Download Brochure Apply Now
January 12, 2026
100% online
courses
Personalized pace
with regular
deadlines
Synchronous Interactive Live Sessions
$3,600*
(excluding the 3 preparatory courses)

The Program

Powered by Abdulla Al Ghurair Hub for Digital Teaching and Learning

The "Artificial Intelligence & Data Science" online Professional Graduate Diploma is the first of its kind in the MENA region, providing you with the skills needed to design and implement AI and DS applications. Unlike other online programs, this diploma uncovers AI and DS concepts in several contexts while focusing on regionally relevant applications and the integration of ethics as a core component. Students from all backgrounds interested in being part of this exciting field in tech can join this diploma.

This program offers the Ideal mix of theoretical knowledge with practice-oriented studies designed to fit tomorrow's job market and match your personal goals.

New to AI? No problem!

  • Students from all backgrounds interested in being part of this exciting field in tech can join this diploma. No prior experience in artificial intelligence is required
  • You are welcomed to take our 3 pre-foundation coursers which will equip you with the necessary tools to utilize during your learning journey within the program
  • Join a highly engaging and ever-evolving program that features interactive online sessions while gaining the support of our innovative learning tools, digital study material, tutorial videos, and student support through our TA's..

Unique Benefits Tailored to Your Needs!

Gain advanced knowledge in data science principles to prepare data for AI applications.
Attain comprehensive understanding of ethical issues related to AI applications.
Leverage the diverse expertise of our world-renowned professors.
Earn a career-centric degree blending theory and practical skills.

Who Is This Program For?

You are
  • Fresh graduates from all backgrounds interested in joining the fastest growing field in tech
  • Working professionals seeking to enhance their knowledge and skills in the fields of AI & DS
  • Applicants from any background interested in this exciting field
  • Applicants from a similar background seeking to advance their career
  • Start-ups or companies seeking to transform their business by upskilling their employees in this field
You have
  • An undergraduate bachelor's degree from a recognized institution of higher learning
  • The English Language Proficiency Requirement (ELPR).
  • Applicants with no prior background from a relevant field will be required to take up to 3 preparatory courses (1 credit each). The Faculty graduate studies committee will decide which preparatory courses are needed for each applicant
  • Applicants with relevant background are waived from the 3 preparatory courses (1 credit each), but the courses remain optional as a refresher

What Skills Will You Gain?

Advanced knowledge in data science principles to prepare data for AI applications
Up to date skills to train various machine learning models for AI applications
Expertise in building real-world regionally and internationally driven AI applications in various domains such as Arabic natural language processing, business, and health
Comprehensive understanding of ethical issues related to AI applications

Testimonials

Mariam Mando

I highly recommend the program to those who want to expand their knowledge in the field of data, especially fresh grads looking to kick off their careers.I would describe this program as an “Opportunity Creator.”

Mariam Mando | AI&DS '24

Data Coordinator at Monty Mobile

Marwa Salman

The program was structured properly, with courses starting from basics to more specific topics. We saw the benefits of AI in real-life scenarios and applied them in hands-on examples.

Marwa Salman | AI&DS '24

Data Engineer at APGAR

Nour Halwani

The program was thorough and well-structured, offering a deep dive into AI and Data Science, bridging theory and real-world applications to solve complex business challenges.

Nour Halwani | AI&DS '24

Executive Management at Laceco

Mariam Mando

I highly recommend the program to those who want to expand their knowledge in the field of data, especially fresh grads looking to kick off their careers. I would describe this program as an “Opportunity Creator.”

Mariam Mando | AI&DS '24

Data Coordinator at Monty Mobile

Marwa Salman

The program was structured properly, with courses starting from basics to more specific topics. We saw the benefits of AI in real-life scenarios and applied them in hands-on examples.

Marwa Salman | AI&DS '24

Data Engineer at APGAR

Nour Halwani

The program was thorough and well-structured, offering a deep dive into AI and Data Science, bridging theory and real-world applications to solve complex business challenges.

Nour Halwani | AI&DS '24

Executive Management at Laceco

Curriculum

Prerequisite courses

These prerequisites are for people coming from a non-relevant background.

A preparatory course that covers the fundamental constructs of the Python programming language and introduces some useful applications. The course assumes no background or experience with programming and aims to train students to write python code, which is necessary for them to develop AI applications using many currently popular Data Science and Machine Learning libraries.

This one-credit course is designed to train students and give them the mathematical background needed in problems emerging from Data Science and Machine Learning. It aims to fill in the gap between high school mathematics and the required mathematical pre-requisites. Students will be introduced to linear algebra and calculus topics which are fundamental to the methods used in the main ML and DS courses.

This course is designed to build a working background for those who want to follow a data science track. The course begins with the definition, interpretation and properties of probability, calculation of probability by methods of enumeration, conditional probability and independent events; univariate and bivariate distributions corresponding to both discrete and continuous random variables; covariance and correlation between random variables, independent random samples and the central limit theorem; basics of point estimation, interval estimation and hypothesis testing.

Core courses

This course covers the mathematical underpinnings of machine learning and the practical know-how needed to effectively train, test, and deploy machine-learning models to real-world problems.

This introductory course explores the output expected of data scientists and equips students with the ability to learn from data to gain predictions and insights. Through real-world examples of wide interest, several facets of the data science pipeline and lifecycle using both the R and Python programming languages will be introduced.

This course provides an overview of deep learning methods and their related applications. It focuses on applied deep learning and includes lab assignments, practical use cases, as well as a project that explores the applications in deep learning.

This course critically examines the various ethical issues related to AI such as safety and security, privacy, transparency, accountability, bias and fairness, and reviews the technical methods to identify and address these issues.

Elective courses

This course focuses on Arabic natural language processing (NLP) and covers its foundational concepts such as tokenization, part-of-speech tagging, syntactic parsing, word sense disambiguation, and semantic representations. It also uncovers NLP’s applications including information retrieval, machine translation, sentiment and emotion analysis, dialogue systems, and question answering.

This course provides students with an introduction to the diverse applications of artificial intelligence (AI) in healthcare research while addressing its limitations and ethical implications. Students will learn about different data representations and sources, and how machine-learning techniques can be used to address various health problems. The course also touches upon AI interpretability and important ethical considerations.

This course explores the foundations, architectures, and applications of Large Language Models (LLMs), focusing on Transformers, self-supervised learning, and fine-tuning techniques. Students will gain hands-on experience developing generative AI applications, including prompt engineering, retrieval-augmented generation, and deployment strategies. Ethical considerations, and real-world case studies will be integrated to ensure a practical understanding of LLMs

It is now a critical strategic advantage for companies to use data effectively to drive rapid, precise and profitable decisions. More specifically, customers today expect to receive outcomes delivered to them based on their preferences; hence, companies must leverage the available wealth of customer data and take customers farther along their journey.
This course explores the growing important role of data in business and covers the key concepts of customer analytics with quantitative strategies to answer different business questions. The aim is to demystify the role of data and AI in impacting customer behavior. Students will learn about AI-powered applications that can enhance the customer journey. The course utilizes relevant theory, empirical analysis, and practical examples to develop the key learning points. By the end of this course, students will have the ability to envision how data, AI and Machine Learning can be used to enhance the business.

This course aims to expand on previously acquired principles in machine learning and data science to work through applications that demonstrate social impact and data-driven decision-making in the field of public policy. Using publicly available datasets and a mix of tools covering exploratory analysis, predictive analytics, spatial analytics, and NLP, this course will walk students through real-life, practical examples that demonstrate the effectiveness of those techniques in the public realm.

Flexible Tuition Fees

Select the payment method that suits you best!
Pay for the courses you register each term.
Base price per credit: $300
Pay in full and benefit from a 10% reduction on tuition fees.
Total program tuition: $3,600
Or $4,500 for learners that need to take the prerequisite courses
Corporate tuition rates are available, contact us for more information.
Contact us

Choose Your Ideal Study Plan!

9 months | full-time study plan
Ideal for ambitious individuals with a strong determination to complete their studies, recommended for those who have no other commitments, allowing them to focus wholeheartedly on their educational goals.
1 year+ | part-time study plan
Created for working individuals, this part-time study plan provides the balance needed between pursuing your studies and managing your professional commitments, by completing all the pre-requisites required and by taking only one course per semester.
Next Start Date

January 12, 2026

Join our upcoming cohort of AI specialists!
Deadline to apply is January 7, 2026 Hurry!

Applicants from non-relevant backgrounds can take prerequisite courses at their own pace throughout the year. For Fall 25-26 semester, prerequisites must be completed 2 weeks before the semester begins.

Need more information?
Want to learn more about this program? Interested in a personalized 1-on-1 session with our enrollment coaches? Schedule a session today!

Instructors

Fatima Abu Salem

PhD in Computing
Expert in Applied Artificial Intelligence and applied data science for impact

Abbas Alhakim

Postdoctoral researcher at KU Leuven Belgium
Expert in Building Physics and Sustainable design for human well-being

Rida Assaf

PhD in Computer Science
Expert in Artificial Intelligence and Bioinformatics

Mariette Awad

PhD in ECE
Expert in Artificial Intelligence and Machine Learning

Karim Barakat

PhD in Philosophy
Expert in Social and Political Philosophy, Foucault, Hobbes

Hans D. Muller

Professor of Ecosystem Management, Department of Landscape Design
Expert on Food System Resilience and Sustainability

Khalil El Asmar

PhD in Clinical Research
Expert in Statistical Applications in Psychiatry

Shady Elbassuoni

PhD in Computer Science
Expert in Machine Learning

Sabine El Khoury

Associate Professor, Department of Chemical Engineering and Advanced Energy
Sustainability champion leveraging diverse industrial, startup, and consulting experience to drive innovative solutions for a greener future

Mireille Makary

PhD in Information Retrieval Expert in Information Retrieval, NLP, Machine Learning and Generative AI

Sophie Moufawad

PhD in Applied Mathematics
Expert in Research Interests: Numerical Analysis, Applied Linear Algebra, Inverse Problems, Parallel Programming, High Performance Computing, Partial Differential Equations.

Saeed Raheel

PhD in Information and Communication Sciences
Expert in Programming Languages and Software Development

Mazen Saghir

PhD in Electrical and Computer Engineering
Expert in Computer Architecture, Reconfigurable Computing, Embedded Systems, and Embedded Machine Learning (TinyML)

Sirine Taleb

PhD in Computer and Communications Engineering, Machine Learning
Expert in Machine Learning, Data Analysis, Business Analytics

Fatima Abu Salem

PhD in Computing
Expert in Applied Artificial Intelligence and applied data science for impact

Abbas Alhakim

Postdoctoral researcher at KU Leuven Belgium
Expert in Building Physics and Sustainable design for human well-being

Rida Assaf

PhD in Computer Science
Expert in Artificial Intelligence and Bioinformatics

Mariette Awad

PhD in ECE
Expert in Artificial Intelligence and Machine Learning

Karim Barakat

PhD in Philosophy
Expert in Social and Political Philosophy, Foucault, Hobbes

Hans D. Muller

Professor of Ecosystem Management, Department of Landscape Design
Expert on Food System Resilience and Sustainability

Khalil El Asmar

PhD in Clinical Research
Expert in Statistical Applications in Psychiatry

Shady Elbassuoni

PhD in Computer Science
Expert in Machine Learning

Sabine El Khoury

Associate Professor, Department of Chemical Engineering and Advanced Energy
Sustainability champion leveraging diverse industrial, startup, and consulting experience to drive innovative solutions for a greener future

Mireille Makary

PhD in Information Retrieval Expert in Information Retrieval, NLP, Machine Learning and Generative AI

Sophie Moufawad

PhD in Applied Mathematics
Expert in Research Interests: Numerical Analysis, Applied Linear Algebra, Inverse Problems, Parallel Programming, High Performance Computing, Partial Differential Equations.

Saeed Raheel

PhD in Information and Communication Sciences
Expert in Programming Languages and Software Development

Mazen Saghir

PhD in Electrical and Computer Engineering
Expert in Computer Architecture, Reconfigurable Computing, Embedded Systems, and Embedded Machine Learning (TinyML)

Sirine Taleb

PhD in Computer and Communications Engineering, Machine Learning
Expert in Machine Learning, Data Analysis, Business Analytics

Frequently Asked Questions

Applicants to this diploma may provide evidence for RUSE by submitting a satisfactory and valid score for one of the following tests: AUB-EN, TOEFL iBT, IELTS (Academic), or Duolingo.

All graduate applicants are required to demonstrate RUSE. Master’s, MD, or PhD applicants who have graduated from AUB or from a recognized college or university in US/UK/Canada/Australia/New Zealand are exempted from demonstrating RUSE.

Test Minimum Score Validity
AUB-EN 32 1 year
TOEFL iBT 80 2 years
IELTS (Academic) 6.5 2 years
Duolingo 120 2 years

The courses consist of pre-recorded lectures that you can access at your convenience. Although the lectures are selfpaced, you will still need to follow regular deadlines. Each course includes one online live interactive session per week, providing you with the opportunity to interact with both your instructors and fellow students. All live sessions are recorded in case you cannot attend. You also have the chance to go on an optional site visit to gain hands-on learning from real world projects.

Class profiles vary from one cohort to the next, but, generally, our online certificates draw a highly diverse audience in terms of professional experience, industry, and geography — leading to a very rich peer learning and networking experience.

To enroll in the AI & DS online diploma, a bachelor’s degree is required, as it is a postgraduate diploma program. If you do not have a bachelor’s degree, you can take the courses à la carte and you will obtain a certificate of completion for each completed course.

Upon program completion, you will receive a professional diploma certificate issued by the Maroun Semaan Faculty of Engineering and Architecture (MSFEA) and signed by the Faculty Dean and MSFEA Online Director.

The committee decides whether an applicant needs to take any of the foundational courses. Applicants who come from relevant majors such as computer science, computer engineering, or other engineering majors are usually waived from the foundational courses, except if they graduated a while ago and need to take the prerequisites as refreshers. Applicants from other majors will most likely need to take prerequisite courses. In all cases, applicants are advised to apply as early as possible.

  • No. Prerequisites must be completed 2 weeks before the core courses begin.
  • All prerequisite courses are now fully self-paced and available to take at any time throughout the year.
  • Each prerequisite course is a 1 credit course that usually requires 4 weeks to complete, however, since it is self-paced you can complete it at your own time and pace prior to the start of the core courses.
  • Prerequisite courses will not have weekly live sessions or engagement with instructors, students will only have access to the Teaching Assistants for Q&A purposes.
  • Students will be given access to the core courses only if they successfully complete and pass the assigned prerequisites (passing grade is 70 or a C+).

The minimum passing grade for the courses within this diploma is 70 (C+).

Online Payment Icon
Pay Online
In this case, you will receive a payment gateway link.
Cash Payment Icon
Pay by cash at the AUB cashier’s office
In this case, we will issue an invoice for you to provide at the cashier’s office at College Hall.

Notes

  • Payments can only be made in USD.
  • Corporate tuition rates are available. Schedule a call for more information.

The minimum passing grade for the courses within this diploma is 70 (C+).

Refunds are allowed only within seven days of the course’s start date. This allows you to get a feel of the course content and assess if this program is a good fit for you.

Currently, there are no financial aid or scholarship offers for online programs. Alternatively, you can benefit from the early bird seat by paying the full tuition fee before the start of the program to receive a 10% deduction.

Upon program completion, you will receive a professional diploma issued by the Maroun Semaan Faculty of Engineering and Architecture (MSFEA), signed by the Dean of MSFEA and the Director of the Abdulla al Ghurair Hub for Digital Teaching and Learning.

Upon successful completion of the program, you will receive a digital copy of your diploma. It can be shared with friends, family, schools, or potential employers. You can use it on your cover letter, resume, and/or display it on your LinkedIn profile. The digital copy will be sent approximately two weeks after the program end date, once grading is complete. Should you request a hard copy of the diploma, this will take around one additional week to be issued and can either be shipped to you or picked up at AUB.

The diploma does not state “online“. All our programs are offered by AUB faculty members in collaboration with industry experts and offer quality education while utilizing advanced tools and technology to facilitate online learning.

No, the diploma does not have an expiry date.

Your access will remain to the online learning platform and course content for 12 months following the program’s end date.

  • Our professional diplomas focus on upskilling you in areas that are in high demand in the job market and equipping you with practical skills and knowledge.
  • These programs also have an academic bearing, meaning you may be able to waive up to six credits should you wish to enroll in a relevant master’s degree at AUB.

Contact Us

WhatsApp
+961 70 013 766
contact us email
[email protected]
contact us consultation
Schedule a consultation
WhatsApp
+961 70 013 766
contact us email
[email protected]
contact us consultation
Schedule a consultation

You might also be interested in

Project Management

Graduate Professional Diploma

Sustainability in the Built Environment

Graduate Professional Diploma

Cybersecurity

Graduate Professional Diploma

Entrepreneurship & Innovation

Graduate Professional Diploma