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Postgraduate study
Applied Computer Science (Online)

Applied Computer Science (Online) MSc

This conversion master’s course allows you to enter the field of computer science, with insights into programming and applications to meet business needs.

 

Course overview

You gain expertise and transferable skills in event-driven programming, patterns, design, development and deployment using industry-standard tools. You also develop your ability to design and implement machine learning, database, big data and analytics applications.

Your individual computer science project gives you the opportunity to apply your practical and theoretical skills in your chosen specialism.

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Course details

Course structure

Core modules

Agile Development

You gain experience of application development utilising an agile development approach. You also take responsibility for determining project aims, objectives, roles, tasks, deliverables, schedules and documentation.

By learning agile principles and applying a specific agile approach (eg SCRUM) in a live simulation of the methodology, the module will help you to prepare for contemporary practice in industry, developing both knowledge and skills in the application of agile principles.

Big Data and Business Intelligence

You develop your ability to design and implement database, big data and analytics applications to meet business needs. A case study is used to follow the system development lifecycle. You develop a plausible application from inception to implementation for a real-world scenario.

You investigate the issues and technologies associated with implementing and supporting large scale databases and the services that are needed to maintain and access a repository of data. Investigations are undertaken in a number of areas including big data, data warehouses, integrating legacy data, data management and approaches that support the modelling and visualisation of data for a range of use views.

Computing Masters Project

You undertake a major, in-depth, individual study in an aspect of your course. Normally computing master’s projects are drawn from commercial, industrial or research-based problem areas. The project involves you in researching and investigating aspects of your area of study and then producing a major deliverable, for example software package or tool, design, web-site and research findings. You also critically evaluate your major deliverable, including obtaining third party evaluation where appropriate.

The major deliverable(s) are presented via a poster display, and also via a product demonstration or a conference-type presentation of the research and findings. The research, project process and evaluation is reported via a paper in the style of a specified academic conference or journal paper. The written report, the major deliverable and your presentation of the product are assessed.

The project management process affords supported opportunities for goal setting, reflection and critical evaluation of achievement.

Machine Learning

Machine learning is a subfield of computer science concerned with computational techniques rather than performing explicit programmed instructions. You build a model from a task based on observations in order to make predictions about unseen data. Such techniques are useful when the desired output is known but an algorithm is unknown, or when a system needs to adapt to unforeseen circumstances.

You explore statistics and probability theory as the fundamental task is to make inferences from data samples. The contribution from other areas of computer science is also essential for efficient task representation, learning algorithms, and inferences procedures. You gain exposure to a breadth of tasks and techniques in machine learning.

Assessment is an in course assessment (100%).

Research Methods

You develop the knowledge and skills to understand the research process in the field of computing and gain the necessary skills to undertake your masters project. You learn how to evaluate previous academic research and generate evidence material to justify your research. You learn different methods of data generation and develop an understanding of how these methods fit into your primary research, development lifecycle, evaluation of the end user experience, use of academic research literature and research ethics.

Software for Digital Innovation

You gain an introduction to the Python programming language and its application to solving problems in digital innovation. This involves the principles of programming, the syntax and structure of Python, its relevant libraries and modules, and how it is incorporated in existing software tools. You form a solid foundation of producing software solutions to real-world problems.

User Experience Modelling

You gain the underpinning knowledge and skills you need for user experience modelling and design. Study the theoretical foundations of human-computer interaction (HCI), interaction design, product design, and participatory design and development. Apply user experience modelling approaches to the design of software applications and services.?

 

Modules offered may vary.

 

How you learn

Your learning is supported through our online learning environment, where our experienced staff can provide advice and guidance. Opportunities to network with staff and other students enable you to work collaboratively, developing your technical skills and knowledge in a professional and supportive space.

You learn through keynote lectures and tutorials using case studies and examples. Critical reflection is key to successful problem solving and essential to the creative process.

How you are assessed

You are assessed informally throughout the programme, which supports your formal assessments. You are assessed on your subject specific knowledge, cognitive and intellectual skills and transferable skills applicable to the workplace.

 

Entry requirements

A UK bachelor’s honours degree (2.2 minimum) or equivalent overseas qualification.

In addition, international students will require IELTS 6.0 or equivalent.

For general information please see our overview of entry requirements

 

Employability

Career opportunities

A master's degree in computer science offers career opportunities in software development, data science, cybersecurity, artificial intelligence, and IT management. Graduates can work in tech companies, financial institutions, healthcare, government agencies, and start-ups, focusing on software engineering, system architecture, data analysis, and network security. The demand for advanced computing skills ensures strong job prospects and potential for career growth in a variety of innovative and high-impact fields.

 

Learning platform

Our virtual learning environment (VLE) is the platform you use to access your online course

 

Teesside University online learning courses are delivered through the Brightspace Learning Environment.

Here are some of the benefits.

  • You can use it on your smartphone, tablet and computer.
  • And you can use it anytime, so that you can plan your learning to fit your own schedule.
  • It's easy to use and navigate.
  • Modules are set out by topics and themes. You can use the progress bar to understand where you are in your modules, and appreciate your achievements.
  • We support you to become familiar with your VLE, helping you to start learning quickly.
  • You get feedback, help and guidance from tutors throughout your course through the VLE, and you can ask questions at any time.
  • Our tutors use a live activity feed to keep you updated about your course.
  • You can create a student profile, collaborate with other students and take part in online discussion forums.

Software requirements

 
 

Online learning

Online learning allows you to get a university-level qualification from the comfort of your own home or workplace. You'll have access to all of the world-class teaching and support that Teesside University has to offer, but all of your lectures, tutorials and assessments will take place online.

Find out more

University of the Year

Teesside University was named University of the Year at the Edufuturists Awards 2022.

Full-time

  • Not available full-time
 

Part-time

2024/25 entry

Fee for all applicants
£7,380 (£820 for each 20 credits)

More details about our fees

  • Length: 2 years
  • Attendance: 100% online
  • Start date: September
  • Semester dates

Apply now (part-time)

Apply now (part-time)

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Get in touch

Contact us

Email: onlinelearning@tees.ac.uk

Telephone: 01642 738801


Online chat (general enquiries)

 
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