The Operations Research course for fourth-year engineering students provides advanced knowledge in mathematical optimization and decision-making techniques. It covers linear programming (formulation, simplex algorithm, and duality theory), integer and Boolean programming using methods such as Branch and Bound and dynamic programming, as well as project scheduling techniques including MPM and PERT. The course also introduces convex optimization (Frank–Wolfe and Kelley cutting-plane methods) and unconstrained optimization methods such as gradient-based, direct, and modern metaheuristic approaches like particle swarm optimization. Emphasis is placed on practical applications using Python for modeling and solving real-world optimization problems, allowing students to implement algorithms and analyze results efficiently.
- Teacher: faiza mahi
- Teacher: boudjelal meftah
Business Intelligence (BI) is a set of ideas, methodologies, processes, architectures, and technologies that change raw data into significant and useful data for business purpose. Business
Intelligence can handle large amounts of data to help identify and evolve new opportunities for the business. Making use of these new opportunities and applying a productive scheme on it can provide a comparable market benefit and long-term stability . Business Intelligence (BI) technologies provide chronicled, present and predictive view of business operations. Common functions of enterprise Intelligence technologies are reporting, online
analytical processing, analytics, data excavation, process excavation, business performance management, benchmarking, text mining, predictive analytics and prescriptive analytics.
- Teacher: Mustapha Sahraoui
Teaching Objectives
This course provides a solid foundation in High Performance Computing (HPC) and its role in scientific computing.
Learning outcomes:
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Become familiar with parallel programming paradigms.
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Study the fundamental techniques for developing HPC applications.
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Understand commonly used HPC platforms.
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Learn methods for measuring, evaluating, and analyzing the performance of HPC applications.
Students will be introduced to the challenges associated with using HPC techniques to solve large-scale scientific problems.
Recommended prerequisites
Advanced Computer Architectures, Operating Systems I & II.
- Teacher: khadidja Yahyaoui