Studyportals

Big Data Science

Queen Mary University of London

M.Sc. On Campus
12 months
Duration
23950 GBP/year
10900 GBP/year
Unknown
Tuition fee
Unknown
Apply date
Unknown
Start date

About

The Big Data science movement is transforming how Internet companies and researchers over the world address traditional problems. Big Data Science course offered at Queen Mary University of London 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.

Overview

Overview

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.

Big Data Science course offered at Queen Mary University of London 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.

Students will be offered 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. Students will also undertake a large project where they 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. 

Programme Structure

Courses include:
  • Applied Statistics
  • Big Data Processing
  • Data Mining
  • MSc Project 
  • Cloud Computing
  • Data Analytics
  • Digital Media and Social Networks
  • Deep Learning and Computer Vision
  • Introduction to the Internet of Things
  • Introduction to Object-Oriented Programming
  • Machine Learning
  • Natural Language Processing
  • Semi-structured Data and Advanced Data Modelling
  • Machine Learning for Visual Data Analysis
  • The Semantic Web

Key information

Duration

  • Full-time
    • 12 months
  • Part-time
    • 24 months

Start dates & application deadlines

Language

English

Credits

180 alternative credits

Delivered

On Campus

Academic requirements

GPA admission requirements GPA Your GPA, or Grade Point Average, is a number that indicates how well or how high you scored in your courses on average. Usually a GPA scales between 1.0 and 4.0, however different countries and universities can have different grading systems.
Required

English requirements

TOEFL admission requirements TOEFL® IBT The TOEFL iBT® is given online through the internet at designated testing site. The test measures your English-language abilities in an academic setting. The score refers to the total score of 4 subjects (writing, listening, speaking, and reading), each subject has a range of 0 - 30.
79
IELTS admission requirements IELTS The International English Language Test System (IELTS) tests your English-language proficiency on a scale of 1 – 9. The score refers to the combined average score of 4 subjects (writing, listening, speaking, and reading).
6

Other requirements

General requirements

  • Completed application form
  • Degree transcripts. Please provide a transcript of your degree(s). If you have not yet completed your degree please provide a transcript of your results achieved to date
  • Please provide the contact details of two referees on your application, at least one reference must be from an academic referee who is in a position to comment on the standard of your academic work and suitability for postgraduate level study. Where appropriate, a second referee can provide comment on your professional experience.
  • Curriculum Vitae (CV)/ Resume
  • Statement of purpose 

Tuition Fee

  • International

    23950 GBP/year
    Tuition Fee
    Based on the original amount of 23950 GBP per year and a duration of 12 months.
  • EU/EEA

    10900 GBP/year
    Tuition Fee
    Based on the original amount of 10900 GBP per year and a duration of 12 months.

Funding

Studyportals Tip: Students can search online for independent or external scholarships that can help fund their studies. Check the scholarships to see whether you are eligible to apply. Many scholarships are either merit-based or needs-based.

Due for update

Updated over a year ago

Check the official programme website for potential updates.

Big Data Science
-
Queen Mary University of London

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