BSc (Econ)(Hons) Economics, Finance and Management
Spanning three years, with options to extend to four or five years to include a year ab...
MSc Data Analytics
Mile End
INTAKE: September
Program Overview
The MSc in Data Analytics at QMUL is structured to provide a robust foundation in data analysis, emphasizing the application of mathematical principles to real-world scenarios. Students are trained to harness statistical techniques and leverage cutting-edge technologies to extract actionable insights, thereby informing strategic decisions across various industries.
Curriculum: The curriculum is thoughtfully crafted to balance theoretical knowledge with practical application. In the initial semester, students engage with core modules such as "Machine Learning with Python," "Storing, Manipulating, and Visualising Data," "Probability and Statistics for Data Analysis," and "Programming with Python." These modules lay the groundwork for understanding data analytics. In the subsequent semester, students can tailor their learning by selecting one of three specialized streams: Applied Machine Learning, Pattern Recognition and Deep Learning, or Statistical Inference. Each stream offers a selection of elective modules, allowing students to align their studies with specific career aspirations.
Research Focus: A pivotal component of the program is the independent research project undertaken during the summer term. This project enables students to delve into areas such as time series analysis, complex systems, or topological data analysis, fostering the development of strong applied data science research skills. Collaborations with industry partners are encouraged, providing students with opportunities to address real-world data challenges.
Industry Engagement: QMUL's School of Mathematical Sciences boasts strong ties with industry, offering students exposure to practical applications of data analytics. The program's emphasis on hands-on experience ensures that graduates are well-prepared to meet the demands of employers across sectors such as finance, healthcare, retail, and manufacturing. Additionally, students have access to state-of-the-art facilities, including dedicated computer labs equipped with industry-standard software and Bloomberg terminals.
Global Perspective: Situated in the heart of London, QMUL provides a vibrant and diverse environment, attracting students from around the globe. This multicultural setting enriches the learning experience, offering a global perspective on data analytics challenges and solutions. The university's commitment to inclusivity and excellence ensures that students are part of a dynamic academic community, poised to address complex data-driven problems worldwide.
Location
Mile End
Score
IELTS 6.5
Tuition Fee
£ 33500
Postgraduate Entry Requirements:
- Applicants should have successfully completed a bachelor's degree or its equivalent from a recognized institution with a minimum overall score of 60% or equivalent.
- English language proficiency is required, and applicants must provide evidence of their English language skills through an approved language test.
- IELTS: A minimum overall score of 6.5 with no individual component below 6.0.
- TOEFL: A minimum overall score of 92, with at least with at least 17 in Listening, 18 in Reading, 20 in Speaking, and 21 in Writing.
- PTE Academic: A minimum overall score of 71 with 65 in Writing, and 59 in Reading, Listening and Speaking..
- Some postgraduate programs may have specific subject prerequisites or additional requirements.
Students must provide:
- academic marksheets & transcripts
- letters of recommendation
- a personal statement - SOP
- passport
- other supporting documents as required by the university.
Work experience: Some postgraduate courses may require relevant work experience in the field.
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 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.
The MSc Data Analytics program opens up a multitude of rewarding career opportunities in today's data-driven world. Graduates are equipped with the skills to excel in various industries and roles.
Data Analyst: Graduates can work as data analysts, extracting valuable insights from data to inform business strategies and decision-making.
Data Scientist: Graduates may pursue roles as data scientists, utilizing advanced analytical techniques to solve complex problems and create predictive models.
Business Intelligence Analyst: Graduates can become experts in business intelligence, helping organizations make informed choices based on data-driven insights.
Machine Learning Engineer: Graduates with a focus on machine learning can work on designing, building, and deploying machine learning models for automation and prediction.
Data Engineer: Graduates may pursue careers as data engineers, responsible for the design and maintenance of data pipelines and infrastructure.
Quantitative Analyst: Graduates interested in finance can become quantitative analysts, using data analytics to assess financial risks and opportunities.
Marketing Analyst: Graduates can work in marketing analysis, using data to understand consumer behavior and optimize marketing campaigns.
Healthcare Data Analyst: Graduates may find opportunities in healthcare, analyzing patient data to improve medical treatments and outcomes.
Consultant: Graduates can become data analytics consultants, providing expertise to organizations seeking to harness the power of data.
Academic Researcher: Graduates may pursue further studies or research positions in academia, contributing to advancements in data analytics.
