Bachelor’s Degree in Cybersecurity

This general education course focuses on enhancing fundamental Arabic language skills—reading, writing, speaking, and listening—for nursing students. The course emphasizes correct grammar, sentence structure, functional writing, and professional communication skills necessary for academic success and clear medical documentation in Saudi healthcare settings.

Type

University Requirement

When

Year one, First semester

Prerequisite

None

This general education course introduces nursing students to the foundational knowledge of the Holy Qur'an and its related sciences (Ulum al-Qur'an). The course focuses on the revelation, compilation, preservation, and main themes of the Qur'an, along with fundamental rules of recitation (Tajweed) and thematic interpretation (Tafsir). Special emphasis is given to health-related Qur'anic concepts, ethical values, human preservation, spiritual care, and therapeutic communication in clinical nursing practice.

Type

University Requirement

When

Year one, First semester

Prerequisite

None

This course provides students with an integrated foundation in the major concepts and components of Information Technology (IT) and establishes the technological background required for subsequent courses in the program. It begins with the concept and role of IT in organizations and society and introduces fundamental computer hardware components, including the CPU, memory, storage devices, and input/output devices, together with basic factors affecting computer-system performance. The course examines software categories, Operating Systems, and the interaction between hardware and software. Students are also introduced to fundamental principles of digital data representation, file types, data storage, and information processing. An introductory overview of Computer Networks and the Internet explains basic communication concepts, data exchange, and common network services. Fundamental concepts of Databases and Information Systems are presented to illustrate how data can be organized, stored, retrieved, and used to support organizational activities. The course also provides a broad overview of contemporary technologies, including Cloud Computing, Mobile Computing, the Internet of Things (IoT), and AI. These areas are introduced to establish technological awareness without duplicating the detailed treatment provided in later specialized courses. Fundamental Cybersecurity concepts are introduced, including account and data protection, privacy, and responsible and safe use of Internet resources and digital services. Upon completion, students should be able to identify the principal components of IT systems, explain their basic functions, distinguish among major categories of digital technologies, and understand the relationships among hardware, software, data, networks, and digital services.

Type

Major Requirement

When

Year one, First semester

Prerequisite

None

This course introduces students to the fundamental principles of programming and develops their ability to analyze problems, formulate algorithmic solutions, and implement those solutions using a modern programming language. It begins with the concept of an algorithm, the program -development process, problem analysis, identification of inputs and outputs, and representation of solutions using flowcharts and pseudocode. The course covers basic program structure, variables, constants, data types, type conversion, arithmetic, logical and relational operators, and input/output operations. Control structures are introduced, including selection statements and iterative structures, and students learn to combine these constructs to solve progressively more complex problems. Functions are introduced as a mechanism for decomposing programs into smaller and more manageable units. Topics include function definition and invocation, parameter passing, return values, and basic modularity. The course also covers one-dimensional arrays, strings, common operations associated with them, input validation, and introductory error handling. Considerable emphasis is placed on producing correct, structured, readable, and testable programs. Students learn to use meaningful identifiers, appropriate code formatting, and consistent programming practices. They also practice tracing program execution and identifying and correcting syntax, runtime, and logical errors. By the end of the course, students should be able to analyze simple and moderately complex programming problems, design appropriate algorithms, implement working solutions, test program output, and systematically identify and correct common errors. The course provides the programming foundation required for Programming (2), Data Structures, and later specialized programming courses in Artificial Intelligence.

Type

Major Requirement

When

Year one, First semester

Prerequisite

None

Unlocks

Programming (2)

This practical course transforms the theoretical concepts introduced in Programming (1) into hands-on programming skills through structured laboratory exercises and small programming projects. Students begin by becoming familiar with an Integrated Development Environment (IDE) and learn how to create projects and source files, write and save code, execute programs, and interpret development and error messages. Students practice using variables, constants, data types, operators, and input/output operations and translate mathematical and logical problems into executable programs. Selection statements and loops are then implemented to create programs involving decision making and repetitive processing. Laboratory activities include defining and calling functions, passing parameters, processing return values, and decomposing solutions into organized functional components. Students also practice working with arrays and strings and perform fundamental operations on collections of values and textual information. Particular emphasis is placed on debugging. Students learn to interpret error messages, trace program execution step by step, use breakpoints and available debugger facilities, and distinguish among syntax, runtime, and logical errors. Exercises progress from short programs focusing on individual concepts to problems requiring the integration of several programming constructs. Toward the end of the course, students complete a simple program or mini-project integrating the principal skills developed during the semester. Upon completion, students should be able to use a programming development environment effectively, independently write, execute, and test basic programs, systematically diagnose and correct common errors, and organize source code according to sound introductory programming practices.

Type

Major Requirement

When

Year one, First semester

Prerequisite

None

Unlocks

Programming (2) - Lap

Introduction to Cybersecurity maps the field by asking which digital assets need protection and who is affected when their confidentiality, integrity, or availability fails. Students distinguish threats, vulnerabilities, risks, and controls through examples such as phishing, malware, exposed passwords, and excessive permissions. Authentication, updates, backups, and awareness are examined as complementary safeguards rather than a guarantee of complete safety. Short cases ask students to define a simple system boundary, identify relevant people and data, and justify an initial protective action. Legal and ethical responsibilities and the limits of authorized testing are introduced. Cryptographic algorithms, network and web security, and digital forensics remain with their later specialist courses. Students compare an incident caused by human error with one caused by a technical weakness and identify where settings, training, or monitoring could help. Protecting a personal device differs from protecting a shared service because exposure and interruption affect more people. Multifactor authentication and least privilege are introduced with their purposes and limits.

Type

Major Requirement

When

Year one, First semester

Prerequisite

None

Unlocks

Data security

This course develops the language competencies students need to understand and use English in engineering, information technology, and computing contexts. It emphasizes the acquisition of fundamental technical vocabulary related to computers, software, networks, data, and digital systems and trains students to understand and use this terminology accurately in academic and professional situations. The course develops technical reading skills through textbooks, simplified technical articles, user manuals, and hardware and software documentation. Students practice identifying main ideas, understanding supporting details, interpreting terminology from context, and following technical instructions, procedures, and specifications. In writing, students learn to construct clear technical sentences and paragraphs and prepare descriptions, instructions, summaries, and basic professional correspondence. They practice describing devices, systems, and technical processes using accurate terminology and clear organizational structures. The course also develops listening and speaking skills through technology-related materials and discussions. Students learn to explain technical information orally, participate in academic and professional conversations, collaborate in group activities, and deliver short presentations on topics related to their fields of study. Upon completion, students should be able to read and understand technical texts appropriate to their academic level, recognize and correctly use essential terminology in computing and information technology, produce basic technical and professional written texts, and communicate technical information orally with greater accuracy and confidence. The course supports students in working effectively with English-language textbooks, documentation, and other resources used throughout their subsequent specialized courses.

Type

College Requirement

When

Year one, First semester

Prerequisite

None

This course introduces nursing students to the fundamentals of scientific research methods and evidence-based practice (EBP) in healthcare. Students will learn how to formulate research questions, conduct literature searches, select appropriate quantitative and qualitative research designs, design data collection tools, follow ethical guidelines, and draft a practical nursing research proposal relevant

Type

University Requirement

When

Year one, Second semester

Prerequisite

None

This course provides first-year nursing students with foundational academic and general English language skills. The course focuses on improving the four core language domains: reading, writing, listening, and speaking. Emphasis is placed on expanding vocabulary, mastering essential grammar rules, reading basic academic and health-related texts, and writing clear paragraphs required for academic success in nursing education.

Type

University Requirement

When

Year one, Second semester

Prerequisite

None

Unlocks

English Language (2)

This course provides students with the mathematical and logical foundations used in Computer Science and Artificial Intelligence and develops their ability to reason abstractly, construct arguments, and solve problems systematically. It begins with mathematical logic, including propositions, logical connectives, truth tables, logical equivalence, and inference, followed by predicates, quantifiers, and precise mathematical statements. The course covers set theory, set operations, Cartesian products, relations and their properties, equivalence and ordering relations, and functions and their principal characteristics. Students are introduced to major mathematical proof techniques, including direct proof, proof by contradiction, contrapositive reasoning, and mathematical induction. Fundamental counting principles are studied, including the rules of sum and product, permutations, combinations, and introductory inclusion-exclusion principles. Recurrence relations are introduced as mechanisms for representing recursively defined processes and computational patterns. The course also introduces fundamental graph theory, including vertices, edges, paths, connectivity, and trees, together with selected applications in computing and structured problem representation. Emphasis is placed on establishing the mathematical reasoning required for later computing and AI courses. Probability and statistical inference are deliberately excluded from detailed treatment because they are addressed in the dedicated Probability and Statistics for Data Science course later in the program. Upon completion, students should be able to use mathematical notation and logical reasoning correctly, construct basic proofs, solve problems involving sets, relations, counting, and graphs, and explain the relevance of discrete mathematical structures to algorithms, data structures, and Artificial Intelligence.

Type

Major Requirement

When

Year one, Second semester

Prerequisite

None

This course builds upon Programming (1) and moves students from basic procedural programming toward more structured software development using Object-Oriented Programming (OOP). Following a brief review of fundamental programming concepts, the course introduces classes and objects, attributes and methods, constructors, object creation, and interaction among objects. Students examine encapsulation and access control and learn how these mechanisms protect object state and organize responsibilities within software. Inheritance and code reuse are introduced, followed by polymorphism, abstraction, and interfaces, with emphasis on their contribution to extensible and maintainable software. Structured error handling using exceptions is introduced, together with techniques for detecting and responding to abnormal program conditions. The course covers file handling for reading, writing, and storing information and introduces fundamental collection structures for managing groups of objects more flexibly than conventional arrays. The course emphasizes object-oriented design, decomposition of a problem into cooperating classes with clear responsibilities, reduction of code duplication, and improvement of software reusability. Introductory testing, debugging, and refactoring practices are incorporated into the development process. The course deliberately focuses on general programming principles rather than AI or Data Science libraries, which are addressed in later specialized courses. Upon completion, students should be able to design and implement medium-scale object-oriented applications, define appropriate relationships among classes, apply encapsulation, inheritance, abstraction, and polymorphism, work with exceptions, files, and collections, and produce modular, understandable, reusable, and maintainable software.

Type

Major Requirement

When

Year one, Second semester

Prerequisite

Programming (1)

Unlocks

Data Structure

This practical course enables students to apply the object-oriented concepts introduced in Programming (2) through progressively structured programming exercises and projects. Students begin by creating classes containing attributes, methods, and constructors and then practice creating and manipulating objects and integrating multiple classes within a single application. Laboratory activities include access control and encapsulation, appropriate inheritance structures, method overriding, and practical use of polymorphism, interfaces, and abstraction. Emphasis is placed on demonstrating how these mechanisms reduce code duplication and improve software extensibility and maintainability. Students use exceptions to handle expected runtime problems in a structured manner and work with files to store and retrieve application data. Fundamental collection classes are used to manage variable numbers of objects and perform operations such as addition, removal, searching, and traversal. Testing and debugging form an important component of the course. Students use breakpoints, inspect object states during execution, identify logical and runtime errors, and apply introductory refactoring to improve existing solutions and reduce unnecessary dependencies among classes. During the final part of the course, students complete a medium-scale mini-project integrating multiple classes, collections or file processing, and exception handling. The project emphasizes sound software organization rather than implementation of AI algorithms. Upon completion, students should be able to translate an object-oriented design into working software, systematically test and debug their implementation, and organize a multi-class programming project according to sound development practices, providing the programming foundation required for Data Structures and specialized AI programming courses.

Type

Major Requirement

When

Year one, Second semester

Prerequisite

Programming (1) - Lap

Unlocks

Data Structure - Lap

This course provides students with the fundamental concepts and skills required to design and construct clear, well-structured, standards-based web interfaces. It begins with an introductory overview of the World Wide Web, web pages, browsers, and web servers and then focuses on HTML as the principal language for defining the semantic structure of web pages. Students learn to organize headings, paragraphs, lists, links, tables, images, and other page elements. The course introduces CSS for controlling visual presentation, including typography, colors, spacing, borders, backgrounds, selectors, and the application of styles to interface components. Fundamental techniques for organizing page layouts and structuring web content are also introduced. Responsive Web Design receives significant attention. Students learn to design pages that adapt to different screen dimensions and devices and examine basic principles of visual design, consistency, readability, content organization, and navigation. Web forms are introduced as mechanisms for collecting user input, including common input types and basic principles for organizing data-entry interfaces. The course also introduces usability and web accessibility, emphasizing semantic HTML and the need to design interfaces that can be effectively used by diverse users. The course remains focused on fundamental front-end design and does not extend into server-side programming, databases, or AI application development. By the end of the course, students should be able to analyze the requirements of a simple website, design its structure, create interconnected and semantically organized pages, apply responsive styling, and incorporate fundamental usability and accessibility principles.

Type

Major Requirement

When

Year one, Second semester

Prerequisite

None

Unlocks

Web Programming

This practical course enables students to apply web-design principles through the construction of actual web pages and small websites using HTML and CSS. Students begin by learning to use a code editor, organize project files, create valid HTML documents, and correctly link pages and resources such as images and style sheets. Laboratory exercises cover headings, paragraphs, lists, tables, hyperlinks, images, multimedia, and forms for user input. Students use CSS to control typography, colors, spacing, borders, backgrounds, and other visual properties and practice applying styles using different selectors. The laboratory provides practical experience in page layout and component organization, including common menus, navigation bars, and other interface structures. Students create responsive interfaces that adapt to different screen sizes and use browser developer tools to simulate different devices and diagnose display problems. Students test pages across different browsers where feasible, verify hyperlinks and file paths, and improve project organization and maintainability. Accessibility principles are incorporated through semantic structure, appropriate alternative text for images, and clearly organized forms. During the final part of the course, students develop a small multi-page website integrating the techniques covered throughout the semester. Upon completion, students should be able to transform an initial interface concept into a functional website, organize project resources effectively, test the interface under different viewport conditions, and ensure that the resulting pages are structured, usable, responsive, and accessible.

Type

Major Requirement

When

Year one, Second semester

Prerequisite

None

Unlocks

Web Programming - Lap

Principles of Communications examines how information is carried between endpoints through signals, frequency, time, amplitude, bandwidth, and noise. Students distinguish analog and digital signals and receive introductory treatment of sampling, coding, and modulation. Attenuation, interference, and limited channel capacity are linked to communication quality. Wired and wireless media, transmitter and receiver functions, and basic measures of data rate, error, and delay are studied through simple calculations and signal diagrams. Students connect the physical channel to later computer networks without confusing transmission properties with network protocols. The course provides a basis for communications and network security while leaving protocol attacks and cryptography to specialist study. Short exercises show how frequency and bandwidth affect a channel choice and how additional noise can raise error probability without necessarily stopping communication. Students compare a cable and wireless medium under basic physical constraints and interpret simple measurements instead of memorizing definitions alone.

Type

Major Requirement

When

Year one, Second semester

Prerequisite

None

This course builds upon English Language (1) by introducing first-year nursing students to specialized medical terminology, clinical communication, and health-related academic writing. The course focuses on medical prefixes, roots, and suffixes, taking patient histories, reading clinical case studies, documenting basic nursing notes, and communicating professionally with patients and multidisciplinary healthcare teams.

Type

University Requirement

When

Year two, First semester

Prerequisite

English Language (1)

This course establishes the probability and statistical foundations required for subsequent study in Data Analysis, Machine Learning, and Data Mining. It focuses on mathematical and statistical reasoning rather than introducing Machine Learning algorithms prematurely. The course begins with fundamental probability concepts, including sample spaces, events, probability rules, conditional probability, independence, and Bayes’ theorem. Students then study discrete and continuous random variables and major probability distributions, including Bernoulli, Binomial, Poisson, and Normal distributions. Expected value, variance, standard deviation, and covariance are introduced as key measures for describing random variables and relationships among variables. The statistics component covers descriptive statistics, including measures of central tendency and dispersion, percentiles, and quartiles. Sampling concepts, sampling distributions, the Central Limit Theorem, and the general concept of statistical estimation are also presented. Students are introduced to confidence intervals and hypothesis testing, including null and alternative hypotheses, significance levels, p-values, Type I and Type II errors. Correlation and introductory linear regression are presented from a statistical perspective without extending into Machine Learning model training. The course emphasizes interpretation of statistical results and understanding underlying assumptions rather than mechanical use of formulas. Upon completion, students should be able to apply fundamental probability principles, summarize and interpret data statistically, use basic sampling and estimation methods, perform introductory hypothesis tests, and understand the probabilistic and statistical foundations required for later data-analysis and predictive-modeling courses

Type

Major Requirement

When

Year two, First semester

Prerequisite

None

Unlocks

Numerical Analysis

This course provides students with a systematic understanding of fundamental data structures and their relationship to algorithm and software efficiency. Building on Programming (2), the course begins with a review of arrays and references and then examines how data can be organized in memory and how suitable data structures can be selected for different problems. Topics include linked lists, stacks, queues, and priority queues, together with fundamental operations such as insertion, deletion, searching, and traversal. Trees, binary trees, binary search trees, and common traversal methods are also studied. The course covers hash tables, hash functions, collision-resolution techniques, graphs, and common graph representations. Students also study selected searching and sorting algorithms and compare them in terms of time and space complexity. Big-O notation is introduced to describe algorithmic growth as input size increases. Students are encouraged to evaluate efficiency rather than focusing solely on functional correctness. The course provides an important foundation for the later AI Algorithms course. Accordingly, it focuses on general-purpose data structures and algorithm analysis rather than AI-specific search and heuristic techniques. Upon completion, students should be able to design and implement fundamental data structures, analyze their efficiency, select appropriate structures for specific computational problems, and justify their choices based on performance and memory requirements

Type

Major Requirement

When

Year two, First semester

Prerequisite

Programming (2)

This practical course enables students to implement and evaluate the data structures introduced in the theoretical course using an appropriate programming language. Students begin with arrays and references and progress to linked lists and operations such as insertion, deletion, searching, and traversal. Stacks and queues are implemented using alternative representations so that students can compare their practical characteristics. Laboratory work also includes binary trees, binary search trees, traversal algorithms, and tree insertion, deletion, and search operations. Students implement hash tables, hash functions, and collision-handling techniques and represent graphs using adjacency matrices and adjacency lists. General graph-traversal algorithms are also implemented. Searching and sorting algorithms are programmed and compared using data sets of different sizes. Students measure execution behavior and relate practical results to theoretical Big-O analysis. Debugging tools are used to identify implementation errors involving references and dynamically organized structures. The course culminates in a mini-project requiring the use of multiple data structures. Students justify their design choices and evaluate performance. Upon completion, they should be able to implement, test, compare, and select data structures effectively for different computational problems

Type

Major Requirement

When

Year two, First semester

Prerequisite

Programming (2) - Lap

This course introduces students to the fundamental concepts of relational database design, management, and use and establishes a strong foundation for later work in Data Science and Artificial Intelligence. It begins with the concepts of data, databases, and Database Management Systems and compares database systems with traditional file-based approaches. Students learn the principal stages of database design and use the Entity-Relationship Model to represent entities, attributes, relationships, cardinalities, keys, and constraints. They then learn how to transform conceptual models into relational schemas composed of related tables. The course covers the relational model, primary and foreign keys, referential integrity, and SQL for creating tables, defining constraints, inserting, updating, deleting, and retrieving data. Query topics include filtering, aggregate functions, grouping, sorting, subqueries, and joins. Functional dependencies and normalization are introduced to reduce redundancy and prevent insertion, update, and deletion anomalies. Fundamental normal forms are studied at an appropriate undergraduate level. The course also provides an introduction to transactions, concurrency, database security, backup, and recovery. Upon completion, students should be able to analyze information requirements, design an appropriate entity-relationship model, transform it into a relational database, write SQL statements to manage and retrieve data, and apply normalization and integrity principles to produce reliable and maintainable database structures.

Type

Major Requirement

When

Year two, First semester

Prerequisite

None

This practical course trains students to design, implement, and manage relational databases using an appropriate Database Management System. Students begin by creating databases and tables and defining data types, primary and foreign keys, and constraints, directly applying concepts from the theoretical Databases course. Students use SQL to perform insert, update, delete, and select operations and then progress to more advanced queries involving filtering, sorting, aggregate functions, grouping, subqueries, and joins. Laboratory activities include designing an entity-relationship diagram for a practical problem, transforming it into a relational schema, and applying normalization principles. Students examine redundancy and dependencies and implement referential-integrity constraints. Introductory exercises involving views, transactions, user privileges, backup, and restoration are included where supported by the selected database platform. The course emphasizes organized database scripts, consistent naming conventions, and systematic testing of data and queries. During the final part of the course, students complete a database project beginning with requirements analysis and conceptual modeling and continuing through table creation, relationship definition, data population, and meaningful queries and reports. Upon completion, students should be able to develop a reliable practical database that can serve as a data source for later Data Analysis and AI applications.

Type

Major Requirement

When

Year two, First semester

Prerequisite

None

Data Security follows information through collection, classification, storage, transmission, sharing, retention, and deletion. Students assign sensitivity levels and authorized access, then connect risks to least privilege, separation of duties, authentication, backups, and records of important actions. Integrity and availability under mistakes or outages, and use of test data without exposing real people, are considered. Encryption and hashing are introduced as tools with different purposes and limits; their algorithms are studied in the following course. For a service holding user accounts, students map data flows, identify where disclosure or unauthorized alteration could occur, and propose a control and a way to check it. The emphasis is protection policy and design decisions, not system penetration testing. A lost device with local records is compared with a file sent to the wrong recipient; each requires a different response. Students identify whom to notify, what copies may remain, and how to restore service or prevent further sharing. Indefinite retention is assessed for the harm it could cause even before any current incident occurs.

Type

Major Requirement

When

Year two, First semester

Prerequisite

Introduction to cyber security

Unlocks

encryption algorithms

This course broadens students’ understanding of the role of Information Technology in organizations and society, with emphasis on practical applications of digital systems and services. It examines Information Systems and the relationship among people, processes, data, and technology and considers how information supports organizational operations and decision making. The course surveys applications of databases, networks, Internet services, cloud services, and mobile technologies in business, education, healthcare, and government. Digital Transformation is introduced as the use of technology to redesign processes, services, and user experiences. Electronic services, e-commerce, remote collaboration, content management, and digital communication are also examined. Data privacy, information security, and responsible practices for collecting and using information are discussed. The course considers broader social and ethical implications of technology, including the digital divide, automation, and the impact of AI and digital technologies on employment and society, without addressing internal AI algorithms. Upon completion, students should be able to explain the organizational role of IT, analyze examples of Digital Transformation, identify benefits and risks associated with different technologies, and understand the relationships among technology, processes, users, and data

Type

University Requirement

When

Year two, Second semester

Prerequisite

None

This general education course introduces students to the history, geography, culture, and social fabric of Palestine. The course covers the historical development of the Palestinian issue from the late Ottoman period to contemporary times, examining key geopolitical milestones, cultural heritage, international law frameworks, and societal resilience. Special emphasis is placed on the health sector's history, social determinants of health in Palestine, and the ethical role of healthcare professionals in serving local communities.

Type

University Requirement

When

Year two, Second semester

Prerequisite

None

Cryptographic Algorithms studies the mathematical and algorithmic basis of protection after Data Security establishes its purpose. Messages, keys, probability, and the distinction between public algorithms and secret keys lead to classical ciphers as examples of weak designs. Students examine symmetric encryption and block-cipher structures and modes conceptually, then asymmetric encryption, key exchange, hash functions, and digital signatures by function and assumptions. They compare computational cost, key sizes, and limitations and trace small examples to check correctness without inventing production protection. Randomness generation and key handling are recognized as critical to security. The focus is why algorithms work and what they guarantee; protocols, certificates, and advanced attacks receive fuller treatment in the later Cryptography course. In limited teaching examples, students calculate an algorithmic step and explain why correct computation alone does not establish resistance to attack. Reversible encryption is distinguished from hashing for verification, and a signature proving origin from a mechanism concealing content. Comparing alternatives requires stating the key type, who holds it, and what must remain protected.

Type

Major Requirement

When

Year two, Second semester

Prerequisite

Data security

Numerical Analysis develops approximate solutions when a direct algebraic answer is impractical, drawing on prior mathematics and statistics. Computer representation of real numbers introduces rounding and accumulated error. Root finding through bisection and Newton's method, linear systems, interpolation and approximation, and introductory numerical integration provide the main techniques. Students compare convergence, stability, and computational cost and recognize results made unreliable by unsuitable inputs or assumptions. Exercises implement a small method, check it against known cases, and observe changes in precision or stopping criteria. The course supports later computation in data processing and simulation without confusing a numerical approximation with a security guarantee. Two methods solve the same equation from different starting values, prompting an explanation of why one converges and the other stalls. Students specify a stopping rule based on tolerable error and a reasonable iteration limit and check that a result is not an artifact of unstable rounding. Tables or plots show the convergence path rather than decorate a report.

Type

Major Requirement

When

Year two, Second semester

Prerequisite

Probability and Statistics for Data Science

Web Programming moves from static pages to services that handle HTTP requests and dynamic responses. Routes, forms, JSON APIs, database operations, sessions, authentication, and authorization form the core. Server-side validation, error handling, and introductory data protection are included. The emphasis is service logic rather than repeating CSS design. Students translate a small service specification into a route table listing method, required input, expected output, and failures. An authenticated user who tries to alter another person's record illustrates authorization as a separate question. Trust boundaries between browser, server, and database are identified, and a validation rule is framed for a manually constructed request. Students distinguish a useful visitor-facing error from information that belongs in a developer log. Handling and storage of credentials are reviewed to reduce exposure without undertaking advanced security protocol design.

Type

Major Requirement

When

Year two, Second semester

Prerequisite

Website Design

Unlocks

web security

Students build a small web service with routes to create, retrieve, update, and delete records. Forms connect to a database, while invalid input and different permission levels are tested. Run instructions and checks of both results and errors are documented; sensitive data are kept out of logs. Assessment focuses on request and data flow rather than visual decoration. Two students exchange a short specification: one implements routes while the other drafts verification cases from the same text. An update is checked with invalid values, a deleted record, and an unauthorized user. Finally, another account or device attempts to run the project, exposing hidden dependence on undocumented files or settings. The report states what was actually verified and what limits use beyond the teaching environment. Steps for reproducing an unresolved defect are recorded precisely enough for another person to investigate.

Type

Major Requirement

When

Year two, Second semester

Prerequisite

Website Design - Lap

This course introduces the fundamental principles of operating systems and their role in managing computer resources and application execution. It begins with operating-system structure and its relationship to hardware and applications and then examines processes, threads, their states, creation, and management. Students study CPU scheduling and common scheduling algorithms and compare them using appropriate performance criteria. Synchronization, critical sections, shared resources, and inter-process communication are introduced together with deadlock conditions and fundamental approaches for handling deadlocks. The course covers memory management, including paging, virtual memory, and page replacement, together with file systems, secondary storage, and input/output management. Protection, user privileges, and fundamental operating-system security concepts are also addressed. The course remains focused on general operating-system principles and does not extend into Cloud Computing or distributed-system topics that are addressed elsewhere in the curriculum. AI-related applications may be used as examples to illustrate the effects of CPU, memory, and process management without changing the scope of the course. Upon completion, students should be able to explain how operating systems manage processors, memory, files, and devices, analyze fundamental scheduling and synchronization problems, and understand how resource-management decisions influence the performance of computational applications

Type

Major Requirement

When

Year two, Second semester

Prerequisite

None

This course introduces nursing students to principles of occupational health and safety within hospital and clinical environments. The course covers workplace hazard identification, infection prevention, ergonomics, chemical and radiation safety, needle-stick injury prevention, emergency preparedness, and the psychological well-being of healthcare workers, aligned with Saudi Ministry of Health regulations and Saudi Central Board for Accreditation of Healthcare Institutions (CBAHI) safety standards.

Type

University Requirement

When

Year three, First semester

Prerequisite

None

This general education course introduces nursing students to the fundamentals of human rights, patient rights, and professional healthcare ethics. The course examines international human rights instruments, Saudi national legislation, patient rights charters, bioethics, informed consent, and non-discrimination. Students will explore the relationship between human rights principles and nursing care, focusing on protecting patient dignity, confidentiality, and vulnerable populations in clinical practice.

Type

University Requirement

When

Year three, First semester

Prerequisite

None

Cryptography extends the earlier Cryptographic Algorithms course from individual primitives to secure use in protocols. Students review symmetric encryption, modes, confidentiality, and integrity, then study key exchange, public-key encryption, digital signatures, certificates, and public-key infrastructure. Authenticated encryption is distinguished from confidentiality alone, and a secure connection is traced to explain how the peer's identity is checked. Randomness, key storage and rotation, reused nonces, and failure to validate certificates show why a sound algorithm can still be deployed insecurely. Students analyze a simplified protocol against its goals, assumptions, and threat model, identifying what each step guarantees and what it does not. The aim is to select established mechanisms and explain their limits, not to invent a production cipher. For a sensitive document exchange, students choose how to provide confidentiality, source verification, and integrity and explain the keys and information each participant needs. Losing a key is compared with having it disclosed, since recovery, revocation, and notification differ.

Type

Major Requirement

When

Year three, First semester

Prerequisite

None

The Cryptography Laboratory applies the companion theory through controlled exercises with established libraries and teaching tools. Students generate test keys, perform authenticated encryption and decryption, compute hashes, and verify signatures; changing a message, key, or nonce reveals how verification responds. A key exchange and a certificate-based test connection illustrate why an invalid certificate or mismatched identity must be rejected. Each exercise records inputs, assumptions, and results without putting real secrets into code or reports. Deliberately misconfigured cases in an isolated environment require students to locate and repair the error. A program running successfully is not treated as evidence that its use of cryptography is secure. A short report contrasts the expected outcome with the observed one and explains a verification failure after inputs change. Students review library API use and error handling without placing plaintext secrets or keys in application logs.

Type

Major Requirement

When

Year three, First semester

Prerequisite

None

Web Security examines the trust boundaries among browser, server, and database after Web Programming. Sessions, authentication, authorization, input validation, and output handling frame examples of injection, cross-site scripting, request forgery, and exposure through misconfiguration. Students trace a request in an account-based service to locate where an access check belongs and connect each flaw to a prevention measure and a repeatable test. Cookie settings, protected connections, and useful logs are considered without exposing passwords or tokens. Exercises use an authorized training environment and focus on defensive review. Students demonstrate a fix and check that the intended function still works, rather than stopping at identification of a vulnerability. Another case examines an account requesting another user's record although the interface does not show a link. Students explain why hiding a control is no substitute for server-side authorization and add tests for both a direct unauthorized request and a legitimate one.

Type

Major Requirement

When

Year three, First semester

Prerequisite

Web Programming

This course provides students with a structured understanding of computer-network principles and how data is transmitted among devices and systems across local networks, wide-area networks, and the Internet. It begins with network components, network classifications, and layered communication models, including the OSI and TCP/IP models and the responsibilities of their major layers. Physical- and data-link-layer concepts are introduced at an appropriate level, including transmission media, frames, MAC addressing, Ethernet, and switching. The course then examines the network layer through IPv4 and IPv6 addressing, subnetting, routing, routers, and path-selection concepts. Transport-layer functionality is studied through TCP and UDP, ports, reliability, flow control, and the distinction between connection-oriented and connectionless communication. Application-layer services include conceptual treatment of DNS, HTTP/HTTPS, and electronic-mail protocols. The course introduces wireless networking and Wi-Fi, basic mobility concepts, and important network-performance measures such as latency, throughput, packet loss, and bandwidth. Fundamental network-security concepts are also introduced, including common threats, firewalls, secure communication, and encryption in transit, while detailed security principles are reserved for the Information Security course. For Artificial Intelligence students, the course establishes the networking foundation required to understand cloud services, IoT systems, distributed data access, and networked AI applications without extending into specialized distributed Machine Learning. Upon completion, students should be able to explain end-to-end data communication, perform basic IP addressing and subnetting, describe routing and transport-layer behavior, diagnose fundamental connectivity problems, and understand how network characteristics influence the performance and reliability of digital systems and applications.

Type

Major Requirement

When

Year three, First semester

Prerequisite

None

Unlocks

Network security

This course introduces the engineering principles, processes, and practices used to develop software systems in a systematic, manageable, and maintainable manner. It begins with the concept of Software Engineering and the need for disciplined development approaches when building medium- and large-scale systems. The Software Development Life Cycle (SDLC) is examined from requirements analysis through design, implementation, testing, deployment, maintenance, and evolution. Students study Requirements Engineering, including elicitation, analysis, documentation, and management of functional and non-functional requirements. System modeling is introduced through appropriate representations such as use cases and selected UML diagrams. The course covers fundamental software design principles, including modularity, component decomposition, separation of concerns, cohesion, coupling, and introductory software architecture. Coding standards, documentation, configuration management, and version-control practices are also addressed. Software testing is introduced conceptually through unit, integration, system, and acceptance testing. Maintenance, software evolution, refactoring considerations, and technical debt are discussed to illustrate the long-term nature of software development. The course also introduces Agile Development, including appropriate elements of Scrum, team roles, iteration planning, effort estimation, risk management, collaboration, and software-project management. For Artificial Intelligence students, the course highlights selected differences between conventional software projects and data-driven or AI-oriented software, particularly the role of data, experimentation, and reproducibility, without extending into specialized MLOps practices. Upon completion, students should be able to analyze software requirements, produce suitable models and designs, organize software into manageable components, collaborate effectively within a development team, and apply engineering practices that improve software quality, testability, maintainability, and long-term evolution.

Type

Major Requirement

When

Year three, First semester

Prerequisite

None

Threat and Risk Assessment gives students a structured way to evaluate a defined digital asset or service. They identify assets, stakeholders, system boundaries, and data flows and distinguish a threat from a vulnerability, event, and consequence. A risk scenario is stated explicitly; likelihood and impact are assessed against declared criteria, with uncertainty recorded instead of hidden behind a number. Students compare reduction, transfer, and acceptance within the authority of a decision maker and assign a control, owner, review point, and residual risk. In a small web service or network case, they prioritize several scenarios and defend the ranking with reviewable evidence. A changed component or permission prompts reassessment, since adding a control alone does not make the risk disappear. A short outage is compared with disclosure of personal records; priorities vary with people affected, data sensitivity, and duration. Students review another team's assessment and ask where likelihood estimates came from and how they will be updated.

Type

Major Requirement

When

Year three, First semester

Prerequisite

None

This course introduces nursing students to the fundamentals of Islamic culture, worldview, and moral philosophy, with a specific focus on medical jurisprudence (Fiqh), bioethics, and patient care. Students will study the core tenets of Islamic faith, ethical principles governing human interaction, spiritual care, and contemporary bioethical issues (such as organ transplantation, end-of-life care, and reproductive health) aligned with Islamic legal rulings and Saudi healthcare practices.

Type

University Requirement

When

Year three, Second semester

Prerequisite

None

This course on self-marketing and personal development addresses self-improvement and life-building, focusing on enhancing human capabilities for the better by acquiring new skills or discovering existing abilities and enabling individuals to benefit from them in various life activities. The course helps students eliminate negative behaviors and adopt positive ones, set clear goals, and develop self-control. It also teaches decision-making skills necessary to build a strong personality capable of shaping a better future and contributing effectively to society.

Type

University Requirement

When

Year three, Second semester

Prerequisite

None

This code denotes the first specialization elective; the study plan does not name a specific course for the student to take. Its topics, learning outcomes, prerequisites, and assessment depend on the approved elective offered by the faculty. Students select an available subject that deepens a relevant area of the program. A final course description must state the knowledge, skills, activities, and assessment of the particular selected course. This general requirement description does not replace that official elective description.

Type

Elective Requirement

When

Year three, Second semester

Prerequisite

None

Network Security builds on Computer Networks to protect infrastructure and communication. Students map trust zones and traffic paths, then study segmentation, firewall rules, secure remote access, wireless protection, and event monitoring. Blocking unauthorized traffic is distinguished from detecting anomalous activity, and students consider what logs can reveal and what encryption or missing telemetry obscures. For a small organization, they design an access policy among users and services and test permitted and denied cases so a legitimate service is not inadvertently blocked. Misconfiguration, updates, and the initial response to an alert are considered. Each control is linked to a protection goal and a testable operational limit. In a diagnostic exercise, firewall logs are compared with service requests to see whether required traffic was blocked or unexpected traffic allowed. A rule records source, destination, port, rationale, and review date instead of leaving a broad temporary opening indefinitely.

Type

Major Requirement

When

Year three, Second semester

Prerequisite

Computer Networks

Software Security treats development and review with attention to flaws that can become paths for abuse. Trust boundaries, input checks, identity and authorization, error handling, secrets, and software dependencies form the core. Students turn a functional requirement into unauthorized-use cases and review code or a design to find the root cause of a flaw rather than only its symptom. Unit tests, automated scanning, and human review are compared for what each finds and misses; a repair includes a regression test. Controlled examples span backend services and components without duplicating Web Security's focus on browser and request behavior. Security considerations are linked from requirements through maintenance, with assumptions and limits documented. A case involving an outdated dependency or an access token committed to a repository asks students to trace exposure, repair, and notification. They compare an immediate fix with a maintainable update plan that prevents recurrence without needlessly breaking service compatibility.

Type

Major Requirement

When

Year three, Second semester

Prerequisite

None

Unlocks

Information security management

Cloud Computing covers service models and the division of provider and customer responsibility, with virtualization, containers, scaling, and load balancing. Students choose storage and processing for a mobile-facing API and consider latency, availability, and cost. Permissions, logs, metrics, backup, and recovery support a simple architecture whose component failures can be analyzed. Students compare two designs for performance, availability, cost, and administrative effort, and locate responsibility for protecting data and settings. A hypothetical failure of a component or region asks what users experience, what can be restored, and how much work might be lost. Students estimate monthly cost for a hypothetical service using assumptions about users, requests, storage, and data transfer, then change one assumption to test sensitivity. Increasing one server's size is compared with adding several smaller instances while checking whether the database or network becomes the bottleneck.

Type

Major Requirement

When

Year three, Second semester

Prerequisite

None

This course develops students’ ability to prepare clear, structured, professional, and academically sound technical documents and reports, with particular relevance to Engineering, Computing, and Artificial Intelligence projects. It begins by distinguishing general writing from technical writing and emphasizes precision, clarity, conciseness, organization, and objectivity. Students learn the structure of a technical report, including titles, abstracts or executive summaries, introductions, background sections, methodologies, results, discussions, conclusions, and recommendations. Appropriate organization of sections and subsections and logical flow among them are emphasized. The course covers effective presentation of technical information through tables, figures, charts, and diagrams, including appropriate captions and in-text references. Students learn to adapt the level of technical detail to the intended audience and to use terminology consistently. Academic referencing and citation management are addressed together with plagiarism avoidance and the distinction among paraphrasing, quotation, and summarization. Ethical reporting practices are emphasized, including accurate presentation of evidence, avoidance of exaggerated conclusions, and transparent reporting of limitations or negative results. For AI-oriented work, students learn to document data sets, methodologies, experimental setups, evaluation metrics, results, and limitations in ways that support reproducibility. The course also includes preparation of technical presentations, project documentation, and selected professional technical communications. Upon completion, students should be able to prepare a complete and logically organized technical report, present data and experimental findings accurately, use references appropriately, document methodologies and experiments clearly, and communicate technical work in forms suitable for academic projects, graduation work, and professional practice.

Type

College Requirement

When

Year three, Second semester

Prerequisite

None

This course introduces nursing students to the fundamental concepts of environmental health and its impact on human health and disease prevention. Students will explore air and water quality, climate change, medical waste management, chemical hazards, vector-borne diseases, and environmental safety standards within healthcare system and community settings.

Type

University Requirement

When

Year four, First semester

Prerequisite

None

This code is the second cybersecurity specialization elective. The plan does not identify the course the student will select, so topics, learning outcomes, prerequisites, and assessment depend on the approved course actually offered. Students use the available options and departmental guidance to extend or deepen an area studied in networks, software, or information protection. The final description for the selected course must specify its technical knowledge, suitable activities or applications, and assessment boundaries. This explains the elective's place in the plan and does not substitute for the official description of a particular offered course.

Type

Elective Requirement

When

Year four, First semester

Prerequisite

None

Information Security Management links organizational goals to governance, policy, and staff responsibility. Students identify assets and owners, classify information, and translate risk assessment into prioritized controls and traceable actions. Access and account life cycles, awareness, suppliers, incident reporting, continuity, backup, and recovery are discussed. A policy stating a principle is distinguished from an implementation procedure and from evidence that the procedure is followed. For a small organization, students prepare a brief risk register, access policy, and review plan, identify who may accept residual risk, and track control implementation. Measurement, review, and improvement are addressed without assuming that a document or certificate alone proves effective protection. In a review exercise, students find that a written access-granting procedure differs from actual system behavior. They identify evidence, the reason for the gap, and corrective action. Restoring service after an outage is compared with verifying restored data integrity, since a running service alone does not prove the information is sound.

Type

Major Requirement

When

Year four, First semester

Prerequisite

software security

Digital Forensics Techniques introduces a systematic approach to evidence from devices, files, and networks. Students define examination scope and appropriate authorization, preserve originals, create verifiable copies with hashes, and document chain of custody. File-system traces, metadata, logs, timestamps, and relevant indicators are studied, including time-zone differences and the risk that collection itself changes data. A technical observation is separated from a plausible inference or a claim needing further support. Reports state source, method, limitations, and reproducible findings. Privacy and limiting review of unrelated material are considered throughout; access without authorization or a single tool result is never treated as a conclusive determination. For an incident involving multiple devices, students weigh the urgency of volatile data against later verifiability and record who made the collection decision and when. They examine how two apparently conflicting incident times can invite a false conclusion unless device clocks and the source of each log are documented.

Type

Major Requirement

When

Year four, First semester

Prerequisite

None

The Digital Forensics Techniques Laboratory applies evidence handling to authorized training images, virtual devices, and synthetic data. Students record the initial media condition and task scope, make a working copy, and verify hashes before and after examination. Files, metadata, logs, and event times are correlated in a timeline, with tool versions, settings, and inconclusive findings documented. A misleading trace or an incorrectly set device clock requires students to test an interpretation rather than accept the first explanation. A short report separates raw observations from inference, while copies and results are stored under laboratory procedures without exposing real people's data. Recovery of a deleted file or message in a log does not by itself identify its author. Students state what the traces establish and what needs independent support. They compare a second tool on a limited sample to decide whether divergent results reflect interpretation or differing settings.

Type

Major Requirement

When

Year four, First semester

Prerequisite

None

This course systematically prepares students for the subsequent Graduation Project by requiring them to identify a meaningful real-world or research problem in Artificial Intelligence or Computing and transform it into a clearly defined and feasible project. Students begin by selecting a problem domain, identifying relevant stakeholders or users, analyzing the problem, and defining project objectives and research or development questions where appropriate. Students conduct a structured literature or technology review to understand existing approaches, available tools, data, and limitations and to establish the rationale for the proposed project. Software-oriented projects define functional and non-functional requirements, while research-oriented projects identify experimental and methodological requirements. The course includes feasibility analysis and selection of suitable technologies, data sets, algorithms, platforms, and tools. Students prepare an initial system architecture or research methodology. AI projects are expected to identify data sources, data-preparation strategies, appropriate baselines, evaluation metrics, comparison procedures, privacy concerns, and relevant ethical considerations. Project planning is addressed through task decomposition, schedules, deliverables, resource requirements, risks, and mitigation strategies. Students are also expected to define a testing or evaluation plan before implementation begins. The principal output is a comprehensive project proposal including background, problem statement, objectives, related work, methodology, requirements, proposed design, evaluation plan, timeline, and references. Upon completion, students should have a technically feasible and academically defensible proposal that can be presented to an academic committee and used as the direct foundation for implementation in the Graduation Project course.

Type

College Requirement

When

Year four, First semester

Prerequisite

None

Unlocks

graduation project

This course develops students’ ability to identify ethical issues and professional responsibilities encountered in Engineering, Computing, and Information Technology and to make professionally responsible decisions based on recognized principles. It begins with the concept of professional ethics, distinctions between legal compliance and ethical responsibility, and the role of professional codes of conduct. Students examine integrity, accountability, truthful reporting, conflicts of interest, intellectual property, and responsibilities toward employers, clients, users, and society. Privacy, confidentiality, data protection, and cybersecurity are considered professional obligations rather than purely technical concerns. Particular attention is given to AI ethics, including bias, fairness, transparency, explainability, accountability, use of personal information, and potential harms associated with automated decision making. The focus is on ethical analysis and governance rather than repetition of AI algorithms. The course also considers professional responsibility when developing software or AI systems that may affect health, safety, rights, opportunities, or access to services. Testing, documentation, risk assessment, disclosure of limitations, and responsible deployment are examined in this context. Case studies are used to analyze conflicts involving performance versus privacy, profit versus safety, and innovation versus social responsibility. Students identify stakeholders, assess possible consequences, and compare alternative actions. Upon completion, students should be able to recognize ethical issues in technology projects, evaluate the impacts of technical decisions on different stakeholders, apply professional principles to decision making, and explain individual and organizational responsibilities associated with the design, development, deployment, and use of AI and digital technologies.

Type

College Requirement

When

Year four, First semester

Prerequisite

None

This course introduces concepts and methods for transforming problems and ideas into innovative and potentially viable ventures, with appropriate emphasis on technology-based products and services. It begins with entrepreneurship and innovation and distinguishes among ideas, inventions, and innovations. Students learn how unmet needs and practical problems can become opportunities for new products or services. The course covers opportunity identification, customer discovery, analysis of users, markets, and competitors, and development of a clear value proposition describing the benefit provided to a target customer or user group. Students are introduced to business models and their major components, including customer segments, channels, revenue streams, costs, key resources, activities, and partners. A tool such as the Business Model Canvas may be used to structure venture concepts. Students develop a Minimum Viable Product (MVP) or prototype, test assumptions with potential users or stakeholders, collect feedback, and iterate before committing substantial resources to full-scale development. The course also introduces pricing, marketing, funding, basic financial feasibility, intellectual property, and risk assessment. For AI-oriented ventures, students consider additional issues associated with data availability, infrastructure, responsible AI use, and the need to demonstrate that AI contributes meaningful value rather than being included solely for technological novelty. Upon completion, students should be able to analyze a problem or opportunity, formulate an innovative solution, develop an initial value proposition and business model, create a prototype or MVP, evaluate basic feasibility, and present the proposed venture effectively to stakeholders or potential supporters.

Type

College Requirement

When

Year four, First semester

Prerequisite

None

This course introduces nursing students to the fundamentals of Hadith Studies (Ulum al-Hadith) with a focus on prophetic traditions related to health, cleanliness, patient care, medical ethics, and compassion. Students will learn the basic methodology of Hadith authentication and examine selected authentic Prophetic traditions (Ahadith) that guide professional nursing behavior, personal hygiene, mental resilience, holistic healing, and ethical duty toward patients in Saudi healthcare settings.

Type

University Requirement

When

Year four, Second semester

Prerequisite

None

This code marks the third cybersecurity specialization elective. The plan names no particular course; topics, outcomes, prerequisites, and assessment follow the approved course offered in this slot. Subject to actual availability and academic advice, students may choose a field that complements their preparation or supports their graduation-project or professional interests. The selected course needs its own description of content, skills, practical work, and assessment. This general text must not be read as the technical syllabus of an elective the plan has not specified.

Type

Elective Requirement

When

Year four, Second semester

Prerequisite

None

Ethical Hacking presents authorized security testing as a process: define scope, goals, and rules of engagement, gather information, analyze attack surfaces, safely validate weaknesses, report findings, and retest after repair. Students distinguish an indicator of weakness from demonstrated impact in a defined environment and avoid service disruption or unnecessary exposure of real data. Network, service, and application misconfigurations illustrate how findings are prioritized by exploitability, impact, and organizational context. Reports describe reproducible steps, evidence, test limits, priority, and remediation. All activities stay within explicit authorization and a teaching environment or consenting organization, with findings handled confidentially. For a finding, students identify service version, conditions for occurrence, and whether required privileges alter impact for an ordinary user. They choose a low-impact validation path first and explain why a repair must be retested without assuming that closing one port resolves the underlying cause.

Type

Major Requirement

When

Year four, Second semester

Prerequisite

None

In the Ethical Hacking Laboratory, students perform a bounded assessment of isolated, authorized training systems. They first read the scope document, record permitted assets, and configure discovery tools to avoid harming the service. Deliberately vulnerable services or applications provide cases in which students collect only the evidence needed to demonstrate impact. An initial result may be a false positive, requiring an alternative check. After proposing a fix or configuration change, students retest and compare outcomes. Their report states what was and was not examined and what risk remains. Discovery of another system or account never extends the authorization for an exercise. Each student records test time, tool settings, expected result, and observed result and resets the environment where needed so a peer can reproduce the check. Cases in which a scan is more aggressive than the rules allow require lower request rates or a less intrusive method.

Type

Major Requirement

When

Year four, Second semester

Prerequisite

None

Field Training applies the student's preparation in an approved workplace under academic and professional supervision. Supervisors and student agree in advance on tasks, hours, access boundaries, and assessable learning outcomes, such as asset documentation, configuration review, or support for protection procedures as permitted by the host. The student records completed work, observations, acquired skills, and challenges and distinguishes personal contributions from work merely observed. Workplace confidentiality, privacy, safety rules, and authorization boundaries govern all activities. A final report omits secrets and client data not approved for disclosure. Assessment considers the quality of work, records, and reflection rather than attendance hours alone. If access limits prevent an assigned task, the student and supervisor agree on a legitimate alternative meeting the learning outcome, such as de-identified data or a training case. Periodic review gives specific feedback on communication, deadlines, and error handling, leading to a brief measurable improvement plan.

Type

Major Requirement

When

Year four, Second semester

Prerequisite

None

The Graduation Project implements the approved proposal from the preceding course, documenting why any scope or evaluation change was made. A team develops a prototype, tool, or applied study for a defined cybersecurity problem in an authorized environment and tests functionality, security properties, and limitations against measurable success criteria. Data quality and reproducibility are examined, and results are compared with the project's objectives and appropriate existing approaches rather than judged only by a working interface. Roles, contributions, and reviews are recorded. The team submits sharable code or materials and a technical report on design, method, outcomes, failures, and limits, then presents and defends decisions without claiming absolute security. If an experimental target is missed, the team explains why and how the shortfall changes its conclusion instead of omitting inconvenient results. It tests a normal use case and one defined threat scenario and distinguishes prototype feasibility from readiness for deployment in a real organization.

Type

Major Requirement

When

Year four, Second semester

Prerequisite

Freelance Work

This course aims to introduce students to the concept of freelancing as one of the modern work models that relies on independence and flexibility in providing services or products online or directly. It focuses on equipping students with the essential skills and knowledge needed to start in the freelancing market, advance toward project management, and achieve financial sustainability

Type

University Requirement

When

Year four, Second semester

Prerequisite

None