Teaching

Speech Processing (EN/FR) 🔊

MSc NLP (Li), IDMC - Université de Lorraine, 2024-2025.

I am supervising practical sessions as part of the "Speech Processing" course, following the lectures delivered by Dr. Yves Laprie and Dr. Romain Serizel. This course delves into fundamental aspects of speech processing, including signal representation, enhancement techniques, and phoneme analysis. Through practical exercises, students gain hands-on experience applying these concepts in Python, developing essential skills for speech analysis and processing.

Speech Robustness (EN/FR) 🔊

MSc NLP (ILPC), IDMC - Université de Lorraine, 2024-2025.

I am supervising practical sessions as part of the "Speech Robustness" course, following the lectures delivered by Dr. Romain Serizel. The course explores key topics such as speech production, speech representation, speech enhancement, and speech recognition. These practicals provide students with hands-on experience in implementing speech processing techniques using Python.

Introduction to Python (EN/FR)

MSc NLP and Master in Cognitive Science, IDMC - Université de Lorraine, 2023-2025.

I am supervising Python practicals that follow Pr. Karën Fort's lectures, covering essential Python fundamentals such as strings, control flow, loops, lists, tuples, sets, and file handling. The practicals involve working with real-world examples like the “80jours50l” and “MyBiblio” files. Additionally, topics such as dictionaries, functions, modules, and key libraries like NumPy and Pandas are explored, concluding with a session on objects. Each topic is accompanied by interactive notebooks, and guidance is provided throughout all the exercises.

Virtualization and Docker (FR)

Bachelor in Computer Science, IUT Nancy Charlemagne - Université de Lorraine, 2023-2024.

I am teaching a comprehensive introduction to virtualization, incorporating both lectures and practicals. The materials given to students, including the slides, are built upon the courses of the Associate Professor Philippe Dosch. The course covers key virtualization concepts such as containers, hypervisors, and virtual machines, along with practical applications of Docker and KVM. The student will engage in hands-on exercises to solidify his/her understanding of these topics, gaining experience in both system administration and deployment in virtualized environments. The course balances theoretical foundations with practical implementations.

Introduction to LaTeX (EN)

MSc NLP, IDMC - Université de Lorraine, 2023-2025.

I am teaching a thorough introduction to LaTeX, a powerful typesetting system used to create documents with complex formatting, such as academic papers, theses, and reports. Throughout the course, students will learn essential LaTeX concepts, including document structure, text formatting, lists, mathematical formulas, tables, images, and citations. In two practical sessions, students will produce a report that can serve as a valuable starting point for their future master projects, equipping them with the skills to create professional-grade documents for academic and research purposes.

Introduction to Shell (EN)

MSc NLP, IDMC - Université de Lorraine, 2023-2025.

This course offers a practical introduction to shell scripting and file manipulation in Unix-like operating systems. I teach students essential commands for navigating file systems, handling text files, and performing basic scripting tasks. In practical sessions, students will work on exercises to create and manipulate files and directories, building useful shell scripts that can serve as a foundation for their future projects.

Algorithm Quality and Complexity (FR)

Bachelor in Computer Science, IUT Nancy Charlemagne - Université de Lorraine, 2023-2024.

This course introduces students to the analysis of algorithms, focusing on understanding and evaluating their efficiency using mathematical techniques. Key topics include time complexity, asymptotic notations (O, Ω, Θ), and recurrence relations. Students will explore both theoretical and practical aspects through mathematical demonstrations and problem-solving sessions. The skills developed will enable students to apply these techniques when designing algorithms or evaluating their performance.