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Data Science and Analytics

Course overview

(BSc) Bachelor of Science
Data Science and Analytics
Current
University of Essex
University of Essex
Mathematical Sciences
Colchester Campus
Honours Degree
Full-time
None
BSC I1G3
http://www.essex.ac.uk/students/exams-and-coursework/ppg/ug/default.aspx
15/04/2017

A-levels: BBB, including Mathematics
Please note we are unable to accept A-level Use of Mathematics in place of A-level Mathematics

IB: 30 points, including Higher Level Mathematics grade 5. We are also happy to consider a combination of separate IB Diploma Programmes at both Higher and Standard Level.

Exact offer levels will vary depending on the range of subjects being taken at higher and standard level, and the course applied for. Please contact the Undergraduate Admissions Office for more information.

English language requirements for applicants whose first language is not English: IELTS 6.0 overall. Different requirements apply for second year entry, and specified component grades are also required for applicants who require a Tier 4 visa to study in the UK.

Other English language qualifications may be acceptable so please contact us for further details. If we accept the English component of an international qualification then it will be included in the information given about the academic levels listed above. Please note that date restrictions may apply to some English language qualifications

If you are an international student requiring a Tier 4 visa to study in the UK please see our immigration webpages for the latest Home Office guidance on English language qualifications.

If you do not meet our IELTS requirements then you may be able to complete a pre-sessional English pathway that enables you to start your course without retaking IELTS.

Additional Notes

If you’re an international student, but do not meet the English language or academic requirements for direct admission to this degree, you could prepare and gain entry through a pathway course. Find out more about opportunities available to you at the University of Essex International College here.

External Examiners

Prof Fionn Murtagh
Professor of Data Science

External Examiners provide an independent overview of our courses, offering their expertise and help towards our continual improvement of course content, teaching, learning, and assessment. External Examiners are normally academics from other higher education institutions, but may be from the industry, business or the profession as appropriate for the course. They comment on how well courses align with national standards, and on how well the teaching, learning and assessment methods allow students to develop and demonstrate the relevant knowledge and skills needed to achieve their awards. External Examiners who are responsible for awards are key members of Boards of Examiners. These boards make decisions about student progression within their course and about whether students can receive their final award.

Key

Core You must take this module You must pass this module. No failure can be permitted.
Core with Options You can choose which module to study
Compulsory You must take this module There may be limited opportunities to continue on the course/be eligible for the degree if you fail.
Compulsory with Options You can choose which module to study
Optional You can choose which module to study

Year 1 - 2019/20

Component Number Module Code Module Title Status Credits
01 CE101-4-FY Team Project Challenge Core 15
02 MA181-4-AU Discrete Mathematics Core 15
03 MA108-4-SP Statistics I Core 15
04 CE151-4-AU Introduction to Programming Core 15
05 CE152-4-SP Object-Oriented Programming Core 15
06 CE153-4-AU Introduction to Databases Core 15
07 MA101-4-FY Calculus Core 30

Year 2 - 2020/21

Component Number Module Code Module Title Status Credits
01 CE291-5-FY Team Project Challenge (CS) Core 15
02 CE205-5-AU Databases and Information Retrieval Compulsory 15
03 CE213-5-AU Artificial Intelligence Compulsory 15
04 MA200-5-AU Statistics II Compulsory 15
05 MA216-5-SP Survival Analysis Compulsory 15
06 MA205-5-SP Optimisation (Linear Programming) Compulsory 15
07 CE204-5-SP Data Structures and Algorithms Compulsory 15
08 MA114-5-AU Matrices and Complex Numbers Compulsory 15
09 MA199-5-FY Mathematics Careers and Employability Compulsory 0

Year 3 - 2021/22

Component Number Module Code Module Title Status Credits
01 MA838-6-FY Capstone Project: Data Science and Analytics Core 45
02 MA317-6-AU Modelling Experimental Data Compulsory 15
03 MA321-6-SP Applied Statistics Compulsory 15
04 CE306-6-SP Information Retrieval Compulsory 15
05 MA199-6-FY Mathematics Careers and Employability Compulsory 0
06 Option(s) from list Compulsory with Options 30

Exit awards

A module is given one of the following statuses: 'core' – meaning it must be taken and passed; 'compulsory' – meaning it must be taken; or 'optional' – meaning that students can choose the module from a designated list. The rules of assessment may allow for limited condonement of fails in 'compulsory' or 'optional' modules, but 'core' modules cannot be failed. The status of the module may be different in any exit awards which are available for the course. Exam Boards will consider students' eligibility for an exit award if they fail the main award or do not complete their studies.

Programme aims

1) To equip students with the knowledge and skills that are currently in high demand in the computing industry and the wider economy
2) To provide students with a foundation for further study and research
3) To enable students to acquire an understanding of computer science, mathematics and statistics as well as business analysis
4) To develop the student’s ability to make an effective contribution to team-based activity
5) To encourage students to adopt an investigative approach and develop autonomous study skills in order to ensure their continuing professional development
6) To provide students with an understanding of the industrial context and an appreciation of a range of external factors that affect the work of a data analyst and computing professional
7) To provide students with experience of the transition to University level

Learning outcomes and learning, teaching and assessment methods

On successful completion of the programme a graduate should demonstrate knowledge and skills as follows:

A: Knowledge and understanding

A1 Principles, techniques and proceses of project management.
A2 The industrial context and the professional, legal and ethical responsibilities of data analysts and computing professionals.
A3 Mathematical principles that underpin the analysis and generation of computer models and algorithms.
A4 Programming models, languages and development environments.
A5 Computer systems, including computer architecture, operating systems, embedded computer systems and computer networks.
A6 Information systems, including data modelling, database design, information retrieval and visualisation and access via interactive web pages.
A7 Systems analysis and software development processes.
A8 Principles, techniques and applications in those areas of Data Science and Analytics in which the student has chosen to develop special expertise.
A9 Experience of the transition into higher education.
Learning Methods: Lectures are the principal method of delivery for the concepts and principles involved in A1 - A9. Students are also directed to reading from textbooks, academic papers and material available on-line.
Understanding is reinforced by means of exercise classes, discussion groups, laboratories, assignments and project work.
Specialist knowledge (A8) is further developed during supervision of the final year individual project.
Transition into higher education (A9) is obtained in all level 3 modules.
Assessment Methods: Achievement of knowledge outcomes is assessed primarily through unseen closed-book examinations, and also through marked coursework.
An assessment of the understanding of underlying concepts and principles forms part of the overall assessment of the final year individual project report and oral presentation.

B: Intellectual and cognitive skills

B1 Analyse a given problem and select the most appropriate methods for its solution.
B2 Evaluate the relative strengths of a range of theories, techniques, tools, languages, etc. used in the design and construction of computer-based systems
B3 Interpret the contents of articles and other sources and form a critical judgement of their relative importance and relevance to an area of study.
B4 Construct informed, succint and reasoned descriptions of, and proposals for, computer-based systems.
Learning Methods: The basis for intellectual skills is provided in lectures, and they are developed by means of recommended reading, guided and self directed study, assignments and project work.
B1 is a key element of most assignments project work.
B2 is developed through exercises and exposure to a range of systems software.
B3 is developed through guided reading and tutor led discussion groups.
B1 - B4 are all important aspects of the final year project, and are developed in the course of individual supervision.
Assessment Methods: Achievement of intellectual skills is assessed primarily through unseen closed-book examinations, and also through marked assignments and project work.

C: Practical skills

C1 Make effective use of a range of theories, techniques, programming languages, operating systems, design support tools and development environments.
C2 Specify, design, implement, test and document a computer-based system.
C3 Work as a member of a team, contributing to the planning and execution of a system development task.
C4 Propose, plan, undertake and report a self-directed individual programme of investigation, design and implementation.
Learning Methods: Practical skills are developed in exercise classes, laboratory classes, assignments and project work.
C1 is developed through exercises and exposure to a range of systems software.
Various aspects of C2 are acquired in programming, software engineering and other assignments, and further developed in team and individual project work.
C3 is developed in group assignments and the first and second year team projects.
C4 is developed during the supervision of the final year individual project.
Assessment Methods: Achievement of practical skills is assessed through marked coursework, project reports, oral presentations and demonstrations of completed systems.

D: Key skills

D1 Communicate effective in written reports and oral presentations using appropriate terminology and technical language.
D2 Retrieve information using search engines, browsers and catalogues; use appropriate IT facilities to prepare and present technical reports in various formats (documents, oral presentations).
D3 Use mathematical techniques in the processes of analysis and design.
D4 Analyse complex problems and design effective solutions.
D5 Plan and manage team projects using available support tools; work effectively as part of a team.
D6 Organise activity and manage time in a programme of self-directed study.
Learning Methods: Students learn key skills in research, problem solving, communication and team project work in the first year module CE101, and thereafter the development of key skills forms an integral part of their overall learning activity. In particular
D1 and D2 are developed in team and individual project work.
D2 is developed through the use of the internet as a major information source, and practice in the use of tools such as Word and PowerPoint.
D3 and D4 are developed in exercises and assignments.
D5 is developed in group assignments and the first and second year team projects.
D6 is developed in the final year individual project.
Assessment Methods: Assessment of the key skills D3 and D4 is intrinsic to subject based assessment.
The assessment of project work includes specific allocations of credit for project management (D5, D6) and the quality of presentations (D1 and D2).
An individual's contribution to team projects (D5) is determined by means of a submission containing reflective and self-assessment components.
The assessment of the final year individual project report includes specific allocation of credit for the quality, extent and relevance of a bibliography, including internet sources (D2).


Note

The University makes every effort to ensure that this information on its programme specification is accurate and up-to-date. Exceptionally it can be necessary to make changes, for example to courses, facilities or fees. Examples of such reasons might include a change of law or regulatory requirements, industrial action, lack of demand, departure of key personnel, change in government policy, or withdrawal/reduction of funding. Changes to courses may for example consist of variations to the content and method of delivery of programmes, courses and other services, to discontinue programmes, courses and other services and to merge or combine programmes or courses. The University will endeavour to keep such changes to a minimum, and will also keep students informed appropriately by updating our programme specifications.

The full Procedures, Rules and Regulations of the University governing how it operates are set out in the Charter, Statutes and Ordinances and in the University Regulations, Policy and Procedures.

Should you have any questions about programme specifications, please contact Course Records, Quality and Academic Development; email: crt@essex.ac.uk.