Course Summary

**Modern societies produce huge amounts of data. However, this information is only useful if we can analyse it and gain practical insights. Data science combines powerful computing technology, sophisticated statistical methods, and expert subject knowledge to carry out this analysis. It is a field that has emerged over recent decades, and is now an exciting, fulfilling, and high-profile career choice, with positions available in many diverse fields.** Our specialist **BSc Data Science with a Foundation Year** programme provides an opportunity for you to develop your mathematics skills and start learning some university-level material, fully preparing you for university study before you progress onto your chosen mathematics programme. The course combines the expertise of internationally-renowned statisticians and mathematicians from the School of Mathematics, Statistics and Actuarial Science (SMSAS) and computer scientists and machine learners from the School of Computing to ensure that you develop the expertise and quantitative skills required for a successful future career in the field. This programme has been designed for those who have achieved grades or are predicted grades significantly lower than our standard entry requirements. **Your studies:** To help bridge the gap between school and university, you’ll cover material from the A Level Mathematics and Further Mathematics syllabuses, along with advanced topics taken from university-level studies preparing you for university. **You will graduate with capabilities including data science, machine learning and communication skills, as well as more specific knowledge skills in areas such as Python, SQL, Java and Hadoop.** **By the end of the programme you will have developed:** 1. systematic understanding of key aspects of knowledge associated with data science and the capability to deploy established approaches accurately to analyse and solve problems using a high level of skill in calculation and manipulation of the material in the following areas: Data mining and modelling, artificial intelligence techniques/statistical machine learning and big data analytics. 2. transferable skills in some or all of: presentations, information retrieval and internet research, report writing, information technology (IT) expertise and the use of statistical and computing software and practical and analytical skills such as software development skills, testing and assessment skills, experimental skills, data gathering and processing skills. **You will also be able to:** 1. apply key aspects of big data science and artificial intelligence/statistical machine learning in well-defined contexts, showing judgement in the selection and application of tools and techniques and of mathematics/statistics and computer technology. 2. plan and develop a project themed in one of data science areas in business, environment, finance, medicine, pharmacy, public health, among others. **Superb student experience** SMSAS and the School of Computing, within the Division of Computing, Engineering and Mathematical Sciences (CEMS), have a thriving student culture, with students from all degree programmes and all degree stages participating in student activities and taking on active roles within the University. As a SMSAS student you benefit from free membership of the Kent Maths Society and Invicta Actuarial Society. You can become a Student Rep and share the views of your fellow students to bring about changes. You could be employed as a Student Ambassador, earning money while you study by inspiring the next generation of mathematicians. Or join one of the society committees and organise socials and events for CEMS students. You will be encouraged to make the most of your time at university and will have access to support and guidance throughout your studies.

Course Details - Modules

Modules are not listed for this Course.

Course Details – Assessment Method

Assessment Methods are not listed for this Course.

Course Details – Professional Bodies

Professional Bodies are not listed for this Course.

How to Apply

26 January This is the deadline for applications to be completed and sent for this course. If the university or college still has places available you can apply after this date, but your application is not guaranteed to be considered.

Application Codes

Course code: G192

Institution code: K24

Campus Name: Main Site

Campus code:

Points of Entry

The following entry points are available for this course:

Foundation

Entry Requirements for Advanced Entry (Year 2 and Beyond)

Entry Requirements for Advanced Entry are not listed for this Course.

International applicants

Standard Qualification Requirements

including Mathematics at grade C. Use of Maths A-level is not accepted as a required subject.

Applications are individually considered by the Admissions Officer

The University will not necessarily make conditional offers to all Access candidates but will continue to assess them on an individual basis. If we make you an offer, you will need to obtain/pass the overall Access to Higher Education Diploma and may also be required to obtain a proportion of the total level 3 credits and/or credits in particular subjects at merit grade or above.

overall or 11 points from three Higher Level subjects, including HL Maths or HL Maths: Analysis and Approaches at 4 or SL Maths or SL Maths: Analysis and Approaches at 6

The University will consider applicants holding BTEC National Diploma and Extended National Diploma Qualifications (QCF; NQF; OCR) on a case-by-case basis. Please contact us for further advice on your individual circumstances.

Please click the following link to find out more about qualification requirements for this course

Minimum Qualification Requirements

Minimum Further Information are not listed for this Course.

English language requirements

Test Grade AdditionalDetails

Applicants should have grade C or 4 in English Language GCSE or a suitable equivalent level qualification.

Please visit our website for further information:

https://www.kent.ac.uk/courses/undergraduate/how-to-apply/english-language-requirements.html

Unistats information

Student satisfaction : 84%

Employment after 15 months (Most common jobs): 56%

Go onto work and study: 85%

Fees and funding

Additional Fee Information

All fees for 2022/23 are to be confirmed. Please see the programme page at www.kent.ac.uk for further information on fees and funding options.

Provider information

Recruitment and Admissions Office
Registry
Address3 are not listed for this Course.
Canterbury
CT2 7NZ

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