Aim: The aim of this course id to introduce the students to the real ethical link between medical data and bioinformatics in terms of using tools, developing workflows, and analysis of genomic data in the form of sequencing, variant calling, annotation,2, and association with databases. Course contents: Introduction to Clinical Bioinformatics, Molecular basis of disease, Personalized and

Aim: The aim of this course is the implementation of a framework that benefits from the interconnected health care systems to monitor the population health and to enhance the public health strategies and practice Course contents: Population health and its determinants, the emerging role of Population health informatics, Distinguishing between Population health informatics and public health

Aim: Compare and select the most appropriate method from: neural, deep learning, fuzzy, evolutionary or hybrid method for any biomedical dataset. Successfully applying this method to analyze the results and compare and select the appropriate sensor for measuring each biomedical data. In addition, the student will construct appropriate sensor network structures and demonstrate the advantage of

Aim: The course covers the principles of imaging informatics, modern strategies of image processing, spatial normalization, statistical parametric mapping, non-parametric image statistics. Though many examples in this course will apply to medical images, the presented strategies are general, apply to a wide range of other medical imaging modalities, such as CT, SPECT and PET, and also cover

Aim: This course covers the fundamentals of digital signal processing topics related to biomedical research and clinical medicine. The course introduces and explores concepts of analyzing and processing signals of biological systems using advanced mathematics. The course will examine the mathematical concepts of low-level signal and high dimensional image processing/analysis (e.g., enhancement and

Aim: The aim of this course is understanding how text mining is applied to texts and literature of the biomedical domains Course contents: Basics of text processing, Natural language processing, Named entity recognition, Relation extraction, Information retrieval/document classification, Concept normalization, Ontologies and computational lexical semantics, User Needs for Computer-based Patient

Course Aim and Contents: The group project is conducted by students who select a project topic according to their subject of interest and the availability of facilities and advisors. Each group carries out necessary research and development work and submits a detailed report. The report is submitted to a departmental committee for evaluation and discussion. In the second semester, each group

Course Aim and Contents: The group project is conducted by students who continue their selected project topic. Each group carries out necessary research and development work and submits a detailed report. The report is submitted to a departmental committee for evaluation and discussion. In the second semester, each group should develop an integrated, complete and functional computing system or

Course Aim: This course aims to introduce students to the fundamental principles of computer science and computational thinking without assuming prior programming experience. Students will learn how to approach problem-solving methodically, how to structure and represent problems, and how to design algorithmic solutions using control flow, data flow concepts, and basic modeling techniques

Course Aim: This course aims to introduce students to the essential principles and practices of computer programming. Designed for students with little or no prior programming experience, the course provides a strong foundation in programming, basic algorithms, and software design. Students will learn to analyze and solve multidisciplinary problems, design and implement small-scale programs using

Course Aim: This course aims to build upon the foundational programming and problem-solving skills developed in the first semester. This course focuses on the principles of software engineering, object-oriented programming, and the design and implementation of basic data structures and algorithms. Students advance their computational thinking skills through the development of larger, modular, and

Course Aim: The course aims to offer a rigorous introduction to the theory and practice of data structures and fundamental algorithms. Students will explore the design, analysis, and implementation of both classical and advanced data structures used in solving computational problems efficiently. Emphasis is placed on algorithmic efficiency, trade-offs between data structures, and the development

Course Aim: This course introduces the basics of database systems analysis and design. You will be introduced to the internal organization of a database system, and the main tasks of a database developer Course contents: Introduction to DB, The Relational Model, Structured Query Language, Data Modeling and E-R Model, Physical Database Design, Database Administration, Functional Dependencies and

Course Aim: This course aims to introduce students to the techniques for the design and analysis of efficient algorithms, emphasizing methods useful in practice. Topics include dynamic programming, greedy algorithms, amortized analysis, graph algorithms, graph and tree traversal, and shortest paths. Advanced topics may include network flow, computational geometry, and number-theoretic algorithms

Course Aim: The Operating System course aims to give students an in-depth comprehension of the fundamental operating system principles, concepts, and techniques. This course gives students the knowledge and skills to design, implement, and manage operating systems effectively. Students should be able to comprehend the tradeoffs involved in designing and managing various operating systems and

Course Aim: The course aims to develop a broad understanding of the discipline of software engineering. It seeks to complement this with a detailed knowledge of techniques for the analysis and design of software systems. It aims to set these techniques in an appropriate engineering and management context. Course contents: Introduction to Software Engineering, Software Process, Software