Artificial Intelligence

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https://www.bcu.ac.uk/courses/artificial-intelligence-bsc-hons-2027-28

Artificial Intelligence - BSc (Hons) - 2027/28 Entry | Birmingham City University

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Artificial Intelligence - BSc (Hons)

Currently viewing course to start in 2027/28 Entry.

Developing skills in artificial intelligence is one of the biggest challenges facing industries both globally and nationally today. This BSc Artificial Intelligence degree is designed to tackle industry demands and equip you with cutting-edge skills in deep learning, natural language processing, computer vision, cloud computing, and Generative AI....

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Undergraduate

Study mode

Full Time

BSc (Hons)

Start date

September 2027

View course fees

Computing

Location

City Centre

This course is:

Available with Professional Placement year

Open to International Students

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Overview

Computing at BCU

Developing skills in artificial intelligence is one of the biggest challenges facing industries both globally and nationally today. This BSc Artificial Intelligence degree is designed to tackle industry demands and equip you with cutting-edge skills in deep learning, natural language processing, computer vision, cloud computing, and Generative AI. These capabilities will enable you to deliver intelligent software solutions that power innovation across the modern economy and contribute towards the future of society. You will graduate prepared for careers like Artificial Intelligence Engineer, Machine Learning Specialist, Data Scientist, and Natural Language Processing Developer.

What's covered in this course?

Throughout the course, you will have opportunities to interact with a curriculum that is supported by commercial and industrial content and partners.

In your first year, modules at the start of the course are mostly common with other Computing and AI courses to ensure a strong technical foundation in the field. You will develop an understanding of programming, algorithms and data structure, computer systems, and web development, while also being introduced to artificial intelligence, and innovation through dedicated projects.

In your second year, you’ll study specialised modules in artificial intelligence and machine learning, natural language processing, computer vision, and software deployment using machine learning operations. You'll also gain solid experience in backend development, object-oriented programming, and database engineering, enabling you to build and train intelligent systems.

In your final year, you will explore advanced AI technologies such as deep neural networks, generative AI, cloud computing, deep neural networks and ethics, and modern data storage systems - as well as ethical and societal implications of AI solutions. A major highlight of your final year is the individual project, where you'll tackle a real-world AI problem, applying your knowledge to research, design, implement, and evaluate a comprehensive solution. This capstone project helps prepare you for professional roles and demonstrates your capabilities to future employers.

Additionally, you will have the opportunity to take a professional placement year between your second and third year, which we highly recommend, as it will give you an invaluable opportunity to hone your expertise, try out a potential career path and get relevant workplace experience that is valued by many employers, boosting your CV.

Top 15 in the UK for quality of teaching for Computer Science and Information Systems Guardian League Tables 2025

Professional Placement year

This course offers an optional professional placement year. This allows you to spend a whole year with an employer, following successful completion of your second year, and is a great way to find out more about your chosen career. Some students even return to the same employers after completing their studies.

If you choose to pursue a placement year, you will need to find a suitable placement to complement your chosen area of study. You will be able to draw on the University’s extensive network of local, regional, and national employers, and the support of our Careers teams. If you are able to secure a placement, you can request to be transferred to the placement version of the course.

Please note that fees are payable during your placement year, equivalent to 20% of the total full-time course fee for that year.

Generative AI is having an unprecedented impact on businesses all across the world, and this course gives you the ability to design, create, evaluate and implement the systems of the future.

Professor Iain Rice

Why Choose Us?

Learn from industry experts - Our staff have a wide range of research and industrial experience. They are also actively involved in a range of professional associations such as the British Computer Society and the Higher Education Academy.

Strong industry links - With companies such as Oracle, Linux Professional Institute, Microsoft and Apple. This allows us to ensure that the course is up to date, relevant and respected by employers.

Student satisfaction - Top 20 in the UK for student satisfaction for Computer Science (Complete University Guide 2025).

Optional professional placement year - You will have the opportunity to undertake professional placement in between your second and final year of study.

Practice based - With emphasis on computer lab-based practical work and project delivery, this course will provide you with many opportunities to acquire both the technical and transferable skills desired by industry.

Greater Birmingham & Solihull Institute of Technology

Students across our Engineering and Computing courses automatically become Institute of Technology Learners and can take advantage of the facilities and opportunities provided by the Greater Birmingham and Solihull Institute of Technology (GBSIoT).

More about the Institute

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Open Day

Join us for our next Open Day where you'll be able to learn about this course in detail, chat to students,

explore our campus and tour accommodation.

Next Open Day: 21 November

an Open Day

Course in Depth

Year one

Year two

Professional Placement Year (optional)

Year three

In order to complete this course, you must successfully complete all the following CORE modules (totalling 120 credits).

Computer Systems 20 credits

Within the Computer Systems Module, you will gain knowledge and experience of computers and computer hardware.

This module presents a holistic view of how computer systems work and it also provides the underpinning knowledge required:

for the design of computer architecture

to show how software interacts with hardware

to apply electronics principles

to use number systems for computer technology

Mathematics for AI 20 credits

A foundation in mathematics is essential to understand AI models, their evaluation and limitations, especially when appraising new developments in the field. This module will cover the required algebra, statistics and matrix operations used by these models.

Data Structures and Algorithms 20 credits

Data structures and algorithms are essential in computer science, software engineering, and computer games and graphics programming. Data structures are structured representations of data; the design of a data structure determines how operations (such as reading to, writing from, modifying, or computing with the data) can be achieved. An algorithm is a set of instructions which can be followed in order to solve a computational problem.

Innovation Project 20 credits

Students will undertake a major project involving research and application of that research in the solution of systems-related problems.

Knowledge and understanding are acquired though a mixture of formal lectures, tutor-led seminars and practical activities, with other independent learning activities at all stages. Emphasis is placed on guided, self-directed and student-centred learning, aimed at increasing independence of approach, thought and process.

The module provides access to effective commercial development environments and ensures students have practical awareness of computer systems requirements. Students are required to meet strict deadlines, and to manage and plan their overall workload.

Knowledge is assessed by several methods, including seminars, coursework, viva, presentation, interactive automated assessment, formal examination, and project work. Assessment criteria are published both at a generic course level and to provide guidance for individual items of assessment. Anonymous marking systems are in place for all formal examinations.

Computer Programming 20 credits

This introductory computer programming module provides the underpinning knowledge and practice for computing students to design, build and test software components. The module will make use of practical sessions primarily to allow you to apply programming principles and constructs in order to creatively solve problems by means of developing small programs. Module content and assessment enables learners to acquire programming skills in a modern imperative language.

Introduction to Artificial Intelligence 20 credits

This module covers the basic principles of artificial intelligence systems, techniques and the types of problems that can be solved by such techniques. This module also evaluates the risks and benefits of AI adoptions in different domains. Students learn about the philosophy of AI and how knowledge is represented.

The module utilises a hands-on approach to teaching. Teaching sessions include experiential activities such as critique of example scenarios; these scenarios will include situations tailored to real world case studies.

Object Oriented Programming 20 credits

Programming is an engineering tool that plays a vital role to drive most of the modern technologies surrounding us, including the technological devices for communication, transportation and entertainment. In other words it can be said that our modern lifestyles are heavily dependent on programming.

Moreover, businesses increasingly rely on computers and the software run on them. Programming skills and a broader and deeper understanding of programming are therefore becoming increasingly important to the jobs market.

Backend Web-Services Development and Database Engineering 20 credits

During the module you will work to design, develop, use and evaluate a “backend service” system backed by a database. You will produce this system over the course of the semester through engaging with the coursework throughout various milestones, developing a “portfolio” of work as you go along.

The module will be taught using a combination of lectures and practical, interactive lab sessions for learning skills and gaining important feedback. Independent learning will also be supported by a range of materials and activities delivered using Moodle.

Artificial Intelligence and Machine Learning 20 credits

Artificial Intelligence (AI) is a core component of computer science, aiming at developing intelligent agents that mimic human’s cognitive capability in learning, reasoning, and problem solving.

As a branch of AI, machine learning (ML) allows to create software that adapts and learns (from examples), rather than being explicitly programmed for a particular outcome. Both AI and ML rely on managing, processing and analysis of large datasets, something that Data Science (DS) is concerned with. Many services provided by technology giants such as Google, Microsoft, IBM, Facebook, Amazon, etc. are powered by DS, ML and AI. The recent advances in these subjects have already led to significant industrial applications such as self-driving cars and Industry 4.0.

Data Management and Machine Learning Operations 20 credits

This module covers the rapidly growing area of Machine Learning Operations (MLOps) and its coupling with the management and governance of data.

Data management aims to minimise the risk and cost of storing and utilising data in an efficient manner that ensures regulatory compliance, while avoiding legal complications, and security breaches. It also entails the provision of efficient access to accurate data when and, where it is needed, to facilitate effective provision of data-powered services and data-driven decision making.

Machine Learning Operations (MLOps) is the Data Science equivalent to the term “DevOps” used in Software Engineering, namely it covers appropriate practices and strategies for organisations to successfully apply Machine Learning techniques in a structured, explainable, repeatable and, importantly, production-ready manner.

Computer Vision 20 credits

Natural Language Processing 20 credits

Natural Language Processing (NLP) is a rapidly developing field with broad applicability throughout the hard sciences, social sciences, and the humanities. The ability to harness, employ and analyse linguistic and textual data effectively is a highly desirable skill for academic work, in government, and throughout the private sector.

This module is intended as a theoretical and methodological introduction to the most widely used and effective current techniques, strategies, and toolkits for natural language processing.

The module will also consider how harnessing large digital corpora and large-scale textual data sources has changed how scholars engage with and evaluate digital archives and textual sources, and what opportunities textual repositories offer for computational approaches to the study of literature, history, and a variety of other fields, including law, healthcare, business, and the social sciences.

In order to qualify for the award of Bachelor of Science with Honours Artificial Intelligence with Professional Placement Year, you must successfully complete all of the modules listed as well as the following Level 5 module:

Professional Placement 120 credits

This module is designed to provide you with the opportunity to undertake a credit bearing, 40- week Professional Placement as an integral part of your Undergraduate Degree.

The purpose of the Professional Placement is to improve your employability skills which will, through the placement experience, allow you to evidence your professional skills, attitudes and behaviours at the point of entry to the postgraduate job market. Furthermore, by completing the Professional Placement, you will be able to develop and enhance your understanding of the professional work environment, relevant to your chosen field of study, and reflect critically on your own professional skills development within the workplace.

Deep Neural Networks and Ethics 20 credits

Deep learning (also called deep neural network) is a sub-field of Artificial Intelligence (AI), aiming at extracting knowledge automatically from large data sets in a hierarchical way.

Deep learning, which is considered as the state-of-the-art in data science and AI, is inspired by the structure of human brain. Now well established and accepted in industry, deep learning provides both predictive and descriptive analytics solutions that can be applied to a wide range of applications from business to scientific and governmental applications.

As artificial intelligence gets widely adopted, its societal implications correspondingly deepen and broaden. Therefore, this module teaches the ethical implications of using artificial intelligence and will invite a critical assessment of such implications in the assessed work.

Modern Datastores and Data Protection 20 credits

This module will introduce NoSQL databases and distributed data storage frameworks through practice based activities. Through guided hands-on tutorials, you will become familiar with techniques using non-structured and semi-structured data examples. Also, you will gain knowledge on managing and processing data in a distributed infrastructure. This module will improve your development skills and provide experience with many different data systems. Also, students will gain knowledge about protection of the data in NoSQL systems.

Generative AI 20 credits

Generative AI refers to a class of artificial intelligence that can produce original content — such as text, images, code, and audio — based on patterns it has learned from existing data. It is the technology behind tools like ChatGPT, Copilot, and others that are reshaping how we work, communicate, and create. This module offers a clear and practical introduction to generative AI. It explores how generative AI works, what it can realistically achieve, and where its limitations lie. Large Language Models, AI agents and common Generative projects will be covered.

Cloud Computing 20 credits

One of the major objectives of the computer science course is to introduce the theory, principles and technologies underlying the construction of modern computing systems. This module introduces Cloud Computing, which is the technology that enables on-demand computing resources (everything from applications to data centres) over the Internet.

This technology has revolutionised modern computing by allowing users to access infinite pool of computing services and resources on a pay-per-use basis. This module introduces the fundamental concepts and technologies related to cloud computing architecture, platforms and services. The module follows a practical approach to equip the students with hands-on experience of cloud computing by using a public Cloud service, such as Amazon Web Services.

Individual Honours Project 40 credits

The purpose of the module is to enable you to undertake a sustained, in-depth and research-informed project exploring an area that is of personal interest to you. In agreement with your supervisor, you will decide upon your topic which will take the form of a practical outcome (artefact) with accompanying contextual material. The main consideration when choosing your topic is that it must be aligned to the programme you are studying, and you should consider the relevance of this topic to your future academic or professional development.

At this level, you will be expected to work independently but you will receive additional one-to-one support from your supervisor, who will be familiar with your chosen topic area. As you progress on the module, extra support will be available and this may take the form of group seminars, workshops and online materials that will help to develop your project.

Knowledge and understanding are acquired though a mixture of formal lectures, tutor-led seminars and practical activities, with other independent learning activities at all stages.

Emphasis is placed on guided, self-directed and student-centred learning, aimed at giving you increasing independence of approach, thought and process.

The course provides access to effective commercial development environments and ensures you have practical awareness of computer systems requirements. You are required to meet strict deadlines, and to manage and plan your overall workload.

Knowledge is assessed by a number of methods, including seminars, coursework, viva, presentation, interactive automated assessment, formal examination and project work. Assessment criteria are published both at a generic course level and to provide guidance for individual items of assessment. Anonymous marking systems are in place for all formal examinations.

You will undertake a major project involving research and application of that research in the solution of systems-related problems.

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BSc Artificial Intelligence embodies the academic and industrial understanding that AI is a highly demanded specialisation of computer science, and therefore practitioners must have a strong and solid foundation in computer science.

Level Four

The first year equips you with a solid foundation in key topics in Computer Science and introduces artificial intelligence. Therefore, the first year shares five of its six modules with BSc (Hons) Computer Science & Artificial Intelligence and covers key concepts, such as computer programming, algorithms and data structures, computer systems, website development and introductory artificial intelligence as well as a dedicated mathematics module, and nurtures your creativity with an innovation project. Your practice is supported by presentations, seminar discussions of key topics and ideas, and collaborative practices with other students. After the first year, you will have covered a broad range of topics in AI that will upskill you to understand the key industrial skills and prepare you to take advanced topics in the subsequent years.

Level Five

The second year consolidates your learning applied AI modules covering machine learning, image analysis, natural language processing and machine learning operations. These modules are complemented by the introduction of object oriented programming and backend development. These topics are highly practical and underpin the roles of Software Developers, Computer Programmers and Machine Learning Engineers in industry.

Level Six

The final year covers the advanced topics in practice of artificial intelligence and covers the key application areas. These include Deep Learning and Generative AI, the technology behind the mass adoption of artificial intelligence in industry and its applications in computer vision and natural language processing. This year also teaches key enabling technology powering scalable computing in industry.

Your learning culminates into an Individual Honours Project where you display your learning by developing a well-rounded, professionally developed, artificial intelligence driven software solution for a problem of modern relevance.

The final year readies you for a graduate level job in the computing, artificial intelligence, and data science industry.

My placement with Jaguar Land Rover

Computer and Data Science student Lavanya Aggarwal has completed her placement with Jaguar Land Rover. Lavanya spoke to us about how the opportunity taught her skills and experiences that will be beneficial for her further studies and future employment.

Learn more about Lavanya's placement

Entry Requirements

These entry requirements apply for entry in 2027/28.

All required qualifications/grades must have been achieved and evidenced at the earliest opportunity after accepting an offer to help confirm admission and allow for on-time enrolment. This can also include other requirements, like a fee status form and relevant documents. Applicants can track their application and outstanding information requests through their BCU mySRS account.

Essential requirements

112-72 UCAS Tariff points

The offer we make you takes into account your individual circumstances, predicted grades, achieved qualifications and potential to succeed at university.

GCSE and other level 2 requirements

This course does not require evidence of GCSE qualifications. Please see A Level, BTEC and other Level 3 requirements below.

A Level, BTEC and other level 3 requirements

Qualification

Entry requirements

A Level: 112-72 UCAS Tariff points / BBC-CDE (or equivalent)

Must include one from Technology, Science, Mathematics or Computing at A Level or level 3 equivalent

AS Level: Must be in a different subject to A Levels

A maximum of four subjects will be considered

Pearson BTEC (Diploma / Extended Diploma/ Extended Certificate)

Accepted subjects: Technology, Science, Mathematics or Computing

Diploma accepted with one A Level or equivalent level 3 qualifications

Extended Certificate accepted with two A Levels or equivalent level 3 qualifications

Typical offers vary according to individual circumstances and may be equivalent to a Merit or Pass overall grade

Accepted subjects: Digital Production, Design and Development; Digital Support Services; Digital Business Services; Media, Broadcast and Production

Access to HE Diploma

Pass with 60 credits. At least 45 credits at level 3.

Accepted subjects: Technology, Science, Mathematics, or Computing

OCR Cambridge Technical qualifications

Accepted subjects: Technology, Science, or Computing

NCFE CACHE Level 3 qualifications

Considered alongside A Levels or equivalent level 3 qualifications, one of which must be Technology, Science, or Computing

WJEC Level 3 qualifications

Irish Leaving Certificate (Highers)

112-72 UCAS Tariff points, achieved in five Higher level subjects

Required subjects: Technology, Science, Mathematics or Computing at Higher Level

Scottish Higher / Advanced Higher

112-72 UCAS Tariff points, achieved from three Advanced Highers or two Advanced Highers plus two Highers

Required subjects: One from Technology, Science, Mathematics or Computing

Welsh Baccalaureate

112-72 UCAS Tariff points. Considered with two A Levels or equivalent level 3 qualifications

If you're applying with an International Baccalaureate Diploma or international qualifications, please see further information below.

Mature students

Applications from mature students (21+) with alternative qualifications and/or considerable work experience will be considered on their merits.

International qualifications

International Baccalaureate Diploma

Obtain a minimum of 28-24 points overall

Required subjects: One of Computer Science, Chemistry, Design Technology or Physics at Higher Level

EU / International students

Please see your country page for further details on the equivalent qualifications we accept. In addition to the academic entry requirements listed above, international and EU students will also require IELTS 6.0 overall with no less than 5.5 in each band.

If you do not meet the required IELTS score, you may be eligible for one of our pre-sessional English courses. Please note that you must have a Secure English Language Test (SELT) to study on the pre-sessional English course. More information on pre-sessional English courses.

If you have a qualification that is not listed, please contact us.

Fees & How to Apply

Please select your student status to view fees and apply

UK Student

International Student

UK students

Annual and modular tuition fees shown are applicable to the first year of study. The University reserves the right to increase fees for subsequent years of study in line with increases in inflation (capped at 5%) or to reflect changes in Government funding policies or changes agreed by Parliament. View fees for continuing students.

Award: BSc (Hons)

Starting: Sep 2027

Duration

£10,050 in 2027/28

Apply via UCAS

International students

£19,220 in 2027/28

Apply Online

Included in your course fees

Access to computer equipment

You will require use of a laptop, and most students do prefer to have their own. However, you can borrow a laptop from the university or use one of our shared computer rooms.

Printing

You will receive £5 print credit in each year of your course, available after enrolment.

Access to Microsoft Office 365

Every student at the University can download a free copy of Microsoft Office 365 to use whilst at university and for 18 months after graduation.

Key software

You will be able to download SPSS and Nvivo to your home computer to support with your studies and research.

Key subscriptions

Subscriptions to key journals and websites are available through our library.

Basic materials for testing

We will provide some basic threads/yarns/printing materials for initial testing and experimentation.

DBS check

If you are required to undertake a Disclosure and Barring Service (DBS) check for this course, the cost for your first DBS check is included in your fees.

Free student copy of Solidworks CAD Package

Students studying on this course will receive a free student copy of Solidworks CAD package.

Certification training (optional)

Training is provided by the University to prepare you for the Linux Professional Institute (LPI) and CISCO Certifications without any extra costs. Certification costs apply.

Not included in your course fees

Excess printing (optional)

Once you have spent your £5 credit, additional printing on campus costs from 5p per sheet.

Personal stationery and study materials (optional)

Based on the past experience of our students, you might find it helpful to set aside about £30 for each year of your studies for your personal stationery and study materials.

Placement expenses (optional)

If you choose to undertake a placement, you'll need to budget for accommodation and any travel costs you may incur whilst living or working away from home.

Accommodation and living costs (optional)

The cost of accommodation and other living costs are not included within your course fees. More information on the cost of accommodation can be found in our accommodation pages.

Guidance for UK students

UK students applying for most undergraduate degree courses in the UK will need to apply through UCAS.

The Universities and Colleges Admissions Service (UCAS) is a UK organisation responsible for managing applications to university and college.

Applying through UCAS

Register with UCAS

Login to UCAS and complete your details

Select your course and write a personal statement

Get a reference

Pay your application fee and submit your application

Guidance for International students

There are three ways to apply:

1) Direct to the University

You will need to complete our International Application Form and Equal Opportunities Form, and submit them together with scan copies of your original academic transcripts and certificates.

2) Through a country representative

Our in-country representatives can help you make your application and apply for a visa. They can also offer advice on travel, living in the UK and studying abroad.

3) Through UCAS

If you are applying for an undergraduate degree or a Higher National Diploma (HND), you can apply through the UK’s Universities and Colleges Admissions Service (UCAS).

You can request a printed form from your school or nearest British Council office. You will be charged for applying through UCAS.

Birmingham City University’s UCAS code is B25 BCITY.

Personal statement

The personal statement gives you a crucial opportunity to say why you’re applying and why the institution should accept you.

Here are the three areas you’ll need to address:

Why do you want to study this course or subject?

Here’s where you explain what makes this course exciting to you. Think about your motivations for studying the course and your future plans. If you’re planning to take a year out, don't forget to give your reasons.

How have your qualifications and studies helped you to prepare for this course or subject?

This is your chance to show what you’ve learned at school or college. You should include the skills and knowledge you’ve gained from education or training and how this will help you succeed in your chosen course.

What else have you done to prepare outside of education, and why are these experiences useful?

Not everything you’ve learned comes from the classroom. Life experience counts too! You might want to talk about work experience, employment, or volunteering and how they’ve helped you develop the skills needed for your chosen course or future career.

Worried about Personal Statements?

If you've got no idea where to start or just want to check you're on the right track, we’ve got expert advice and real examples from our students to help you nail your personal statement. You can even download our ultimate personal statement guide for free.

Get personal statement advice

Financial Support

We offer further information on possible undergraduate financial support. This includes the type of loans, grants and scholarships available both from the government and from Birmingham City University.

View fees for continuing students

Employability

Enhancing your employability skills

You will learn of range of skills which will be key to enhancing your future employability.

Specifically, you will learn to:

Develop software solutions to real world problems.

Use a range of modern techniques to engineer software products.

Understand the role, and techniques and application of artificial intelligence in the modern software systems and their societal impact.

Implement the deployment pipeline of artificial intelligence and machine learning based software system.

Work independently and collaboratively.

Be a self-motivated, organised, effective learner.

Communicate your work effectively via both oral and written communication skills.

Professional practice guidance will teach you a range of skills such as writing CVs and job applications, and preparing for interviews; the use of social media and other platforms for self-promotion, presenting yourself and your work in a professional framework using a range of appropriate communication skills, such various types of presentation software will also be practised.

Graduate Jobs

AI roles have changed titles and focus rapidly over the last decade, but this course teaches the most advanced methodologies which will create attractive graduates. Relevant roles include:

AI engineer

MLOps Specialist

Data Scientist

Machine Learning engineer

Data Analyst

Further study

You can progress onto a range of postgraduate studies, including (but not limited to) an MSc in disciplines concerning Computer Science, Artificial Intelligence, Data Science, Software Engineering, and Computer Games. You could also potentially go straight to doctoral research study.

MSc Big Data Analytics and MSc Artificial Intelligence are popular choices for applicants with background or interest in the above-mentioned disciplines.

Placements

You will have the opportunity to take a placement year between your second and third year. This is something that is highly recommended, as it will give you an invaluable opportunity to put your skills into practice, try out a potential career path and get relevant workplace experience that is valued by so many employers.

Industry links

While studying your Artificial Intelligence degree with us, you’ll also have access to dedicated industry-standard facilities in a fully equipped lab running the latest software. Plus, we’re home to a Cisco Systems and a Microsoft Academy Centre, so you can rest assured knowing our university course will prepare you for a successful career in the industry.

Innovation Fest

Innovation Fest is designed to foster entrepreneurship and support the development of our first-year students as future world-changers. The festival contributes to the knowledge economy, increasing students’ employability by providing genuine portfolio material.

Innovation Fest at BCU

Facilities & Staff

Computing facilities

Take a look around the facilities available to you as a Computing student at BCU.

See our Computing facilities

Our staff

Dr Hadeel Saadany

Lecturer in Data Science and Natural Language Processing (NLP)

Dr Hadeel Saadany is a lecturer in Data Science and Natural Language Processing (NLP). She conducts research in multidisciplinary fields focusing on the intersecting areas of NLP, Deep Learning and Artificial Intelligence (AI) in different domains. Her research projects are primarily focused on utilizing AI to solve real-life problems through...

More about Hadeel

Dr Abdul Rahman Alsewari

Associate Professor

Dr. AbdulRahman A. Alsewari received his Ph.D. in Software Engineering from Universiti Sains Malaysia (USM), Penang, Malaysia, in 2012. He earned his Master’s degree in Electronic System Design Engineering (MEng) in 2009 from USM and a Bachelor’s degree (BEng) in Computer Engineering in 2002 from Iraq. With over 14 years of research and teaching...

More about Abdul Rahman

Dr Ogerta Elezaj

Lecturer of Computing and Digital Technology

For the past six years, Ogerta Elezaj has been a Senior Lecturer in the University of Tirana, teaching different courses such as Big Data, Artificial Intelligence, and Data Mining. She was recipient of Alain Bensoussan postdoctoral fellowship from European Research Consortium for Informatics and Mathematics in 2019-2020 and held ERCIM postdoc...

More about Ogerta

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