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Professor with advanced information, helps students and students consult exams and conferences. Interviens aux class

From 35 £ /h

I am a certified computer science professor who helps graduates and students with exam retakes and competitions. I tutor preparatory classes (MPSI, MP, PSI, ECS, etc.) up to university level (Bachelor's & Master's in Science or Economics). My method is based on understanding the lessons, practicing correctly, organizing the concepts, and completing exercises and problems of your choice. Each session includes verbal exercises, methodological tips, and subsequent personalized advice. You will receive a video recording and an annotation in PDF format after each session. The online courses are conducted via Google Meet, 5 days a week, with flexible scheduling. I am available between sessions to answer questions. Contact me for an initial consultation.

Location

Online from Morocco

About Me

**🎓 Associate Professor of Mathematics – Make a difference in your studies!**

With several years of experience as a teacher, examiner and examiner, I support pupils and students of all levels to achieve their academic goals and pass competitions or exams.

### **📘 Supported Levels and Specialties:**
- **High school:** Terminale (French mission) and 2 Bac Sciences Maths.
- **Preparatory Classes (CPGE):** MP, PSI, MPSI, PCSI, ECS, ECT.
- **Universities:** Bachelor's and Master's courses in science or economics.

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### **🔑 Methodology:**
1. **Complete assimilation of the course**: Ensure that each concept is fully understood before moving on to practice.
2. **Targeted and progressive exercises**: A bank of varied and in-depth exercises, adapted to the specific needs of each student.
3. **Structure and organization**: Helps to develop effective and sustainable working methods.
4. **Tailor-made support**: Sessions adapted to each student to maximize their potential.
5. **Additional Resources**:
- **Video recording of each session** for review at any time.
- **Annotated PDF** containing all the notes and explanations shared during the course.

---

### **🎯 My strong points:**
- **Rigor and pedagogy**: Courses designed for clear and lasting understanding.
- **Flexibility**: Availability 5 days a week, with online courses via Google Meet.
- **Personalized follow-up**: Contact between sessions to answer questions.

---

**💻 Prices: adjustable according to level and terms.
**📲 Contact me now** for an initial discussion and an assessment of your needs.

---

Education

**"Guaranteed success in mathematics with an experienced and qualified professor - High school, preparatory and higher education, all topics covered"**

With **solid training** and **more than 10 years of experience**, I support you with methods adapted to succeed in your exams and competitions.

### **My academic background:**
- **Bac Sciences Maths**: Solid initial training in mathematics.
- **Bachelor's degree (2010-2013)**: Mathematics, Physics and Computer Science.
- **Master (2013-2015)**: Mathematics and Computer Science.
- **Agrégation (2015-2016)**: Mathematics.

### **My teaching experience:**
- **Since 2018**: Teacher in public and private **preparatory classes** (MP, PSI, ECS and ECT specialties).
- **Since 2012**: Academic support in **mathematics**, in groups and in private lessons.
- **Since 2020**: Content producer on a **higher education mathematics channel**, with several subscribers.

Experience / Qualifications

**"Guaranteed success in mathematics with an experienced and qualified professor - High school, preparatory and higher education, all topics covered"**

With **over 10 years of experience** in teaching mathematics, I support my students towards success by offering them personalized and rigorous support.

### **My teaching career:**
- **Since 2016**: Teacher in public and private **preparatory classes**, specializing in **MP, PSI, ECS and ECT**.
- **Since 2012**: Academic support in **mathematics** in groups and private lessons, for all levels.
- **Since 2020**: Content producer on a **higher education mathematics channel**, with a loyal audience of several subscribers.

Age

Children (7-12 years old)

Teenagers (13-17 years old)

Adults (18-64 years old)

Seniors (65+ years old)

Student level

Beginner

Intermediate

Advanced

Duration

90 minutes

120 minutes

The class is taught in

French

English

Arabic

Skills

Computer science

Computer programming

Reviews

Availability of a typical week

(GMT -04:00)

New York

Online via webcam

Mon

Tue

Wed

Thu

Fri

Sat

Sun

00-04

04-08

08-12

12-16

16-20

20-24

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My lessons are customized to meet each student's unique needs and are designed to be engaging and insightful.

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- Preparation for IB/IA, A-Levels, GCSE, University Entry, or equivalent.
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Ongoing Support: Get unlimited email support for any questions you have between sessions.

As a Python expert, I have a passion for teaching and sharing my knowledge. My goal is to guide you effectively in your learning journey.

Book Your First Lesson:

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📌 Mentored students to achieve top grades in Cambridge ICT & Computer Science exams.
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A- TOPICS YOU CAN EXPLORE AND MASTER:
1- PYTHON FOUNDATIONS
• Variables, data types, operators, conditional structures, loops, functions, modules, files, exceptions, and object-oriented programming
• Lists, tuples, dictionaries, sets, comprehensions, debugging, and writing clear, reusable, well-structured code
• Jupyter Notebook, Anaconda, Visual Studio Code, virtual environments, and package management

2 — PROGRAMMING, ALGORITHMS, AND COMPUTER SCIENCE FOUNDATIONS
• Algorithmic thinking, problem decomposition, pseudocode, flowcharts, procedural programming, object-oriented programming, recursion, and modular program design
• Fundamental data structures including arrays, lists, stacks, queues, dictionaries/hash tables, sets, trees, graphs, and their appropriate use
• Searching, sorting, traversal, algorithm efficiency, computational complexity, Big-O notation, debugging, testing, code organization, and problem-solving strategies
• Practical programming exercises ranging from beginner problems to university-level algorithmic and computational challenges

3- DATA PREPARATION AND EXPLORATION
• NumPy and pandas for importing, cleaning, transforming, filtering, grouping, reshaping, and merging data
• Missing values, duplicates, outliers, inconsistent formats, data leakage, and data-quality validation
• Exploratory data analysis using descriptive statistics, Matplotlib, Seaborn, and graphical interpretation

4- MATHEMATICAL FOUNDATIONS
• Linear algebra, vectors, matrices, derivatives, optimization, probability, and statistics
• Loss functions, gradients, distance measures, regularization, likelihood, and model complexity
• Mathematical concepts are explained according to the learner’s level and the requirements of the selected algorithms

5- SUPERVISED MACHINE LEARNING
• Linear and polynomial regression, logistic regression, and regularized models
• k-nearest neighbours, decision trees, random forests, gradient boosting, support vector machines, and Naive Bayes classifiers
• Classification, regression, model assumptions, decision boundaries, feature importance, and interpretation of results

6- UNSUPERVISED LEARNING
• Clustering using k-means, hierarchical clustering, and density-based methods
• Principal component analysis, dimensionality reduction, anomaly detection, and pattern or structure discovery
• Method selection, evaluation of data structure, and interpretation of results without predefined labels

7- MODEL EVALUATION AND IMPROVEMENT
• Training, validation, and test sets; cross-validation; hyperparameter optimization
• Accuracy, precision, recall, specificity, F1 score, ROC–AUC, confusion matrices, MAE, MSE, RMSE, and R2
• Underfitting, overfitting, bias–variance trade-off, class imbalance, feature engineering, feature selection, scaling, and regularization

8- DEEP LEARNING
• Neural-network foundations, activation functions, forward propagation, backpropagation, and gradient descent
• Multilayer perceptrons, convolutional neural networks, recurrent neural networks, and Transformer foundations
• TensorFlow, Keras, or PyTorch depending on the learner’s project and working environment

9- ARTIFICIAL INTELLIGENCE APPLICATIONS
• Natural language processing, text classification, embeddings, sentiment analysis, and foundations of language models
• Computer vision, image classification, fundamental principles of object detection, and image preprocessing
• Recommendation systems, forecasting, anomaly detection, intelligent automation, and decision-support applications

10- GENERATIVE AI AND LARGE LANGUAGE MODELS
• Transformer architecture, tokens, embeddings, attention mechanisms, prompt engineering, Retrieval-Augmented Generation (RAG), and model evaluation
• Use of artificial-intelligence APIs, vector databases, document-retrieval systems, and structured AI-enabled workflows when relevant
• Reliability, hallucinations, bias, privacy, responsible use, and appropriate human validation

11- TOOLS AND LIBRARIES
• Python, NumPy, pandas, Matplotlib, Seaborn, scikit-learn, SciPy, Statsmodels, TensorFlow, Keras, and PyTorch
• Jupyter Notebook, Anaconda, Visual Studio Code, Git, GitHub, SQL, Excel, and Power BI when useful to the project
• Additional libraries may be introduced depending on the selected specialization and dataset

12- PROJECTS, RESEARCH, AND INTERVIEW PREPARATION
• Complete projects covering data preparation, model development, evaluation, interpretation, and presentation of results
• University assignments, dissertations, theses, research projects, portfolio projects, technical interviews, and professional applications
• Code review, debugging, documentation, reproducibility, model comparison, and communication of results

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B- PERSONALIZED TUTORING: LEARNING HOW TO REASON
Machine learning and artificial intelligence become much more accessible when mathematics, algorithms, Python code, data, and real-world applications are clearly connected.

My lessons help you move beyond simply copying code or using models as “black boxes.” You will learn how to define the problem correctly, prepare the data, select an appropriate algorithm, understand how it works, train and evaluate the model, diagnose errors, improve performance, and interpret results rigorously and responsibly.

Each lesson is personalized according to your current level, mathematical background, programming experience, dataset, university work, research project, interview preparation, or professional objective. We begin by identifying your existing knowledge, software environment, expected outcomes, and main conceptual or technical difficulties. We then establish a structured learning plan.

The first lesson combines a discussion of your background, objectives, and tutoring needs; an initial assessment of your current knowledge; personalized planning and organization of future sessions; and a short trial lesson to determine the most effective learning approach.

A typical session may include conceptual explanation, development of mathematical intuition, live coding, guided implementation, model evaluation, technical problem solving, and a concise summary of the next steps.

You may work with your own dataset, university assignment, research project, or professional problem, provided that confidential information is handled appropriately. I can also provide structured examples and datasets suited to your level.

My goal is not simply to help you run an algorithm. It is to help you understand why it is appropriate, how it learns from data, how to evaluate it correctly, why it may fail, and how to build a reliable, interpretable, and scientifically rigorous solution.

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Whether you're preparing for IB, IGCSE, GCSE, or simply want to build confidence in Mathematics, I'm here to help. I have over 3 years of teaching experience and 7 years of professional software engineering experience, allowing me to explain mathematical concepts in a clear, logical, and practical way.

My lessons are tailored to each student's needs and learning pace. I believe understanding the "why" behind a concept is far more valuable than memorising formulas. During lessons, I use carefully prepared practice questions and exam-style exercises, many of which I create myself using professional typesetting tools like LaTeX that is used by IB and Cambridge directly.

I encourage students to ask questions freely and develop strong problem-solving skills. Whether you're aiming to improve your grades, prepare for school exams, or study for international curricula such as IB, IGCSE, or GCSE, I'll help you build confidence step by step in a supportive learning environment.

I use a Pen Display Tablet to write on it using Goodnotes as the writing app, which I share the link to the whiteboard used with the students.

Lessons are available online or in-person (within 30 mins train travel from Shinjuku, Tokyo), and are conducted in English.