MSc Data Science (Part Time 3 Year)

Key details

MSC DATA SCIENCE (PART TIME 3 YEAR)

Start Year

2023

Attendance

Part Time

Award

Degree of Master of Science

Duration (years)

Great business decisions are underpinned by high quality data. As a data scientist you are absolutely integral to the success of an organisation – you will source, analyse and utilise vast amounts of data to support strategic decision-making.

If that’s where you aspire to be, then this course is for you. You'll gain an advanced practical and theoretical grounding in data mining and statistics, with the chance to customise your degree through modules in artificial intelligence, visualisation, programming and database manipulation.

We have a large data mining, machine learning and statistics research group, which has made significant contributions to the field in the last 20 years, so you’ll be working directly with pioneering experts.

Data scientists are highly prized in almost any industry, so you’ll have great graduate career prospects as well as a wide range of transferable skills.

About

The unique structure of this course offers a truly part-time route for mature professionals to supplement their work with an accredited qualification. The MSc requires students to study one module per semester over a three-year period. The timetable for this course is designed so that students are able to study alongside working, and contact time for each module is scheduled as a maximum of one day per week.

The course follows the successful model of the KDD MSc (Industry Based), which we have run for our partner Aviva for over 18 years. During this time, we have produced more than 80 outstanding graduates for Aviva, bolstering their workforce with Master’s-level recognition.

The course was short-listed as one of the most innovative collaborations between Business and a university by the East of England Development Agency.

This MSc is one of the few similar academic qualifications to have been conceived and developed to meet the specific needs of industry partners.

The course teaches skills which are directly relevant to industry, as the sector increasingly seeks to expand its use of data analytics.

Students will be able to see the direct impact of the course on their vocational work, as the dissertation is normally based on a project using their company’s data. This will allow students to integrate their university dissertation into their job, putting the principles they have learnt from the classroom into practice.

Companies will directly benefit from a relationship with the university which will involve access to state-of-the-art expertise in topical subjects such as data mining, statistics and visualisation as well as artificial intelligence and database manipulation.

The MSc represents excellent value for money, as employers are able to part fund high quality training to incentivise staff and increase retention. The added bonus of only having to give participants a single day off per module during term time makes the programme much more cost effective than other similar programmes.

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Important Information

Whilst the University will make every effort to offer the courses listed, changes may sometimes be made arising from the regular review of course programmes. Where this activity leads to significant (but not minor) changes to programmes, there will normally be prior consultation of students and others. Changes 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 inform students.

Assessment for Year 1

We have a mixture of individual and group assessments. These include written work, presentations or demonstrations, and exams (closed and/or time-limited assessment). They combine theoretical understanding with practical application and are designed to test the range of skills and competencies required for the learning outcomes of each module. The balance of assessment types varies according to the options chosen. Additionally, there is an individual project which is assessed through a combination of written work and demonstration or presentation.

Structure

On this course, you’ll take compulsory modules in research techniques, data mining, statistics and artificial intelligence or visualisation.

Alongside this, you’ll take two optional modules from a range – which may include applications programming, database manipulation, human computer interaction, computer vision or a research topic.

A key element of the course is your dissertation, which will give you the chance to explore a topic or work on a problem (which may be with an industry partner) in depth, under the supervision of a member of faculty. 

Recent dissertation titles include:

Classification rule induction for atmospheric circulation patterns
Keyword-based email classification
Data analysis of orthopaedic operations

Teaching and Learning

The course has both theoretical and practical elements, so you’ll get hands on experience in data mining and statistical programming environments. You will even have the opportunity to participate in commercial data mining projects as part of your assessment, gaining experience on all the stages of the KDD process.

Independent study

Your individual study (around 7 hours per week) will complement the formal teaching and will evolve along with your skills and expertise in data analysis. Beginning with an initial focus on the basics of programming and data manipulation, you’ll move on to much deeper study and appreciation of specialist topics such as data mining and statistics.

Your dissertation will also form a key part of your course, which will involve extensive independent study supported by your supervisor.

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Assessment for Year 2

Structure

Part-time students will take the required compulsory modules and will choose optional modules according to their programme's profile. However, there will be flexibility on which year students take particular modules and choices will be made in conjunction with the academic adviser to ensure the best fit to work and other commitments.

Teaching and Learning

Independent study

Your dissertation will also form a key part of your course, which will involve extensive independent study supported by your supervisor.

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Assessment for Year 3

Structure

Teaching and Learning

As you will be engage in one module per semester, you will have an average of between 4 to 5 hours of contact time per week with teaching staff, depending on your module choices. This will be made up of a mixture of lectures, seminars and lab classes – where the lab and seminar classes reinforce and expand on the lecture material. The course has both theoretical and practical elements, so you’ll get hands on experience in data mining and statistical programming environments. You will even have the opportunity to participate in commercial data mining projects as part of your assessment, gaining experience on all the stages of the KDD process.

Independent study

Your dissertation will also form a key part of your course, which will involve extensive independent study supported by your supervisor.

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Assessment for Year 1

Compulsory Modules

Optional A Modules

(40 credits)

APPLICATIONS PROGRAMMING

Code CMP-7000A

Credits 20

This module aims to establish a clear understanding of Software Development, from the initial application programming through to full development of a software program, including a structured Technical Design Document. You will be introduced to a modern programming language used in many Industries (Python), was well as the standard processes for software design. The module will provide you with the fundamental skills and knowledge for working in a range of computing science industries.

AUDIO AND VISUAL PROCESSING

Code CMP-7016A

Credits 20

This module explores how computers process audio and video signals. In the audio component, the focus is on understanding how humans produce speech and how this can be processed by computer for speech recognition and enhancement. Similarly, the visual component considers the human eye and camera, and how video is processed by computer. The theoretical material covered in lectures is reinforced with practical laboratory sessions. The module is coursework only and requires you to build a speech recogniser capable of recognising the names of students studying the module using both audio and visual speech information.

HUMAN COMPUTER INTERACTION

Code CMP-7018A

Credits 20

Human Computer Interaction (or UX) covers a very wide range of devices, including conventional computers, mobile devices and “hidden” computing devices. In this module you will learn about interactions from a variety of perspectives, such as cognitive psychology, ethnographic methods, security issues, UI failures, the principles of good user experience, heuristic and experimental evaluation approaches and the needs of a range of different audiences.

INFORMATION VISUALISATION

Code CMP-7022B

Credits 20

This module is an introduction to information visualisation. You will learn techniques for summarising and presenting a wide range of data. There is a strong emphasis on understanding the appropriate context and use of visualisation techniques. You will also learn about problems and techniques for dealing with large data flows and issues of integrating multiple data sources.

DATA MINING

Code CMP-7023B

Credits 20

This module is designed for postgraduate students studying on MSc courses. You will explore the methodologies of Knowledge Discovery and Data Mining (KDD). You will cover each stage of the KDD process, including preliminary data exploration, data cleansing, pre-processing and the various data analysis tasks that fall under the heading of data mining, focusing on clustering, classification and association rule induction. Through this module, you will gain knowledge of algorithms and methods for data analysis, as well as practical experience using leading KDD software packages.

DATABASE MANIPULATION

Code CMP-7025A

Credits 20

This module introduces you to important aspects of databases, database manipulation and database management systems. The module is based on the relational model. You will explore the tools and methods for database design and manipulation as well as the programming of database applications. Part of the practical experience you will gain will be acquired using a modern relational database management system. You will also gain programming experience using SQL, and using a high level programming language to write applications that access the database.

COMPUTER VISION

Code CMP-7026B

Credits 20

Computer Vision is about “teaching machines how to see”. You will study methods for acquiring, analysing and understanding images in both lectures and laboratories. The practical exercises and projects that you undertake in the laboratory will support the underpinning theory and enable you to implement contemporary computer vision algorithms.

ARTIFICIAL INTELLIGENCE

Code CMP-7028B

Credits 20

This module will introduce you to core techniques in Artificial Intelligence. Topics covered may include state space representation and search algorithms, knowledge representation, expert systems, Bayesian networks, Markov Models, Neural networks, Deep learning and an Introduction to Robotics and Drone.

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Important Information

Whilst the University will make every effort to offer the modules listed, changes may sometimes be made arising from the annual monitoring and review of modules. Where this activity leads to significant change to a programme and modules, the University will endeavour to consult with affected students. The University may not be able to offer a module for reasons outside of its control, such as the illness of a member of staff. Availability of optional modules may be restricted owing to timetabling, lack of demand, or limited places. Where this is the case, you will be asked to make alternative module choices and you will be supported during this process.

This is your SECOND year of study.

Assessment for Year 2

Compulsory Modules

RESEARCH TECHNIQUES (RESEARCH METHODS)

Code CMP-7030Y

Credits 20

This module aims to prepare postgraduate students with necessary intellectual and practical skills for successfully carrying out research work for their MSc Dissertation in Computing Sciences and Computational Biology. Specifically, it teaches research methodologies, techniques and tools used in computing sciences. More importantly, it provides systematic training to enhance students' transferable skills and their understanding in ethics, social and legal issues involved in computing professions.

Optional A Modules

(20 credits)

APPLICATIONS PROGRAMMING

Code CMP-7000A

Credits 20

AUDIO AND VISUAL PROCESSING

Code CMP-7016A

Credits 20

HUMAN COMPUTER INTERACTION

Code CMP-7018A

Credits 20

INFORMATION VISUALISATION

Code CMP-7022B

Credits 20

DATA MINING

Code CMP-7023B

Credits 20

DATABASE MANIPULATION

Code CMP-7025A

Credits 20

COMPUTER VISION

Code CMP-7026B

Credits 20

ARTIFICIAL INTELLIGENCE

Code CMP-7028B

Credits 20

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Open Days

Important Information

This is the THIRD year of study

Assessment for Year 3

Compulsory Modules

DISSERTATION

Code CMP-7027X

Credits 60

In this module, each Masters student is required to carry out project work with substantial research and practical elements on a specified topic for their MSc dissertation from January to late August. The topic can be chosen and allocated from the lists of proposals from faculty members, or proposed by students themselves with an agreement from their supervisor and also an approval from the module organiser. The work may be undertaken as part of a large collaborative or group project. A dissertation must be written as the outcome of the module.