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Scientific and Data Intensive Computing MSc

Scientific and Data Intensive Computing MSc

Different course options

Full time | UCL (University College London) | 1 year | SEP

Study mode

Full time

Duration

1 year

Start date

SEP

Key information
DATA SOURCE : IDP Connect

Qualification type

MSc - Master of Science

Subject areas

Scientific / Technical Information Services Data Analysis Numerical Analysis

Course type

Taught

Course Summary

Scientists and engineers are tackling ever more complex problems, most of which do not admit analytical solutions and must be solved numerically. Numerical methods can only play an even more important role in the future as we face even bigger challenges. Therefore, skilled scientific programmers are in high demand in industry and academia and will drive forward much of the future economy. This programme aims to provide a rigorous formal training in computational science to produce highly computationally skilled scientists and engineers capable of applying numerical methods and critical evaluation of their results to their field of science or engineering. It brings together best practice in computing with cutting-edge science and provides a computing edge over traditional science, engineering and mathematics programmes.

Careers

We expect our graduates to take up exciting science and engineering roles in industry and academia with excellent prospects for professional development and steep career advancement opportunities. This degree enables students to work on cutting-edge real-life problems, overcome the challenges they pose and so contribute to advancing knowledge and technology in our society.

Employability

Students develop a comprehensive set of skills which are in high demand both in industry and academia: professional software development skills including state-of-the-art scripting and compiled languages; knowledge of techniques used in high-performance computing; understanding and an ability to apply a wide range of numerical methods and numerical optimisation; a deeper knowledge of their chosen science subject; oral and written presentational skills.

Modules

Numerical Methods - Core
Techniques of High-Performance Computing - Core
Machine Learning with Big-Data - Core
Computational and Simulation Methods - Core
Research Software Engineering with Python - Core
Numerical Optimisation - Core
Statistical Data Analysis - Core
Research Computing with C++ - Core

Tuition fees

UK fees
Course fees for UK students

For this course (per year)

12,900

International fees
Course fees for EU and international students

For this course (per year)

32,100

Entry requirements

A minimum of an upper second-class Bachelor's degree from a UK university, or an overseas qualification of an equivalent standard, in mathematics, computer science, engineering, physical sciences or a closely related subject. The degree stream must contain at least one university level mathematics course.

University information

University College London (UCL) is one of the largest and most highly ranked higher education institutions in the world, conducting leading research across a wide range of subject areas. Throughout its long and prestigious history, it has inspired and educated countless minds and produced 30 Nobel prize recipients. With one campus located in the heart of Bloomsbury, and a second campus in vibrant east London the university is home to around...more

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