understanding and practical application, preparing them for careers in data analysis, research, and industry roles that demand sophisticated statistical expertise.

The program features a blend of lectures, seminars, and practical projects, fostering an environment of active learning and collaboration. Students have opportunities to work on real-world datasets, develop algorithms, and implement advanced analytical techniques. The specialized modules focus on statistical modeling, data visualization, and uncertainty quantification, enabling graduates to develop insights from complex datasets. Additionally, the course emphasizes ethical considerations in data science and the importance of reproducible research practices.

Career support services at UCL assist students in securing internships and employment placements, and alumni of the program have gone on to work in sectors such as finance, technology, healthcare, and academia. The program is suitable for students with a background in computer science, mathematics, engineering, or related fields who wish to deepen their expertise in statistical analysis within the broader scope of data science. Students may also have the opportunity to participate in seminars, workshops, and conferences to stay updated with the latest developments in the field. Overall, the MSc Data Science with Specialisation in Statistics prepares graduates for the evolving demands of the data-driven economy by providing a rigorous, interdisciplinary education emphasizing statistical proficiency and practical problem-solving skills.