University of Sharjah

What you'll study

The MSc Artificial Intelligence combines advanced coursework with a substantial research or project component. Core topics typically include advanced machine learning, deep learning, statistical pattern recognition, and research methods. Electives allow specialisation in areas such as computer vision, natural language processing, reinforcement learning, robotics and multi-agent systems, big data analytics, and AI ethics and governance.

• Core modules (examples): Advanced Machine Learning; Deep Learning; Statistical Methods for AI; Research Methodology and Scientific Writing.
• Elective modules (examples): Computer Vision and Image Analysis; Natural Language Processing; Reinforcement Learning; Big Data Systems; Intelligent Robotics; Optimization and Heuristic Search.
• Project / Thesis: Students choose between a research thesis, supervised by faculty, or an industry-oriented final project. The thesis pathway emphasises original research and is suitable for those considering PhD study; the project pathway focuses on applying AI methods to real-world problems.
• Practical work: Laboratory sessions, programming assignments in Python and relevant libraries (TensorFlow, PyTorch, scikit-learn), and team-based project work are integral to the programme.
• Duration and credits: The programme is designed to be completed over one to two years of full-time study, depending on the chosen track and the student’s prior background, comprising a mix of taught credits and a research/project component.

Entry requirements

Applicants are normally expected to hold a recognised bachelor’s degree in computer science, electrical engineering, information technology, mathematics, statistics or a closely related discipline. A good academic record at undergraduate level is required. Applicants with strong professional experience in software development, data science or related fields but from a different academic background may be considered on a case-by-case basis.

• Transcripts demonstrating satisfactory undergraduate performance (specific GPA requirements follow university policy).
• A statement of purpose describing academic and professional objectives and any relevant project or research experience.
• Two academic or professional references indicating the applicant’s readiness for graduate study.
• Evidence of English language proficiency if the applicant’s prior degree was not in English (accepted tests and minimum scores are set by the university).
• Relevant CV/resume and, where applicable, sample project work or publications.

Career prospects

Graduates of the MSc Artificial Intelligence are well placed for a broad range of technical and research roles. The programme equips students to design, implement and evaluate AI systems across sectors.

• Machine Learning / AI Engineer: building and deploying models for classification, prediction and recommendation systems.
• Data Scientist / Data Analyst: extracting insights from large datasets, feature engineering and model validation.
• Computer Vision or NLP Engineer: developing applications such as image analysis, autonomous systems, or language understanding.
• Robotics and Autonomous Systems Specialist: integrating perception, planning and control for intelligent machines.
• R&D and PhD pathways: students who follow the thesis route may continue to doctoral study or research roles in industry labs and universities.
• AI Consultant / Technical Lead: advising organisations on AI strategy, deployment and governance.

Why study at University of Sharjah

The University of Sharjah offers an environment that combines regional relevance with international standards of teaching and research. The university has dedicated engineering and computer science faculties with staff active in AI-related research, and facilities that support hands-on laboratory work and access to computing resources. Its location in the UAE provides proximity to a rapidly growing technology and innovation ecosystem, enabling networking and collaboration opportunities with industry partners and government initiatives in AI.

Students benefit from supervised research, opportunities to engage in applied projects with local organisations, and a culturally diverse campus community. The programme’s balance of theoretical foundations, practical implementation and research preparation makes it suitable for graduates aiming to advance their technical careers or continue to doctoral study.