MSc Big Data Science
The Big Data science movement is transforming how Internet companies and researchers over the world address traditional problems. Big Data refers to the ability of exploiting the massive amounts of unstructured data that is generated continuously by companies, users, devices, and extract key understanding from it. A Data Scientist is a highly skilled professional, who is able to combine state of the art computer science techniques for processing massive amounts of data with modern methods of statistical analysis to extract understanding from massive amounts of data and create new services that are based on mining the knowledge behind the data. The job market is currently in shortage of trained professionals with that set of skills, and the demand is expected to increase significantly over the following years.
If you are looking to pursue a career as a data scientist, this programme is designed for you. You will cover the fundamental statistical (e.g. machine learning) and technological tools (e.g. cloud platforms, Hadoop) for large-scale data analysis.
The course leverages the world-leading expertise in research at Queen Mary with our strategic partnership with IBM and other leading IT sector companies to offer to students a foundational MSc on the field of Data Science. The MSc modules cover the following aspects:
- Statistical Data Modelling, data visualization and prediction
- Machine Learning techniques for cluster detection, and automated classification
- Big Data Processing techniques for processing massive amounts of data
- Domain-specific techniques for applying Data Science to different domains: Computer Vision, Social Network Analysis, Bio Engineering, Intelligent Sensing and Internet of Things
- Use case-based projects that show the practical application of the skills in real industrial and research scenarios.
You will attend lectures that explain the core concepts, techniques and tools required for large-scale data analysis. Laboratory sessions and tutorials will put these elements to practice through the execution of use cases extracted from real domains. You will also undertake a large project where you will demonstrate the application of Data Science skills in a complex scenario.
The programme is offered by academics from the Networks, Centre for Intelligent Sensing, Risk and Information Management, Computer Vision and Cognitive Science research groups from the School of Electronic Engineering and Computer Science. This is a team of more than 100 researchers (academics, post-docs, research fellows and PhD students), performing world leading research in the fields of Intelligent Sensing, Network Analytics, Big Data Processing platforms, Machine Learning for Multimedia Pattern Recognition, Social Network Analysis, and Multimedia Indexing.
Intakes
- Jan
- Sep
Application Processing Time in Days: 30
Application Process
Minimum English Language Requirements
| English Level Description | IELTS (1.0 -9.0) | TOEFL IBT (0-120) | TOEFL CBT (0-300) | PTE (10-90) | |
|---|---|---|---|---|---|
| Expert | 9 | 120 | 297-300 | 86-90 | |
| Very Good | 8.5 | 115-119 | 280-293 | 83-86 | |
| Very Good | 8 | 110-114 | 270-280 | 79-83 | |
| Good | 7.5 | 102-109 | 253-267 | 73-79 | |
| Good | 7 | 94-101 | 240-253 | 65-73 | |
| Competent | 6.5 | 79-93 | 213-233 | 58-65 | |
| Competent | 6 | 60-78 | 170-210 | 50-58 | |
| Modest | 5.5 | 46-59 | 133-210 | 43-50 | |
| Modest | 5 | 35-45 | 107-133 | 36-43 | |
| Limited | 4 | 32-34 | 97-103 | 30-36 | |
| Extremely Limited | < 4 | < 31 | < 93 | < 30 |
Job Opportunity Potential
Careers support
The services we offer to support your career development include:
- one-to-one appointments to help you with your career direction, give feedback on job applications, offer insight into the job market and prepare you for interviews
- workshops to support your career development and job hunting
- employer events attracting recruiters and alumni from a rich range of sectors
- support for finding internships and parttime jobs
- specialist careers consultants to support PhD students through appointments, events and workshops.
Support for international students
- We offer a programme of support for international students throughout the year, which involves talks on how to find graduate work in the UK and an International Students Week featuring external speakers.
- Students can search for jobs across the world with our international jobs database, as well as browse our guides on getting work in particular markets.
- All students have access to a rich programme of employer events and career development workshops, running across the University year.
Support after graduation
Our careers support continues after you leave Queen Mary.
- All graduates have access to our Careers and Enterprise services for two years after graduation.
- You can have -
free one-to-one appointments in person, over the phone or via Skype
Attend our employer events
use our online psychometric testing and mock-interview software
access our jobs board – over 3,000 employers uploaded vacancies in 2018/19.
Queen Mary graduates have gone on to work in these organisations:
• Accenture • Allen & Overy • Arup • AstraZeneca • Baker McKenzie • Barts Health NHS Trust • European Central Bank • Fintech Innovation Lab • Google • HSBC • IBM • Institute of Cancer Research • Institute of Dentistry • J.P. Morgan • Jaguar Land Rover • Lloyds Banking Group • Natural History Museum • Penguin • PwC • Queen Mary • Save the Children • Shell • Stella McCartney • Thales • Thomson Reuters • World Economic Forum ...and many more!
Careers success
93% of our postgraduates are in work and/or study six months after graduation. 84% of those in work/study are in highly skilled work/study (most recent DLHE Survey of 16/17 leavers)*
Enterprise support
Many students and graduates across Queen Mary start or grow their own business or social venture each year. In 2018/19, Queen Mary gave out £45,000 in seed funding to help students start new, or grow existing businesse
PSW Opportunity
- 2 Years PSW is applicable after the course completing (Bachelors level or above).
Admission Requirement / Eligibility Criteria
Degree requirements
- A 2:1 or above at undergraduate level in Electronic Engineering, Computer Science, Mathematics or a related discipline.
India
We normally consider the following qualifications for entry to our postgraduate taught programmes: Bachelor Degree (minimum 3 years) from selected institutions.
- UK 1st class degree: 70% to 80%
- UK 2:1 degree: 60% to 70%
- UK 2:2 degree: 50% to 60%
Offer conditions will vary depending on the institution you are applying from. For some institutions/degrees we will ask for different grades to above, so this is only a guide.
- Course Type: Full Time
- Course Level: Masters/PG Degree
- Duration: 01 Year
-
Total Tuition Fee:
25950 GBP
Annual Cost of Living: 12006 GBP
Application Fee: N/A
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