Formation Professionnelle et Certifiante
Aperçu du programme :
Détails du programme:
| Dates | Starts March, September Programme de 6 mois. |
| Horaire | Le samedi de 10h00 à 13h00 |
| Langue | Français et anglais |
| Format | Accès à un contenu en ligne de qualité de MUST et Coursera. Des laboratoires pratiques offrant des sessions de travail avec un professeur de MUST. |
| Dernier délai d’inscription | March, September |
| Emplacement | MUST University, Lac3, Tunis. |
| Coût | 2800 TND. Discounts: 50% for students (MUST or otherwise).International participants: 1400 USD |
Thèmes du programme :
Part 1: Foundations of Machine Learning and Deep Learning
- Mathematical Foundations of Machine Learning
- Supervised and Unsupervised Learning
- Machine Learning with Python
- Introduction to Deep Learning & Neural Networks
- Building Deep Learning Models with Keras & TensorFlow
- Computer Vision and Image Processing
- Introduction to Neural Networks with PyTorch
- Deep Learning with PyTorch
- AI Capstone Project with Deep Learning
Part 2: Advanced Generative AI and Large Language Models
- Generative AI and LLMs: Architecture and Data Preparation
- Foundational Models for NLP & Language Understanding
- Generative AI Language Modeling with Transformers
- Engineering and Fine-Tuning Generative AI Models
- Advanced Fine-Tuning for LLMs
- AI Agents and Autonomous Systems with RAG & LangChain
- Project: Generative AI Applications with RAG & LangChain
Coursera Instructeur(s)
Nos instructeur(s) :
Tarek Gasmi is an Assistant Professor in Computer Science. Tarek’s academic research and industrial expertise encompass Edge and Cloud AI, Computer Vision, MLOps, LLMOps and data analytics. Tarek is recognized as an Nvidia Faculty Ambassador and a Microsoft Certified Trainer. Additionally, Tarek contributes as a Co-Founder and CEO of DataDoIt startup, focusing on the powerful combination of Computer Vision and Generative AI, particularly in the domain of intelligent video analytics.
Dr. Wafa Mefteh earned her PhD in Computer Sciences, with a focus on Artificial Intelligence, from the University of Toulouse III – Paul Sabatier. Her doctoral research was conducted at the Institute for Computer Sciences Research of Toulouse (IRIT), within the SMAC (Multi-Agent Cooperative Systems) team. In addition to her academic qualifications, she has acquired several professional certifications for Trainers (Machine Learning, Data Science, Big Data, Business Intelligence, …).
From 2009 to 2020, she held several positions as a researcher-teacher at various esteemed institutions. Since 2020, she has been serving as an Assistant-Professor of Higher Education in Computer Sciences at the National Engineering School of Tunis. Throughout this period, she developed a strong and rigorous foundation in higher education through extensive studies, professional training, and multiple certifications in higher education pedagogy and online training engineering. Her teaching portfolio is both extensive and diverse, spanning all academic levels—from Licence’s to professional master’s, engineering, and research master’s programs. She has delivered a wide array of courses that cover main areas within computer sciences and Artificial Intelligence.
Throughout her career, she has supervised numerous projects across various academic levels, including Licence’s, engineering, and professional master’s programs. Her mentorship extends to supervising several research-masters and contributing to the supervision of PhD theses in areas such as software engineering, artificial intelligence and complex data management and engineering. Her research activities primarily revolve around the modeling and development of intelligent software systems, complex data management, and the development (design, simulation and implementation) of advanced artificial intelligence techniques to handle the complexity of Data and Systems. She has authored numerous published research papers that underscore her active contributions to the field.
Mentor(s):
Pr. Fakhri Karray is the inaugural co-director of the University of Waterloo Artificial Intelligence Institute and served as the Loblaws Research Chair in Artificial Intelligence in the department of electrical and computer engineering at the University of Waterloo, Canada. He is also Professor of Machine Learning and held the position of Provost at the Mohamed bin Zayed University of Artificial Intelligence (MBZUAI), a research-oriented artificial intelligence (AI) graduate institution in Abu Dhabi, UAE. Fakhri’s research focuses on operational and generative AI, cognitive machines, natural human-machine interaction, and autonomous and intelligent systems, with applications to virtual care systems, cognitive and self-aware devices, and predictive analytics in supply chain management and intelligent transportation systems.
He holds editorial roles in major publications related to intelligent systems and information fusion. Fakhri’s latest textbook, “Elements of Dimensionality Reduction and Manifold Learning,” was published by Springer Nature in early 2023. In 2021, he was honored by the IEEE Vehicular Technology Society (VTS) with the IEEE VTS Best Land Transportation Paper Award for his pioneering research on enhancing traffic flow prediction using deep learning and AI. Furthermore, his research on federated learning in communication systems earned him and his co-authors the 2022 IEEE Communication Society’s MeditCom Conference Best Paper Award. He holds fellowship status in the IEEE, the Canadian Academy of Engineering, and the Engineering Institute of Canada. Additionally, he has served as a Distinguished Lecturer for the IEEE and is a Fellow of the Kavli Frontiers of Science. Fakhri earned his Ph.D. from the University of Illinois Urbana-Champaign, USA.
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