Bachelor in Artificial Intelligence

Course No: 1501215

Course Title: Data Structures

Credit Hours: 3-0:3

Prerequisite: 1501211 Programming II

Catalog description: Basics of algorithm design. Linear Structures: Multidimensional arrays and their storage organization, Lists, Stacks and Queues and introduction to the C++ STL library. Introduction to recursion. Nonlinear structures: trees (binary trees, tree traversal algorithms) and Graphs (graph representation, graph algorithms). Elementary sorting and searching methods.

Course No: 1501220

Course Title: Python Programming

Credit Hours: 3-0:3

Prerequisite: 1501100 Introduction to IT

Catalog description: This course covers advanced features of the Python programming language, with an emphasis on programming practice. It aims to help learners understand the semantics of Python and the process of structuring data using collections such as lists, dictionaries, tuples, strings, and sets. Learners will be guided to develop important skills, including working with classes, data structures, and sorting algorithms, as well as implementing threads and exception handling. The course involves substantial Python programming practice through projects and assignments.

Course No: 1501263

Course Title: Introduction to Database Management Systems

Credit Hours: 3-0:3

Prerequisite: 1501215 Data Structures

Catalog Description: This course explores how databases are designed, implemented and used. The course emphasizes the basic concepts/terminology of the relational model and applications. The students will learn database design concepts, data models (Entity-Relationship and Relational Model), SQL, functional dependencies and normal forms. The students will gain experience working with a database management system.

Course No: 1501279

Course Title: Discrete Structures

Credit Hours: 3-0:3

Prerequisite: 1440131 - Calculus I OR 1440133 - Calculus I for Engineering

Catalog Description: This course emphasizes the representations of numbers, arithmetic modulo, radix representation of integers, change of radix. Negative and rational numbers. Sets, one-to-one correspondence, properties of union, intersection, and complement, countable and uncountable sets. Representing Relations, and Equivalence relations. Recurrence relations. Functions: Injective, surjective, and bijective functions. Mathematical Induction, proof by contradiction. Combinatorics and recurrence relations. Fundamentals of logic, truth tables, conjunction, disjunction, and negation, Boolean functions and disjunctive normal form. Numbers theory. Graphs Theory: Introduction, Paths and connectedness, Eulerian and Hamiltonian Graphs, Graph Isomorphisms. Trees.

Course No: 1501315

Course Title: Practical Data Science

Credit Hours: 3-0:3

Prerequisite: 1501220 Python Programming

Catalog Description: Data science is an interdisciplinary field that uses statistics, mathematics, programming, and domain knowledge to extract insights from data. This course introduces students to key concepts such as data collection and Wrangling, data cleaning and normalization, data visualization and exploration. Students will learn to use Python tool and will gain hands-on experience in working with real-world datasets to solve complex problems and make data-driven decisions.

Course No: 1501329

Course Title: AI Ethics and Responsible Artificial Intelligence

Credit Hours: 2-0:2

Prerequisite: 1501330 – Introduction to Artificial Intelligence

Catalog Description: This course provides an applied and critical introduction to ethical, legal, and societal issues in AI. Students study moral reasoning and professional responsibility; algorithmic bias and fairness; privacy and data protection; transparency and explainability; safety, robustness, and misuse risks (including generative AI); and organizational governance approaches for responsible AI. Using local and global case studies, students conduct audits and produce governance artefacts (e.g., responsible AI impact assessments, documentation, and policy briefs) aligned with major frameworks and relevant UAE/regional expectations.

Course No: 1501330

Course Title: Introduction to Artificial Intelligence

Credit Hours: 3-0:3

Prerequisite: 1411215 Data Structures/ 1501214 Programming with Data Structures + 1440131 Calculus I

Catalog Description: This course will provide an introduction to the fundamental concepts and techniques in the field of artificial intelligence. Topics covered in the course include basic search, heuristic search, game search, constraint satisfaction, knowledge representation, and machine learning algorithms, Robotics, and Natural Language Processing.

Course No: 1501331

Course Title: Introduction to Machine Learning

Credit Hours: 3-0:3

Prerequisite: 1501220-Python Programming

Catalog Description: This course offers a foundational and practical exploration of machine learning, covering essential models and techniques for building and evaluating predictive systems. Students begin with core concepts, including feature types, model selection, and the bias-variance tradeoff. Key models explored include classification (k-nearest neighbors, logistic regression, and Gaussian Naive Bayes), regression (linear and elastic net), support vector machines, decision trees, and ensemble methods. Advanced topics introduce neural networks, deep learning architectures, and clustering techniques for unsupervised learning. The course emphasizes hands-on applications, preparing students to effectively design, assess, and improve machine learning models for practical applications.

Course No: 1501352

Course Title: Operating Systems

Credit Hours: 3-0:3

Prerequisite: 1501215 Data Structures

Catalog Description: This course covers the fundamentals of operating systems, including system structures, processes and threads, CPU scheduling, synchronization, memory management, virtual memory, storage systems, and disk scheduling algorithms. Emphasis is placed on understanding system-level design, resource management, and performance evaluation of modern operating systems.

Course No: 1501364

Course Title: Big Data Analytics

Credit Hours: 3-0:3

Prerequisite: 1501263 Introduction to Database; 1440281 Introduction to Probability and Statistics

Catalog Description: This course introduces key concepts, technologies, and tools used in big data analytics. Topics include the data analytics lifecycle, clustering, classification, regression, association rules, time series, text analytics, MapReduce, Hadoop, in-database analytics, and data visualization. Students apply analytical techniques to real-world datasets and complete a team-based analytics project.

Course No: 1501366

Course Title: Software Engineering

Credit Hours: 3-0:3

Prerequisite: 1501215 Data Structures

Catalog Description: This course follows the formal software development lifecycle from requirements and specification through design, implementation, testing, and maintenance. Topics include software process models, project management, UML modeling, verification and validation, quality assurance, and software maintenance.

Course No: 1501371

Course Title: Design & Analysis of Algorithms

Credit Hours: 3-0:3

Prerequisite: 1501279 Discrete Structures; 1501215 Data Structures

Catalog Description: This course emphasizes fundamental concepts in algorithm design and analysis, including divide and conquer, greedy methods, dynamic programming, backtracking, and randomized algorithms. It covers sorting, searching, graph algorithms, maximum flow, string matching, and computational complexity including NP-completeness.

Course No: 1501387

Course Title: Practical Training I in AI

Credit Hours: 0-2:1

Prerequisite: Junior Standing

The course will be designed to equip students with an understanding of their target industries and the professional skills required to excel in them. It will focus on imparting practical technical skills that are in high demand, alongside project management and execution strategies using industry-standard methodologies. Furthermore, the course will emphasize the development of essential soft skills, such as communication and teamwork, while also preparing students for the job market with robust career readiness training, including resume writing, interview techniques, and networking.

Course No: 1501388

Course Title: Practical Training II in AI

Credit Hours: 0- :2

Prerequisite: 1501387 Practical Training I in AI

This course serves as a bridge between theoretical knowledge gained in introductory courses and its real-world application in professional settings. Through hands-on experiences and guided practice, students will develop essential skills and competencies necessary for success in the computing field. The students will engage in practical tasks and projects that simulate real-world computing scenarios. They will work individually and in teams to tackle challenges, develop solutions, and present their findings. Regular feedback sessions and self-reflection exercises will help students track their progress and identify areas for improvement.

By the end of the course, students will have gained valuable hands-on experience, enhanced their technical proficiency, and developed the professional skills necessary to thrive in diverse computing environments. This course prepares students to function effectively in the workforce, contributing to the advancement of computing solutions while adhering to ethical standards and industry best practices. The course consists of no less than 6 weeks of supervised practical training at an approved organization for a minimum of 40 hours per week. The course is expected to be completed during the summer session.

Course No: 1501398

Course Title: Junior Project in AI

Credit Hours: 3-0:3

Prerequisite: 1501215 Data Structures; 1501246 Object-Oriented Design

Catalog Description: This course represents the first phase of the AI senior project. Students form teams, conduct literature reviews, define project requirements, design system architecture, and develop an initial AI-based prototype. Emphasis is placed on documentation, ethical reporting, teamwork, and effective presentation.

Course No: 1501431

Course Title: Edge AI

Credit Hours: 3-0:3

Prerequisite: Object-Oriented Design with Java

Catalog Description: This course introduces the fundamentals of Edge Artificial Intelligence and deployment of AI models close to data sources. Topics include edge-cloud architectures, resource constraints, model trade-offs, security, privacy, safety, and system-level design considerations for real-world edge applications.

Course No: 1501435

Course Title: Natural Language Processing

Credit Hours: 3-0:3

Prerequisite: 1501331 Machine Learning

Catalog Description: This course introduces the fundamentals of Natural Language Processing (NLP) and focuses on how computers analyze, process, and represent human language. Topics include text preprocessing, tokenization, normalization, feature extraction, text representation (bag-of-words, n-grams, TF-IDF), basic text classification and sentiment analysis, model evaluation metrics, introductory neural NLP concepts, and ethical and social considerations in language technologies.

Course No: 1501446

Course Title: Introduction to Deep Learning

Credit Hours: 3-0:3

Prerequisite: 1501331 Introduction to Machine Learning

Catalog Description: This course provides a comprehensive introduction to foundational and advanced deep learning techniques. Topics include gradient descent and optimization (including Adam), neural networks and backpropagation, CNNs, RNNs, LSTMs, Autoencoders, GANs, Diffusion Models, Graph Neural Networks, Transformers, and selected applications such as NLP, recommender systems, and reinforcement learning. Emphasis is placed on implementation and practical AI applications.

Course No: 1501459

Course Title: Information Security

Credit Hours: 3-0:3

Prerequisite: 1501215 Data Structures or 1501214 Programming with Data Structures

Catalog Description: This course introduces concepts, methodologies, and techniques in information security. Topics include security threats and attacks, malicious software, web and network vulnerabilities, access control mechanisms, cryptography and encryption algorithms, digital signatures and certificates, public key infrastructure, and legal, ethical, and professional aspects of information security.

Course No: 1501498

Course Title: Senior Project in AI

Credit Hours: 3-0:3

Prerequisite: 1501398 Junior Project in AI

Catalog Description: This course builds on the Junior Project in AI and focuses on the design, integration, implementation, and evaluation of a substantial AI-based software system. Students work in teams to address a real-world problem, produce technical documentation, present and defend their solutions, and demonstrate professional, collaborative, and ethical practices in project development.

Course No: 1501335

Course Title: Agentic AI

Credit Hours: 3-0:3

Prerequisite: 1501330 Intro to AI

Catalog Description: This course introduces the principles and design of autonomous and agentic artificial intelligence systems. Students explore intelligent agents, decision-making frameworks, goal-directed behavior, planning, reasoning, and interaction strategies in dynamic environments. Emphasis is placed on designing, implementing, and evaluating agent-based systems for real-world applications.

Course No: 1501337

Course Title: Information Retrieval

Credit Hours: 3-0:3

Prerequisite: 1501330 Intro to AI

Catalog Description: This course introduces the fundamental concepts and techniques of information retrieval systems. Topics include text representation, indexing, ranking models, search evaluation, relevance feedback, web search technologies, and modern retrieval methods. Students gain practical experience in building and evaluating search and retrieval systems.

Course No: 1501341

Course Title: Web Programming

Credit Hours: 3-0:3

Prerequisite: 1501116 Programming I

Catalog Description: This course covers the fundamentals of web programming including client-side and server-side technologies. Topics include HTML, CSS, JavaScript, HTTP protocols, and dynamic web development. Students design and implement interactive and database-driven web applications.

Course No: 1501432

Course Title: Computational Intelligence

Credit Hours: 3-0:3

Prerequisite: 1501215 Data Structures

Catalog Description: This course introduces soft computing techniques including evolutionary algorithms, fuzzy systems, neural networks, and swarm intelligence. Students design and implement heuristic optimization methods and apply them to real-world artificial intelligence and optimization problems.

Course No: 1501434

Course Title: Reinforcement Learning

Credit Hours: 3-0:3

Prerequisite: 1501330 Intro to AI

Catalog Description: This course introduces reinforcement learning principles and algorithms for sequential decision-making. Topics include Markov Decision Processes, dynamic programming, Monte Carlo methods, temporal-difference learning, and Q-learning. Students implement and evaluate reinforcement learning solutions.

Course No: 1501436

Course Title: Knowledge Representation & Reasoning

Credit Hours: 3-0:3

Prerequisite: 1501279 Discrete Structures

Catalog Description: This course introduces symbolic knowledge representation and reasoning techniques including propositional and first-order logic, ontologies, semantic web technologies, and knowledge graphs. Students design and query knowledge bases for intelligent systems applications.

Course No: 1501437

Course Title: Robotics & Autonomous Systems

Credit Hours: 3-0:3

Prerequisite: 1501215 Data Structures

Catalog Description: This course introduces robotics fundamentals including kinematics, dynamics, sensing, perception, and control. Students study modeling and analysis of robotic systems and explore applications in autonomous systems.

Course No: 1501438

Course Title: AI for Immersive Metaverse

Credit Hours: 3-0:3

Prerequisite: 1501215 Data Structures

Catalog Description: This course explores artificial intelligence concepts and implementations for immersive virtual environments. Topics include finite state machines, behavior trees, pathfinding, agent communication, and reinforcement learning within metaverse applications.

Course No: 1501443

Course Title: Human–Computer Interaction

Credit Hours: 3-0:3

Prerequisite: 1501245 Multimedia Programming

Catalog Description: This course introduces principles of human–computer interaction, usability engineering, and interface design. Students design, prototype, and evaluate user-centered interfaces for interactive systems.

Course No: 1501444

Course Title: Game Design and Development

Credit Hours: 3-0:3

Prerequisite: 1501215 Data Structures

Catalog Description: This course covers principles of game design and development including gameplay mechanics, narrative design, game balancing, and AI integration. Students develop functional games using modern game engines.

Course No: 1501454

Course Title: Quantum Computing

Credit Hours: 3-0:3

Prerequisite: None

Catalog Description: This course introduces the foundations of quantum computing including quantum circuits, algorithms, and programming frameworks. Students explore applications in cryptography, optimization, and machine learning.

Course No: 1501458

Course Title: Mobile Applications & Design

Credit Hours: 3-0:3

Prerequisite: 1501215 Data Structures

Catalog Description: This course introduces mobile application architecture and development using modern SDKs. Students design and implement mobile applications with user interfaces and event-driven programming.

Course No: 1501465

Course Title: Development of Web Applications

Credit Hours: 3-0:3

Prerequisite: 1501341 Web Programming

Catalog Description: This course focuses on building web-based database applications using three-tier architecture. Students develop dynamic web applications integrating databases, server-side scripting, and security mechanisms.

Course No: 1501498

Course Title: Topics in AI I

Credit Hours: 3-0:3

Prerequisite: 1501330 Intro to AI

Catalog Description: This course explores advanced and emerging topics in artificial intelligence, emphasizing recent research developments, experimentation, and critical evaluation of AI systems.

Course No: 1501499

Course Title: Topics in AI II

Credit Hours: 3-0:3

Prerequisite: 1501330 Intro to AI

Catalog Description: This course continues the exploration of advanced AI topics with deeper focus on research trends, applications, evaluation, and independent study of emerging artificial intelligence technologies.