Course Description
This course in Numerical Analysis is specifically designed for third-year students in Computer Engineering (Licence 3 – Ingénierie en Informatique).
The main objective of this course is to develop and strengthen students’ abilities in numerical computation and numerical approximation techniques. It aims to equip them with the essential tools and methods needed to solve complex mathematical and engineering problems that cannot be solved analytically, with high accuracy and computational efficiency.
The course follows a clear and logical progression covering the following main topics:
- Numerical Differentiation Finite difference methods (forward, backward, central), error analysis, and higher-order approximations.
- Numerical Integration Newton-Cotes formulas, rectangle methods, trapezoidal rule, Simpson’s rule, Romberg integration, and Gaussian quadrature.
- Matrices, Eigenvalues and Eigenvectors Matrix operations, characteristic polynomial, eigenvalues, eigenvectors, and their fundamental properties.
- Matrix Decomposition and the Power Method Gram-Schmidt orthogonalization, QR decomposition, and the power method for computing dominant eigenvalues and eigenvectors.
- Numerical Solution of Ordinary Differential Equations Euler’s explicit and implicit methods, Runge-Kutta methods (particularly the classical fourth-order RK4), stability analysis, and practical implementation.
Through a combination of theoretical foundations, algorithmic development, and practical numerical experiments, students will gain the ability to select appropriate numerical methods, analyze their accuracy and stability, and implement them effectively in real-world scientific and engineering applications.
- المعلم: abdelouahab mani
This course is designed for third-year engineering students (Ing3) specializing in Artificial Intelligence. It introduces the ethical, legal, and societal issues related to artificial intelligence and the digital revolution. The course examines ethical challenges in AI design and deployment, data privacy, cybersecurity, professional responsibility, and the societal impact of computing technologies. It also addresses the responsibilities of social networks and ethical concerns in emerging technologies such as the Internet of Things and autonomous vehicles, with the goal of promoting responsible and ethical AI practices.
- المعلم: safa attia
This course provides 3rd-year AI students with a comprehensive introduction to project management, covering the full project lifecycle from initiation to closure. Students learn to distinguish projects from routine operations, define roles and responsibilities, plan and schedule tasks using tools like Gantt charts and PERT, manage resources and costs, monitor progress, and ensure quality. Emphasis is placed on both technical and human aspects, including team management, communication, and risk assessment. By the end of the course, students will be equipped to plan, execute, and successfully close AI-related projects while applying best practices in leadership, organization, and project control.
- المعلم: safa attia