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Postgraduate study
 
  • Apply now to start in January or September 2021.
  • Course changes for 2020/21: for a safe environment and a great student and learning experience.
 

Course overview

Artificial intelligence (AI) is increasingly important in developments in all parts of business and society. The School has active research groups in machine learning and intelligent systems, and AI related modules.

The course gives you specialist skills in artificial intelligence, opening the door to a range of careers. You will develop strong theoretical and technical knowledge and skills including a thorough grounding in data analytics and specialist skills in artificial intelligence, which will provide the directly transferable skills for a career in the field of AI.

You will explore state-of-the-art technologies, concepts and theories, supported by a thriving active research community. You will develop specialist knowledge and experience in the development of intelligent systems. Topics studied will include machine learning, A I Programming, research and statistical methods and data analytics.The distinctive nature of the award is the close integration with our AI and Machine Learning research groups coupled with the opportunity for an internship and a highly supportive environment, particularly for international students.The course also provides you with directly transferable skills for a career in a range of industries from the finance sector to healthcare to automotives, as well as progression opportunities to PhD research There are three routes you can choose from to gain an MSc Artificial Intelligence:full-time - 2 years with advanced practice (September and January start)full-time - 1 year (September start) or 16 months (January start)part-time - 2 years.

 

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.

Computing Master's 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 Analytics

This module provides you with the core principles and practical skills to apply state-of-the-art computational methods to perform data analytics. The skills are very important in the new horizon of data analysis where existing massive amount of data contains valuable knowledge, which is critical for prediction and decision-making. Due to its characters (3V: volume, velocity, and variety), computational methods are required to extract such knowledge.

You form a solid foundation of both descriptive and predictive analytics, which refers to tools and techniques for building statistical or machine learning models to make predictions and decisions based on data. Practical guidance about how to handle unlabelled, noisy, incomplete, large-scale data is discussed and you learn how to select the best technique to handle different type of data in different scenarios.

Intelligent Decision Support Systems

You focus on the fundamentals of tackling decisions of increasing difficulty in technology, health and business decision, and gain an understanding about the need for, and the effectiveness of, computerised methods for supporting decisions. This includes classifications, data mining and knowledge management-based decision methods with examples of various application domains.

You will be provided with the opportunity to implement simple computerised decision support systems applied to specific real-life problems. The process and practices develop your ability to build simple versions of decision support systems and familiarity with full-scale versions of decision support systems for various application domains.

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 gain the knowledge and skills to understand the research process in computing and digital media, and the necessary skills to undertake your masters project. You learn how to use and critically evaluate previous academic research, and to generate good evidence material to justify their professional practice. This involves you learning about different research strategies and data generation methods and how they fit into the development lifecycle and the evaluation of the user experience, the use of the academic research literature, and research ethics.

Assessment involves you preparing a research proposal which can form the basis of your master's project.

Statistical Methods

You develop necessary knowledge and practical understanding of the main statistical techniques. You explore quantitative and qualitative data analysis techniques, reflecting scientific and social science methods. You focus on correlation testing, regression, data categories, normalization - the tools needed, rather than the philosophical approaches. You understand how to apply valid techniques and interpret the results in preparation for experimental work.

Your assessment is a single ICA based around a number of case studies that require you to identify the correct data analysis and modelling processes.

 

Advanced practice (2 year full-time MSc only)

Internship

The internship options are:

Vocational: spend one semester working full-time in industry or on placement in the University. We have close links with a range of national and international companies who could offer you the chance to develop your knowledge and professional skills in the workplace through an internship. Although we cannot guarantee internships, we will provide you with practical support and advice on how to find and secure your own internship position. A vocational internship is a great way to gain work experience and give your CV a competitive edge.

Research: develop your research and academic skills by undertaking a research internship within the University. Experience working as part of a research team in an academic setting. Ideal for those who are interested in a career in research or academia.


 

Modules offered may vary.

 

How you learn

You learn about concepts and methods primarily through keynote lectures and tutorials using case studies and examples. Lectures include presen-tations from guest speakers from industry. Critical reflection is key to successful problem solving and essential to the creative process. You de-velop your own reflective practice at an advanced level, then test and assess your solutions against criteria that you develop in the light of your research.

How you are assessed

The programme assessment strategy has been designed to assess your subject specific knowledge, cognitive and intellectual skills and transferable skills applicable to the workplace. The strategy ensures that you are provided with formative assessment opportunities throughout the programme which support your summative assessments. The assessments will include assignments, tests, case studies, presentations, research proposal and literature review, and the production of a dissertation. The assessments may include individual or group essays or reports. The assessment criteria, where appropriate, will include assessment of presentation skills and report writing.

 
 

Entry requirements

You will normally have a first degree in related discipline (2.2 minimum) or relevant experience or equivalent qualifications.

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

For additional information please see our entry requirements

International applicants can find out what qualifications they need by visiting Your Country

 

Employability

Career opportunities

In recent years, careers in artificial intelligence (AI) have grown significantly to meet the demands of digitally transformed industries. There are plenty of jobs in artificial intelligence, however coupled with that is a significant shortage of top tech talent with the necessary skills, ie there will be a skills shortage in this field leading to increased demand for talented individuals with this skillset.

Careers in AI include business intelligence developer, data scientists, AI developer and big data engineers.

Throughout your course we offer a wide range of business networking opportunities for you to extend your knowledge of the industry and show case your skills, enhancing your opportunity of securing your dream job. We host events such as:-

ExpoTees our end of course showcase of graduate work which attracts over 150 business partners each year, these are businesses who are looking for the emerging talent in the digital fields.

Drawing on our extensive industry links we invite guest speakers in your field to present to our students. Throughout your course we bring in industry speakers to ensure that you develop your knowledge of the industry that you plan to build your career in. In addition to covering technical subjects these speakers provide an insight into what employers are looking for in their employees, from technical to professional skills.

 

Information for international applicants

Qualifications

International applicants - find out what qualifications you need by selecting your country below.

Select your country:

  
 

Useful information

Visit our international pages for useful information for non-UK students and applicants.

Talk to us

Talk to an international student enrolment adviser

 
 

Full-time

2020/21 entry

Fee for UK/EU applicants
£6,500 a year

£4,335 a year with advanced practice

More details about our fees

Fee for international applicants
£13,000 a year

£7,500 a year with Advanced Practice

More details about our fees for international applicants

  • Length: within 1 year (September start), 16 months (January start) or 2 years with advanced practice (September or January start)
  • Enrolment date: September or January
  • Semester dates

Apply online (full-time)

Apply online (fast-track) for current students

 

Part-time

2020/21 entry

Fee for UK/EU applicants
£722 for each 20 credits

More details about our fees

  • Length: Up to 3 years (can be completed in 2 years if preferred)
  • Enrolment date: September or January
  • Semester dates

Apply online (part-time)

Apply online (fast-track) for current students

 
 
 

Choose Teesside

Progress

Stand out from other job applicants with your higher level qualification, specialist knowledge and expanded networks.

 

Skills

Improve your project management, critical thinking, research skills, time management, presentation skills and teamwork.

 

Earnings

The median salary for working-age (16-64) postgraduates in 2018 was £6,000 more than graduates
(DoE Graduate Labour Market Statistics 2018, tees.ac.uk/source)

 

Campus

Study in our friendly town-centre campus with over £270m recently invested and another £300m over the next 10 years.

 

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