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Postgraduate study
Applied Data Science (Online)

Applied Data Science (Online) MSc

Data scientists are responsible for the handling of raw data, analysing it, identifying patterns and presenting insights for forecasting and predicting business problems. Data science uses maths, statistics, machine learning, a range of computer science disciplines and a common toolset such as Python, SQL, and R.

 

Course overview

Data scientists are in high demand as government departments and leading companies realise the importance of big data and its applications to developing successful strategies in their decision making or business relations.

You gain technical and critical thinking skills in applying knowledge of data science to real-world problems, and learn fundamentals of software for digital innovation, applied machine learning, big data and business intelligence, interactive visualisation of data, and applications. You explore professional, ethical, security and social implications of future data science technologies.

Progressing from almost any first degree discipline, you gain leading-edge skills, solid programming experience, research expertise and optional industry experience to enter this field and rapidly expanding job market.

You may be eligible for a £10,000 Artificial Intelligence and Data Science Office for Students Scholarship to support your studies.

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Course details

Course structure

Core modules

Artificial Intelligence Ethics and Applications

You gain a deep insight into the business applications of artificial intelligence (AI) and data science (DA). You explore a range of AI and DS applications such as chatbots, virtual assistants, medical diagnosis, biometric recognition, personalisation, fraud detection and autonomous machines, and analyse both the risks and opportunities of applying AI and DS techniques in these areas.

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.

Data Science Foundations

Gain an introduction to core data science concepts and tools, focusing on real-life data science problems with practical exposure to relevant software. Topics such as preparing and working with data, data visualisation and databases are covered.

Interactive Visualisation

Dynamic, interactive visualisations enable the reader to explore the data for themselves through a variety of perspectives. Static visualisations are excellent for print medium but are restricted to showing a single perspective and do not handle multidimensional datasets well. Using an interactive graphic the reader can zoom in on sections of the data which are of interest, explore more than one dimension at a time, and sort and filter to discover new patterns and themes within the data. Particularly useful is the ability to provide a macro/micro view of the same data, ie a big picture view of the full dataset from which the reader can then ‘drill down’ into the lower level detail.

This module uses the javascript library for Data-Driven Documents (D3js) for creating animated, dynamic graphics for the web, and looks at other alternatives available.

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%).

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.

 

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.

You learn through keynote lectures and tutorials using case studies and examples.

How you are assessed

You are assessed informally throughout the programme to help you prepare for your formal course 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 any subject.

International students will require IELTS 6.0 or equivalent.

For general information please see our overview of entry requirements

 

Employability

Career opportunities

Companies hiring data science professionals include American Express, AstraZeneca, BBC, IBM, Mastercard, Rolls Royce, Space Ape Games, Warner Bros. Entertainment, WhatsApp, plus many more.

Graduates can expect to find employment in one of the increasing number of sectors needing specialists equipped with the cutting-edge expertise in financial and digital technologies.

According to itjobswatch.co.uk, the median salary in the UK for data science professionals is £65k but the top 10% can earn upwards of £100k.

 

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

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Get in touch

Contact us

Email: onlinelearning@tees.ac.uk

Telephone: 01642 738801


Online chat (general enquiries)

 

Open days and events

Wed

16

Oct

Postgraduate open day

9.00am - 3.00pm

Middlesbrough campus, On campus


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Sat

23

Nov

Postgraduate open day

9.00am - 3.00pm

On campus


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