Nawres Gammoudi

My lessons in Machine Learning and Artificial Intelligence are structured to combine clear theoretical explanations with practical applications. I start by evaluating the student’s current level and objectives in order to design a personalized learning plan.
Each session typically includes three parts. First, I explain the core concepts in a simple and intuitive way (for example: regression, classification, decision trees, model evaluation, and data preprocessing). Then we work on practical examples and exercises, often using real datasets to understand how algorithms behave in practice. Finally, we review the results together and discuss how to improve the approach or model.
I also support students with university assignments, exam preparation, and projects related to data science, Python programming, and machine learning models. My goal is not only to help students solve problems but also to ensure they truly understand the reasoning behind each method.
Lessons are interactive, and I encourage students to ask questions and actively participate. I adapt the difficulty and pace depending on the student’s level, whether they are beginners discovering AI or students already studying computer science or data science.
By the end of the lessons, students should be able to understand machine learning concepts, implement models, analyze results, and approach real-world data problems with confidence.