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Data Science MSc

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The Data Science MSc provides advanced technical and practical skills in the collection, collation, curation and analysis of data. This is an ideal study pathway for graduates with a background in quantitative subjects, or who possess relevant work experience, who want to gain experience in current methods and techniques of data science.

Offer Holders: Do you hold an offer for entry in the 2020/21 academic year? Visit your offer holder hub for the latest updates.


Key benefits

  • 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).
  • The Department of Informatics has a reputation for delivering research-led teaching and project supervision from leading experts in their field.
  • 92 per cent of research outputs ranked as world leading or internationally excellent – confirming the department’s position as a world-class institution for research in Computer Science (REF 2014).

Key information

Application status Open

Duration 1 Year FT, commences in September

Study mode Full-time

Credit value UK 180/ECTS 90

Course intake 50 FT

Course leaders

Further details

Course contact for further information

Course contact form Postgraduate admissions

Awarding institution King's College London

Faculty Faculty of Natural & Mathematical Sciences

Department Department of Informatics

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Course detail

Description

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.

Rooted in the renowned research strengths of the Department of Informatics, this course enables you to study a wide variety of topics in advanced computing while allowing you to specialise through your choice of modules.  You will learn advanced practical techniques and implementation skills for solving complex computational problems.

Teaching

We use lectures, seminars and group tutorials to deliver most of the modules on the course. You will also be expected to undertake a significant amount of independent study.

You are expected to spend approximately 10 hours work per credit for each module you attend in your degree, e.g. 150 hours work for a 15-credit module. These hours cover every aspect of the module.

Assessment

The primary method of assessment for this course is a combination of written examinations, coursework, in-class tests, individual projects and oral presentations. The individual project will be assessed through a dissertation.

Structure

Year 1

You will complete the course in one year, studying September to September. You must take modules totalling 180 credits to meet the requirements of the qualification, 60 of which will come from an individual project.

Required Modules

You are required to take:

  • Computer Programming for Data Scientists (15 credits) or Big Data Technologies (15 credits)
  • Databases, Data Warehousing & Information Retrieval (15 credits)
  • Statistics for Data Analysis (15 credits) or Elements of Statistical Learning (15 credits) or Statistics in Finance (15 credits)
  • Data Mining (15 credits)
  • Individual Project (60 credits)
Optional Modules

You are required to take 60 credits from a range of optional modules, which may typically include:

  • Elements of Statistical Learning (15 credits)
  • Statistics in Finance (15 credits)
  • Agents & Multi-Agent Systems (15 credits) *
  • Nature-Inspired Learning Algorithms (15 credits) *
  • Pattern Recognition, Neural Networks & Deep Learning (15 credits) *
  • Network Theory (15 credits)
  • Big Data Technologies (15 credits)
  • Simulation & Data Visualisation (15 credits)
  • Computer Vision (15 credits)
  • Telling Stories with Data (15 credits)

You will also be able to select up to 30 credits form a range of level 6 modules, which may typically include:

  • Machine Learning (15 credits) *
  • Optimisation Methods (15 credits) *
  • Artificial Intelligence Reasoning and Planning (15 credits) *

* These modules are not available if you have previously studied in the Department of Informatics and have already taken this module at Level 6.

King’s College London reviews the modules offered on a regular basis to provide up-to-date, innovative and relevant programmes of study. Therefore, modules offered may change.

Entry requirements & how to apply

Data Science MSc Entry Requirements
Minimum requirements  2:1

A Bachelor’s degree with 2:1 (Upper Second Class) honours is required in one of the following subject areas:

  • Computer Science, or Computing

  • Mathematics, Pure Mathematics, Mathematical Statistics or Statistics

  • Physics

  • Natural Science

  • Electronic Engineering

  • Geographic Information Systems

  • Operations Research

In order to meet the academic entry requirements for this programme you should have a minimum 2:1 undergraduate degree with a final mark of at least 60% or above in the UK marking scheme. If you are still studying you should be achieving an average of at least 60% or above in the UK marking scheme. 
International requirements   Visit our admissions webpages to view our International entry requirements.
English Language requirements Band D Visit our admissions webpages to view our English language entry requirements.

 

Application procedure

Applications must be made online using King’s online application portal apply.kcl.ac.uk and a non-refundable application fee of £100 applies. 

Your application will be reviewed by an academic tutor and we aim to respond to applications within four to six weeks, although this may take longer during busy and holiday periods.

Personal statement and supporting information

You will be asked to submit the following documents in order for your application to be considered:

Personal Statement  Yes

A personal statement is required. This can be entered directly into the online application form (maximum 4,000 characters) or uploaded as an attachment to the online application form (maximum 2 pages). Please explain why you wish to apply for this programme and why you feel it matches your interests, academic background, and, if relevant, your career plans.
Previous Academic Study Yes A copy (or copies) of your official academic transcript(s), showing the subjects studied and marks obtained. If you have already completed your degree, copies of your official degree certificate will also be required. Applicants with academic documents issued in a language other than English, will need to submit both the original and official translation of their documents.
References Yes One academic reference is required. A professional reference will be accepted if you have completed your qualifications over five years ago. In some cases, we may request an additional reference from you.
Other Optional Applicants may wish to include a CV (Resume) or evidence of professional registration as part of their application

 

Application closing date

We recommend that you submit your application as soon as possible. Our first application deadline is the 31 March 2020. After this date, applications will remain open if places are available, but programmes will be closed as soon as they are full. For programmes with spaces remaining, no further applications will be accepted from non-EU (Overseas) nationals after 31 July 2020 or from UK/EU nationals after 28 August 2020.

Please note you will not be eligible for an application fee refund if you apply after the first application deadline and places are filled before the final deadlines above and we are unable to process more offers.

Help and support

If you don't have a suitable qualification for direct entry to a UK university, or if English isn't your first language, our academic preparation courses can help you get ready for study in the UK.

Preparation courses

Fees and funding

  • Full time Home/EU fees: £9,990 per year (2020/21)
  • Full time overseas fees: £26,550 per year (2020/21)

Students starting their programme in 2020/21 who are eligible to pay EU fees will pay the same rate of tuition fees as UK students. This will apply for the duration of their programme, but may be subject to change by the UK Government for subsequent cohorts from 2021/22.

These tuition fees may be subject to additional increases in subsequent years of study, in line with King’s terms and conditions.

Deposit

When you receive an offer for this course you will be required to pay a non-refundable deposit to secure your place. The deposit will be credited towards your total fee payment.

The UK/EU deposit is £500.

The INTERNATIONAL deposit is £2,000. 

  • If you receive an offer before 1 June 2020, payment is due by 30 June 2020.

  • If you receive an offer between 1 June 2020 and 30 June 2020, payment is due within one month of receiving the offer.

  • If you receive an offer between 1 July 2020 and 31 July 2020, payment is due within two weeks of receiving the offer.

  • If you receive an offer on or after 1 August 2020, payment is due within one week of receiving the offer.

  • If you receive an offer in late August, payment is due within 2 days of receiving the offer.

    If you are a current King’s student in receipt of the King's Living Bursary you are not required to pay a deposit to secure your place on the programme. Please note, this will not change the total fees payable for your chosen programme.

Additional costs/expenses

In addition to your tuition fees, you can also expect to pay for: 

  • Books, if you choose to buy your own copies 
  • Clothing for optional course related events and competitions 
  • Course packs, which are a vital part of your learning at King's and normally contain extracts from books and other useful documents that will inform your study.
  • Library fees and fines 
  • Personal photocopies 
  • Printing course handouts 
  • Society membership fees 
  • Stationery 
  • Travel costs for travel around London and between campuses 
  • Graduation costs

Please visit our web pages on fees and funding for more information.

Financial help and support

Visit the fees and funding webpages to find out more about bursaries, scholarships, grants, tuition fees, living expenses, student loans and other financial help available at King's.

Testimonials

Federico

Federico

From statistics lectures to machine learning tutorials, the Data Science MSc will give you everything you need to understand the power of data and to start using it. At King's there are outstanding researchers and professors as well as a huge amount of resources that guided me through my studies.

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