Artificial Intelligence with Data Analytics

Teesside University

United Kingdom, Middlesbrough

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Teesside University

United Kingdom , Middlesbrough

Key Facts

Program Level

Master by Course Work

Study Type

Full Time

Delivery

On Campus

Campuses

Main Site

Program Language

English

Start & Deadlines

Next Intake DeadlinesJanuary-2024

Apply to this program

Go to the official application for the university

Duration 2 year(s)

Tuition Fee

GBP 15,000 / year

Next Intake January-2024

Artificial Intelligence with Data Analytics

About

You strengthen and deepen your skills on the cutting edge of computer science and are prepared to make the transition from programmers to team leaders and designers. Particular features include:

In addition to major themes of artificial intelligence and data analytics, you also focus on a supporting strand of statistical methods and research methods to provide the academic rigour required for postgraduate study and the practical skills for entry to industry.
You experience new trends pervading the software industry that influence a wide range of applications, from supply chain analysis to pharmaceutical manufacture.
You benefit from a range of authentic and engaging learning experiences and assessments.
It is particularly suited to overseas students who wish to develop practical and cutting edge skills for entry to their local computer science industry.
The fixed module diet presents a unique course that encapsulates leading edge skills, solid programming experience, research expertise and industry experience.

If you take the two year course the Advanced Practice (internship) provides an opportunity to improve employment prospects by providing real-world experience to develop new skills and a deeper understanding of the subject.

The MSc Artificial Intelligence with Data Analytics course is designed for graduates seeking to build on your existing skills to develop specific expertise in the field of artificial intelligence and data analytics.

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 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 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 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.

Statistical Methods for Data Analytics

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.

Disciplines

Computing & Cyber Security

Requirements

Entry Requirements

A bachelor degree with a minimum of 65%, 2.5/4.0 or good

Fee Information

Tuition Fee

GBP 15,000

How to Apply

Applying Online - Information Required to Complete Your Application

Personal Details

- Full Name, including title
- Sex
- Date of Birth
- E-mail Address
- Telephone Number
- Home and Correspondence addresses, including postcode
- Alternative email Addresses
- Country of Permanent Residence or Local Authority
- Country of Birth
- Nationality
- Ethnicity - this data will not be accessible to those making the application decision
- Type of applicant - choose from UK/EU or Overseas
- Who is entering the application - choose from Applicant, University Staff/Overseas Office or Other Third Party
- Disability
- Whether your parents/guardians have Higher Education qualifications
- Details of any previous study or application to this University

Payment of Fees

- Who is paying your fees
- Name and address of your Fee Payer
- Details of any previous funding body and previous course

Overseas Applicants Only

- Date of entry to UK/EU
- Passport Number (if you need a visa)
- Previous UK study, including details of any previous visas, overstays in the UK and visa refusals

University Staff and Office/Agent Applications Only

- School/Office Code
- Agent Code
- Agent Name
- Agent Company
- Reference Number

Qualifications

Qualifications Held (maximum of 6)
(For certain courses e.g. Summer University courses & other short courses, this information is not requested)

- Year and month awarded
- Qualification type, level and subject
- Grade
- Awarding Establishment e.g. College/University Name

Qualifications Pending (maximum of 6)
(For certain courses e.g. Summer University courses & other short courses, this information is not requested)

- Year and month of exam
- Qualification type, level and subject
- Date grade expected
- Awarding Establishment e.g. College/University Name

Highest qualification

Portfolio Details

Foreign Language Courses Only

- Qualifications and experience in chosen language
- where more than one occurence of a courses runs in paralell, indicate which group you wish to join

Professional Qualifications

- Professional/Statutory Body and Registration PIN
- Other course specific professional details as required

School of Health & Social Care courses only

- NHS PIN
- NHS Trust / Practice details
- National Insurance Number
- Assignment/Employee Number
- Line manager name and email address
- Full or part time
- Pay band
- Profession, Staff Group and Job Role
- Other course specific details as required

Social Work Practice Education courses only

- Social Work Registration Number

Erasmus Applications

Details of the Exchange Co-ordinator at Your Home Institution
- Name
- Position
- Email Address

Higher and Degree Apprenticeships

- Unique Learner Number
- National Insurance Number
- *Employer Code
- *Employer Postcode (This is your normal place of work which may be different from the company's main postcode)
- *Number of employees at this postcode
- Highest level qualifications in English language and mathematics

*Your employer should be able to supply this information

Last Two Education Establishments Attended
(For certain courses e.g. Summer University courses & other short courses, this information is not requested)

- Name and address
- Dates from and to
- Full or Part time
- Level of study

English Language Ability
(For certain courses e.g. Summer University courses & other short courses, this information is not requested)

Whether English is your first language

If not

- IELTS - score, date of exam and Test Report Form Number
- Other test - name, score and date of exam

Work Experience (maximum of 2)
(For certain courses e.g. Summer University courses & other short courses, a reduced set of employment information is requested)

- Employers name
- Job title
- Dates from and to
- Full or Part time
- Main responsibilities

Summer & Winter University Courses Only

- Whether you are enrolled or due to enrol on a college or university course
- If so, where and which course
- Whether you are thinking of starting a Higher Education course
- If so, area of interest/study
- Reason for applying to Summer/Winter University

Referee
(For certain courses e.g. Summer University courses & other short courses, this information is not requested)

- Name
- Address
- Other contact details

Note : some course will require two referees, e.g. PHD courses

Personal Statement
(For certain courses e.g. Summer University courses & other short courses, this information is not requested)

Can be uploaded as a document or entered as text

It is suggested that your statement is prepared electronically in advance of starting the application

Enrolment

Some short courses may ask you to provide enrolment information as part of the application. This will require extra details but also means you will not be asked to complete the full on-line registration process at a later date.

This data will not be accessible to those making the application decision

- Type of Term-time Accomodation
- Next of Kin Name
- Next of Kin Telephone Number
- Next of Kin Relationship
- Religious Beliefs
- Criminal Conviction Declaration

Documents currently available for upload
(For certain courses e.g. Summer University courses & other short courses, this option is not available)

- Reference
- Personal Statement
- CV
- Results
- Proof of English Language Qualifications, e.g. IELTS or TOEFL certificate
- Passport
- Previous Visas
- Previous Visa Refusals

For Research courses, the following additional uploads are mandatory

- Research Proposal
- Research Training Document
- Research Personal Statement
- Research Sponsorship/funding letter