Bachelor's Degree
Bachelor of Artificial Intelligence – Undergraduate Degree Program
The Bachelor of Artificial Intelligence at the College of International Justice (CI Justice) is an advanced academic and applied undergraduate degree programme designed to address the massive technological revolution of artificial intelligence and machine lear...
Duration4 years
Credit hours148
DegreeBachelor
Language of studyArabic
Terms8
About the program
The Bachelor of Artificial Intelligence at the College of International Justice (CI Justice) is an advanced academic and applied undergraduate degree programme designed to address the massive technological revolution of artificial intelligence and machine learning, and its profound transformations across business, law, security, and governmental services. The programme integrates solid mathematical and algorithmic foundations (probability, linear algebra, and advanced search algorithms) with advanced practical applications in machine learning, deep learning, natural language processing (NLP), computer vision, generative AI models, and a vital focus on artificial intelligence ethics, governance, and regulatory and legal dimensions.Spanning eight academic semesters (four academic years – 240 ECTS), the curriculum guides students progressively from discrete mathematics, systems programming in Python, and basic algorithms to specialized studies in artificial neural networks, computational text processing for Arabic and other languages, autonomous robotics and intelligent systems, algorithmic governance, and AI deployment in justice and business sectors. Furthermore, the programme bridges theoretical study with smart laboratory applications and live intelligent systems simulation.
Vision
To achieve global leadership and academic excellence in preparing AI scientists and engineers equipped with technical innovation, ethical responsibility, and legal awareness to lead responsible intelligent transformation across diverse sectors and societies.
Mission
To deliver cutting-edge undergraduate education in artificial intelligence sciences and applications aligned with European and British academic standards—combining mathematical and algorithmic foundations with applied innovation and ethical frameworks—to qualify graduates capable of designing and building smart systems that serve humanity efficiently and reliably.
Objectives
- Solid Mathematical and Algorithmic Foundation: Equip students with a comprehensive knowledge base in mathematics, probability, statistics, and advanced computer algorithms.
- Mastery of Machine Learning and Deep Learning Techniques: Enable scholars to build, train, and evaluate machine learning models and deep neural networks to solve complex problems.
- Specialization in Natural Language Processing and Computer Vision: Provide students with advanced skills in text analysis (including Arabic text processing) and digital image and video processing.
- Comprehension of AI Ethics and Governance: Familiarize students with regulatory, ethical, and legal frameworks governing the development and deployment of intelligent systems (algorithmic transparency and fairness).
- Deployment of Generative AI and Autonomous Systems: Train students to design applications powered by Large Language Models (LLMs) and autonomous systems.
- Development of Applied Research and Entrepreneurial Skills: Build graduates' capacities to innovate AI-driven solutions and conduct advanced applied research.
Educational philosophy
In delivering the Bachelor of Artificial Intelligence, the College of International Justice adopts the philosophy of "Algorithmically-Rigorous & Responsibly-Governed AI." This philosophy recognizes that a modern AI engineer must not only master coding and mathematics, but also fully comprehend the legal, ethical, and societal implications of their systems.Accordingly, the programme rests on four philosophical pillars:Integration of Mathematical Depth and Applied Impact: Linking pure mathematical theories with practical applications in programming and model engineering.Practical Learning in Data & AI Labs: Relying on model building and training projects using supercomputers and real datasets.Focus on Technology Governance and Ethics: Embedding algorithmic governance and AI regulation courses directly into the core curriculum.Flexible Interactive Learning Environment: Delivering multimedia educational content via the smart College platform with close supervision from a dedicated Personal Tutor for each module.
Learning outcomes
- Comprehend mathematical, statistical, and algorithmic foundations underlying AI and machine learning models.
- Exhibit comprehensive awareness of deep neural network architectures, large language models, and optical processing techniques.
- Understand ethical, legislative, and governance frameworks regulating the use and development of AI systems.
- Recognize operational mechanisms of big data analytics and cloud computing infrastructures.
- Critically analyze AI model performance and identify algorithmic bias and error issues.
- Objectively evaluate technical solutions and select appropriate algorithms to solve complex problems.
- Foresight rapid evolutions in the AI sector and evaluate their impact on organizations and society.
- Build, train, and fine-tune machine learning and deep learning models using programming languages (Python/R).
- Develop Natural Language Processing (NLP) applications, computer vision systems, and smart recommendation engines.
- Deploy generative AI tools and platform APIs in process automation and organizational problem-solving.
- Apply governance and transparency standards in designing algorithmic systems.
- Communicate complex technical findings effectively to present and analyze intricate AI results to technical and non-technical audiences.
- Demonstrate collaborative leadership within intelligent systems development teams and manage software projects.
- Utilize version control tools and cloud computing environments (Google Cloud / AWS AI) with high proficiency.
Career prospects
- Major Tech Companies & Research Centers: Machine Learning Engineer, Deep Learning Engineer, or AI Researcher.
- Data & Language Processing Sector: Natural Language Processing (NLP) Engineer or Big Data Engineering Specialist.
- Computer Vision & Autonomous Systems Sector: Computer Vision Engineer or Intelligent Robotics Systems Developer.
- Governmental & Legislative Sector: AI Governance and Algorithmic Policy Advisor or Technical Compliance Specialist.
- Startups & Digital Transformation: Generative AI Product Developer or Smart Digital Solutions Consultant.
Curriculum
Introduction to Information Technology and Computer Science 3 credit hours · AI101Fundamental Programming (Python / Java) 3 credit hours · AI102Discrete Mathematics for Computing 3 credit hours · AI103Operating Systems (Linux & Windows) 3 credit hours · AI104Computer Networking Fundamentals 3 credit hours · AI105Technical English Terminology I 3 credit hours · AI106
Data Structures and Algorithms 3 credit hours · AI201Advanced Computer Networks and Communications 3 credit hours · AI202Relational Database Design and Development 3 credit hours · AI203Object-Oriented Programming (OOP) 3 credit hours · AI204Systems Analysis and Design 3 credit hours · AI205Technical Writing in English II 3 credit hours · AI206
Software Engineering 3 credit hours · AI301Web Programming and Development (Frontend) 3 credit hours · AI302Advanced and Non-Relational Databases (NoSQL) 3 credit hours · AI303Scripting and Systems Administration (Bash / Python) 3 credit hours · AI304Human-Computer Interaction (UI/UX) 3 credit hours · AI305Information Technology Networks and Systems Security 3 credit hours · AI306
Backend Web Development 3 credit hours · AI401Mobile Application Development 3 credit hours · AI402Advanced Operating Systems and Systems Engineering 3 credit hours · AI403Software Testing and Quality Assurance (QA & Testing) 3 credit hours · AI404IT Project Management 3 credit hours · AI405Advanced Data Structures and Algorithm Design 3 credit hours · AI406
Cloud Computing Fundamentals 3 credit hours · AI501Distributed Systems Engineering and Large-Scale Web Applications 3 credit hours · AI502Microservices Architecture 3 credit hours · AI503Advanced Web Content Management Systems 3 credit hours · AI504Data Analysis and Visualization 3 credit hours · AI505Secure Coding and Application Security 3 credit hours · AI506
DevOps Engineering 3 credit hours · AI601Big Data Engineering 3 credit hours · AI602Enterprise Artificial Intelligence and Machine Learning Systems 3 credit hours · AI603Cloud Computing and Infrastructure Security 3 credit hours · AI604API Design and Security 3 credit hours · AI605IT Service Management (ITIL) 3 credit hours · AI606
IT Governance and Compliance 3 credit hours · AI701Internet of Things and Embedded Systems (IoT) 3 credit hours · AI702Advanced Software Architecture 3 credit hours · AI703Robotic Process Automation (RPA) 3 credit hours · AI704Business Continuity and Technical Disaster Recovery 3 credit hours · AI705Technical Innovation Management and Digital Entrepreneurship 3 credit hours · AI706
Applied Workshop on Technology Seminar and Modern Practices 3 credit hours · AI801Professional Field Training in Information Technology 3 credit hours · AI802Advanced Technologies Engineering and Edge Computing 3 credit hours · AI803Advanced Seminar in Information Technology 3 credit hours · AI804Tech Solutions Clinic and Digital Transformation Consultancy 3 credit hours · AI805Technical Graduation Project in Information Technology 3 credit hours · AI806
Frequently asked questions
How are teaching and learning delivered?
Through the CI Justice Educational Environment, combining synchronous interactive lectures, virtual cloud AI laboratories equipped with GPUs, and flexible asynchronous study, supported by weekly study planners, multimedia materials, and lifetime access.
How does the Personal Tutor and Academic Supervision System work?
Each student is assigned a specialized Personal Tutor for every module who monitors algorithmic and programming progress, evaluates training projects and models, and conducts individual or small-group tutorials via dedicated Online Tutoring Rooms.
How are students assessed and evaluated?
Through Computer-Marked Assignments (CMAs), Tutor-Marked Assignments (TMAs) such as neural network training and NLP applications, and End-of-Module Examinations predominantly conducted remotely via secure proctoring systems and practical development labs.
How do students gain practical experience during their studies?
Through engagement in Professional Field Training in Artificial Intelligence, model building within the Innovation Lab, and intelligent solutions consultancy clinics.
Accreditation, Licensing & Credit Transfer
Accreditation & Licensing: Fully accredited, sharing institutional and academic accreditations with International Suleiman University, officially licensed by the UK Government under provider reference (UKPRN / ID: 10093951), and monitored by the Quality Control Office.Credit Transfer: Operates a Transfer of Accreditation system recognizing academic credits completed at other universities, alongside evaluating and accrediting recognized professional AI and cloud certifications (such as Google Cloud AI, AWS Certified Machine Learning, Microsoft Azure AI) toward graduation requirements under College regulations.
What distinguishes the Artificial Intelligence programme at the College of International Justice?
The programme expertly blends solid mathematical and algorithmic foundations (linear algebra, optimization) with modern practical applications (Large Language Models GenAI, computer vision, and algorithmic governance), with a unique focus on AI applications within the justice and legal sectors.
What is the standard duration of the programme, and can it be accelerated?
The standard duration is 4 years (8 semesters – 144 credits / 240 ECTS). High-achieving students may accelerate their study timeline based on their Cumulative GPA.
Does this programme qualify me to work as a deep learning engineer or AI developer?
Yes, the programme equips graduates with all necessary mathematical, programming, and engineering skills required to work as machine learning engineers, deep learning engineers, or generative AI model developers in major corporations.
Does the programme require an advanced mathematical or programming background upon enrollment?
No prior advanced specialization is required. The programme begins by systematically building the student's foundation in Python programming, mathematics, and statistics from the first semesters before progressing to advanced specialized modules.
How are tuition fees calculated, and are scholarships available?
Tuition fees are calculated transparently per registered credit hour each semester, supported by flexible installment plans and partial merit-based scholarships.
Admission requirements
- Academic Qualification: Hold a recognized High School Diploma (Science or Technology track) or an equivalent qualification from an accredited educational institution.
- Transfer of Accreditation (Credit Transfer & RPL): The College allows students transferring from other universities, or holders of accredited professional certificates in computer science and AI, to apply for credit transfer and exemption following evaluation.
- Mathematical and Language Proficiency: Demonstrate proficiency in the language of instruction, a strong foundational mathematical background, and commitment to completing specialized technical English terminology modules.
- Documents and Technical Requirements: Certified copy of the High School Diploma and official academic transcript. Copy of a valid passport or national identity card. Recent formal passport-sized photograph and Curriculum Vitae (for credit transfer/RPL applicants). Reliable internet connection and computer with appropriate specs (GPU preferred) to access learning environments and computing labs.
Tuition & fees
Application fee$145.00
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