As a PhD researcher, I contribute to teaching activities at Mohammed V University, focusing on computer science and data science courses.
Courses Taught
Mathematics for Computer Science
- Linear algebra and matrix operations
- Probability theory and statistics
- Discrete mathematics and logic
Machine Learning
- Supervised and unsupervised learning algorithms
- Neural networks and deep learning fundamentals
- Model evaluation and validation techniques
Data Science
- Data preprocessing and cleaning
- Exploratory data analysis (EDA)
- Statistical inference and hypothesis testing
Artificial Intelligence
- Search algorithms and optimization
- Knowledge representation and reasoning
- Introduction to multi-agent systems
Statistics & Probability
- Descriptive and inferential statistics
- Probability distributions
- Regression analysis
Teaching Philosophy
My teaching approach emphasizes:
- Conceptual Understanding — Building strong theoretical foundations before diving into applications
- Hands-On Practice — Real-world projects and coding exercises to reinforce learning
- Real Datasets — Working with authentic data to prepare students for industry challenges
- Project-Based Learning — Collaborative projects that develop teamwork and problem-solving skills
- Interactive Sessions — Encouraging questions, discussions, and peer learning
Tools & Technologies Used in Teaching
- Programming: Python, R, MATLAB
- Libraries: Scikit-learn, TensorFlow, Pandas, NumPy
- Platforms: Jupyter Notebooks, Google Colab
- Visualization: Matplotlib, Seaborn, Plotly
Open to Collaboration
I am available for:
- Guest lectures and workshops
- Student supervision (Master’s and PhD level)
- Curriculum development in AI/ML/Data Science