Data Science

King’s College London

Master

In London

Price on request

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Description

  • Type

    Master

  • Location

    London

The Data Science MSc is an interdisciplinary study programme that will provide you with advanced technical and practical skills in the collection, collation, curation and analysis of data. It also examines the professional, legal and ethical responsibilities of data scientists. This is an ideal study pathway for graduates with a background in quantitative subjects, or who possess relevant work experience in the current methods and techniques of data science.
The course information sheet is a printable version of the information on this web page, which you can download here.

Located in central London, giving access to major libraries and leading scientific societies, including the Chartered Institute for IT (BCS), and the Institution of Engineering and Technology (IET).
You will gain an in-depth understanding of the general principles of the computational and statistical approaches and methods used in data science, as well as their underlying assumptions and limitations.
Frequent access to speakers of international repute through seminars and external lectures, enabling you to keep abreast of emerging knowledge in advanced computing and related fields.
Exposure to interdisciplinary aspects of Data Science through opportunities to interact with multiple departments and faculties across King's diverse campuses
The Department of Informatics has a reputation for delivering research-led teaching and project supervision from leading experts in their field.

Facilities

Location

Start date

London
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Strand, WC2R 2LS

Start date

On request

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Subjects

  • Access
  • Statistics
  • Project
  • Engineering
  • Computational

Course programme

Year 1 Required Modules

    Courses are divided into modules. Each year you are required to take modules totalling 180 credits
  • Data Science Individual Project (60 credits)
  • Computer Programming for Data Scientists (15 credits)
  • Databases, Data Warehousing and Information Retrieval (15 credits)
  • Statistics for Data Analysis (15 credits) *

* If you already have an undergraduate degree in mathematical statistics, you may be exempt from this module at the discretion of the programme director.

Optional Modules

In addition, students take at least 30 credits from:

  • Big Data Technologies (15 credits)
  • Simulation and Data Visualisation (15 credits)
  • Data Mining (15 credits)
  • Machine Learning (15 credits)

Students are required to take 45 credits from the following modules, to bring their total number of credits for the year to 180:

  • Elements of Statistical Learning (15 credits)
  • Statistics in Finance (15 credits)
  • Advanced Research Topics (15 credits)
  • Advanced Software Engineering (15 credits)**
  • Agents and Multi-Agent Systems (15 credits)**
  • Fundamentals of Digital Signal Processing (15 credits)
  • Operations Management (15 credits)
  • Project Management (15 credits)
  • Random Variables and Stochastic Processes (15 credits)
  • Artificial Intelligence (15 credits)**
  • Algorithms for Computational Molecular Biology (15 credits)
  • Communications Theory (15 credits)
  • Optimisation Methods (15 credits)**
  • Text Searching and Processing (15 credits)**
  • Biologically Inspired Methods (15 credits)**
  • Pattern Recognition (15 credits)**
  • Network Theory (15 credits)
  • Topics on Data and Signal Analysis (15 credits)
  • Data Mining (15 credits)
  • Machine Learning (15 credits)
  • Big Data Technologies (15 credits)
  • Simulation and Data Visualisation (15 credits)

There are options to take modules in other departments such as Digital Humanities and War Studies.

**These modules are not available if you have previously studied in the Department of Informatics and have already taken this module at Level Six.

King’s College London reviews the modules offered on a regular basis to provide up-todate, innovative and relevant programmes of study. Therefore, modules offered may change. We suggest that you keep an eye on the course finder on our website for updates.

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