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Since August 2023
Instructor since August 2023
Algorithmic Thinking: From Game Logic to Engineering Programming 🚀💡
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From 18 £ /h
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As a Digital Transformation student, I know that programming is a fundamental building skill—whether you are a future engineer or a curious young learner. I designed this course as a practical guide to mastering essential tools and, above all, to developing the creative mindset of a programmer.

You will learn how to break down complex problems into logical steps, turn your ideas into functional code, and view errors (“bugs”) as stimulating challenges rather than obstacles.
Extra information
A computer with stable internet access
notebooks, pens, pencils
For beginners/children: curiosity :)
Location
location type icon
Online from Morocco
About Me
Je suis passionnée par l’enseignement et le partage des connaissances, notamment en mathématiques, physique , anglais et programmation . Ayant déjà tutoré des lycéens dans ma ville natale, j’adapte toujours mes méthodes à chaque élève pour les aider à comprendre profondément les concepts et à progresser à leur rythme.

Mon approche combine rigueur, patience et encouragement : je m’assure que chaque élève se sente à l’aise pour poser des questions et explorer les sujets de manière active. J’aime travailler avec des étudiants motivés et curieux, mais je sais aussi accompagner ceux qui ont besoin d’un peu plus de soutien pour renforcer leur confiance et leurs compétences.

En tant qu’étudiante en ingénierie avec un fort background en sciences physiques et en technologies, j’apporte également une dimension pratique et concrète à mes cours, reliant la théorie à des applications réelles. Mon objectif est que chaque élève ne se contente pas d’apprendre pour réussir ses examens, mais développe une vraie compréhension et une passion pour la matière.

Je suis convaincue que l’apprentissage est plus efficace lorsqu’il est personnalisé, interactif et stimulant, et je mets tout en œuvre pour créer un environnement positif et motivant pour chaque étudiant.
Education
École Nationale des Sciences Appliquées de Béni Mellal - Maroc, Étudiante en Ingénierie, spécialisée en Transformation Digitale Industrielle et innovations technologiques
Experience / Qualifications
-Tutorat en Mathématiques, Physique et Anglais
-Engagement environnemental et climatique (membre de YOUNGO)
-Compétences techniques : Maîtrise de MATLAB, Excel, Word, PowerPoint, LaTeX et Linux. Connaissances en programmation (Python et C), modélisation physique et ingénierie des systèmes.
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
45 minutes
60 minutes
90 minutes
The class is taught in
English
French
Arabic
Reviews
Availability of a typical week
(GMT -04:00)
New York
at teacher icon
Online via webcam
Mon
Tue
Wed
Thu
Fri
Sat
Sun
00-04
04-08
08-12
12-16
16-20
20-24
This English program is designed for beginners of all ages and requires no prior knowledge. Its aim is to lay a solid foundation in English through progressive, structured learning that is accessible to everyone.

The course focuses on developing fundamental English skills, including:

-enrichment of basic vocabulary

-comprehension and oral expression

-Introduction to reading and writing

-learning simple grammatical structures

Teaching is based on interactive methods adapted to the learners' profiles, such as practical activities, guided exchanges, visual aids and fun exercises, in order to promote understanding and confidence in the use of the language.

This program allows learners to gradually communicate in English, strengthen their academic or personal foundations, and acquire the essential skills to continue their English learning in an academic or everyday setting.
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Dive into a dynamic and motivating approach to learning mathematics, designed for ambitious high school students! Through clear explanations, concrete examples, and progressive exercises, you will strengthen your understanding and build confidence. This course covers all the key high school concepts while developing your logic, methodology, and problem-solving skills. Get ready to excel, achieve your best grades, and approach exams with confidence and strategy. Join us to turn mathematics into an engaging challenge and aim for the High Honors distinction!
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Start your journey to Python mastery now by booking your first lesson. Whether you aspire to enter the development field or hone your existing skills, these courses are designed for you.
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The authenticity of an exchange. In a society increasingly rooted in a competitive approach, where automated exchanges with Artificial Intelligence cannot replace the need for human interaction, this is precisely what we lack.
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These courses are part of a structured and progressive training in Object-Oriented Programming (OOP) with JavaScript, designed for beginner or intermediate developers who want to understand in depth how the language works, write clearer, more maintainable code and prepare themselves calmly for modern frameworks like React ⚛️.

Object-Oriented Programming is often perceived as complex or abstract.

My goal is simple: to make it logical, concrete, and immediately applicable.

🎯 Training Objectives

Upon completion of this training, you will be able to:

Understanding what Object-Oriented Programming really is (and when to use it)
Create and manipulate objects in JavaScript in a clean and efficient way
Use ES6 classes, constructors, and methods with confidence
Mastering this, the prototype, and the instantiation logic
Apply encapsulation, inheritance, and polymorphism without confusion
Avoiding common mistakes made by OOP beginners
Structure your JavaScript code like a professional developer

📖 Training Plan – Object-Oriented Programming in JavaScript
1. Introduction to Object-Oriented Programming 🧠
Understanding the concept, objectives and benefits of OOP.
2. Procedural Programming vs. OOP
Why unstructured code quickly becomes unmanageable.
3. Objects in JavaScript
Properties, methods and representation of the real world.
4. The keyword this
Understanding the execution context (often poorly understood).
5. Limitations of simple objects
Why duplicating code is a bad idea.
6. Constructive functions
Create multiple objects from the same model.
7. The keyword new
What it's actually doing under the hood.
8. The prototype
Sharing methods and memory optimization.
9. ES6 Classes
Modern syntax and best practices.
10. The builder
Proper initialization of objects.
11. Data Encapsulation
Protect the internal state of objects.
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Reusing code intelligently.
13. The keyword super
Communication between parent and child in the classroom.
14. Polymorphism
The same behavior, several forms.
15. Composition vs. Inheritance
Choosing the right architecture.
16. Best practices in OOP
Write readable, scalable, and maintainable code.
17. Common mistakes made by beginners
Pitfalls to absolutely avoid.
18. Guided practical exercise
Creation of a concrete class (product, user, etc.).
19. Assessment Quiz (Multiple Choice Questions)
To validate the actual understanding of the concepts.

🛠️ Teaching method: Understand before writing

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Clear and illustrated explanations
Concrete examples from real projects
Simple but effective exercises
Constant questioning to avoid rote learning
Adaptation to the learner's level and pace
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🚀 Learner's result

At the end of the training, you will not only know how to write a JavaScript class.
You will know:

1- Why does it exist?
2- When to use it
3- and when not to use it

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a solid understanding of OOP
a cleaner and more professional code
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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

-------------------------------------------------------------------------------------------------------------------------------------------------------------------------------
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.

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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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My name is Jonathan. I am a young teacher with already 15 years of experience in the field of academic support for primary and secondary school children up to rhetoric.

I also provide individual monitoring for your work method, more particularly in terms of understanding the instructions and the work schedule. If you need a helping hand, I'm here to listen.
verified badge
An engineer by training, I have been supporting students of all levels, in mathematics and beyond, for 10 years.

My classes aren't just about explaining formulas: I strive to convey a work method, self-confidence, and a positive approach to learning. Together, we'll work on gaining a deeper understanding of mathematical concepts, but also on becoming more organized, managing stress, and progressing independently.

👉 What I propose:

- Clear explanations adapted to your level

- Practical and structured exercises

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- Stress management and mental preparation before exams

- Regular and personalized monitoring

It's September, the start of the new school year: the perfect time to get off to a good start and give yourself the best possible chance. Getting support now will allow you to approach the year with confidence, with a solid foundation and an effective working method.

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verified badge
Engineer and senior professor of engineering sciences provides support courses in analog and digital electronics at all levels, engineering schools. having a scientific and technical knowledge, five years of experience in the field of teaching, teaching and a sense of listening and analysis, I am able to help pupils and students and train them in the chapters of which they have difficulties. for more info please contact me
verified badge
Python is one of the best, if not the best, language to start learning programming. It is also one of the most widely used languages today, especially in cutting-edge areas such as machine learning.

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As an aeronautical engineer, I like to share my knowledge and derive satisfaction from it by teaching and motivating others.

I'm used to working with people of different ages. I believe in the importance of segmenting learning, visualizing progress, setting concrete goals and practicing regularly.

Beyond these general principles, there is no magic rule or method. Some approaches work with some students but not with others. Adaptation to individual needs is therefore the main objective of private lessons. So I will do my best to find what motivates and helps my student.
verified badge
Don't settle for anything less than excellence.
I am an Aerospace Engineer with a Master's degree in Quantum Physics and have completed Ph.D. work at the University of Cambridge in Computational Physics. Additionally, I have 4 years of experience developing MATLAB and possess deep programming skills in MATLAB/Simulink family, C/C++, Fortran, and Python.

With over 12 years of tutoring experience, I have successfully guided more than 50 students worldwide to achieve distinction in various fields. Consistent results are my priority, and I strive for excellence in all aspects of my teaching.

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

Whether you are at a school level or require advanced or professional-level instruction, I offer support in the following areas:
- Preparation for IB/IA, A-Levels, GCSE, University Entry, or equivalent.
- Experience in preparing students to access world-class schools and universities, including Cambridge University, Oxford, Ivy League and other top institutions in the UK and US.
- University levels (undergraduate and postgraduate).
- High school studies and diploma programs.
- Assistance with specific projects at a professional level, including job interview preparation.
- Extensive experience working with children.

Every lesson is meticulously planned in advance to ensure that it aligns with your goals and targets areas for improvement.
I prioritize a dynamic and interactive learning experience, with one-on-one sessions tailored to your individual requirements. Lessons will be conducted via webcam, enabling you to connect from anywhere.

I have a highly flexible schedule and can adapt to accommodate your needs.
If you have any questions about my teaching method, availability, or pricing, please don't hesitate to reach out. I am here to assist you and provide the support you need.
verified badge
Python is a powerful and versatile programming language with countless possibilities. You can use it for data analysis, image processing, automation, software development, hardware control, and much more.

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Automate repetitive tasks?
Control or manage your own hardware?

Whether you are just starting to learn Python or already have a specific project and need some guidance, I would be happy to help you.

My goal is to explain things clearly, adapt to your level, and help you understand not only how to make something work, but also why it works.

Let's turn your ideas into working Python projects!
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Master Python with Personalized Courses

Discover the art of programming with Python courses tailor-made to meet your specific needs. Whether you are a beginner, intermediate or professional, my lessons are suitable for all levels.

Why Choose My Courses?

Personalized Teaching Approach: Each course is tailored to your skill level and individual goals.

Practical Experience: Learn by doing with real-world projects that build your understanding and skills.

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:

Start your journey to Python mastery now by booking your first lesson. Whether you aspire to enter the development field or hone your existing skills, these courses are designed for you.
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Learn the law through an academic, modern, and practical approach. Thanks to my university and professional experience, I help students understand legal concepts in depth, develop legal reasoning, and retake exams. The courses combine clear and applied explanations, legal methodology, and personal guidance. Thanks to my university and professional experience, I help students understand legal concepts deeply, develop legal reasoning, and retake exams. The courses combine clear and practical explanations, legal methodology, and personal guidance. Learn about law through an academic, modern, and practical approach. Thanks to my university and professional experience, I help students understand legal concepts deeply, develop legal reasoning, and retake exams. The courses combine clear and practical explanations, legal methodology, and personal guidance. Learn about law through an academic, modern, and practical approach. Thanks to my university and professional experience, I help students understand legal concepts deeply, develop legal reasoning, and retake exams. The courses combine clear and practical explanations, legal methodology, and personal guidance. Learn about law through an academic, modern, and practical approach. Thanks to my university and professional experience, I help students understand legal concepts deeply, develop legal reasoning, and retake exams. The courses combine clear and practical explanations, legal methodology, and personal guidance. Learn about law through an academic, modern, and practical approach. Thanks to my university and professional experience, I help students understand legal concepts deeply, develop legal reasoning, and retake exams. The courses combine clear and practical explanations, legal methodology, and personal guidance. Learn about law through an academic, modern, and practical approach. Thanks to my university and professional experience, I help students understand legal concepts deeply, develop legal reasoning, and retake exams. The courses combine clear and practical explanations, legal methodology, and personal guidance. Learn about law through an academic, modern, and practical approach. Thanks to my university and professional experience, I help students understand legal concepts deeply, develop legal reasoning, and retake exams. The courses combine clear and practical explanations, legal methodology, and personal guidance. Learn about law through an academic, modern, and practical approach. Thanks to my university and professional experience, I help students understand legal concepts deeply, develop legal reasoning, and retake exams. The courses combine clear and practical explanations, legal methodology, and personal guidance. Learn about law through an academic, modern, and practical approach. Thanks to my university and professional experience, I help students understand legal concepts deeply, develop legal reasoning, and retake exams. The courses combine clear and practical explanations, legal methodology, and personal guidance. Learn about law through an academic, modern, and practical approach. Thanks to my university and professional experience, I help students understand legal concepts deeply, develop legal reasoning, and retake exams. The courses combine clear and practical explanations, legal methodology, and personal guidance. Learn about law through an academic, modern, and practical approach. Thanks to my university and professional experience, I help students understand legal concepts deeply, develop legal reasoning, and retake exams. The courses combine clear and practical explanations, legal methodology, and personal guidance. Learn about law through an academic, modern, and practical approach. Thanks to my university and professional experience, I help students understand legal concepts deeply, develop legal reasoning, and retake exams. The courses combine clear and practical explanations, legal methodology, and personal guidance. Learn about law through an academic, modern, and practical approach. Thanks to my university and professional experience, I help students understand legal concepts in depth, develop legal reasoning, and retake exams. The courses combine clear and practical explanations, legal methodology, and personal guidance.
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I teach Python specifically for finance and data applications - the kind used in economics, business analytics, and quantitative programs. This isn't a general "learn to code" course; it's built around real financial data, benchmarking, and the workflows you'll actually use in coursework or early career work.

Topics include:
Python fundamentals through a finance lens (data structures, functions, control flow).
Working with financial data and datasets.
Performance benchmarking and writing efficient code.
Applying concepts from Hilpisch's Python for Finance.
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It is true that the philosopher is the friend of wisdom, but above all, he is someone who does not want to make mistakes in reasoning. Philosophizing is a way of reasoning and a way of solving problems that will never have a perfect and definitive solution. Knowing the distance between the Earth and the Moon is not a problem of philosophy, because it is enough to measure to solve it. On the other hand, knowing, for example, what justice is, is a problem of philosophy. A meter will not be able to help us know the answer. We must go about it differently, and in the courses I offer, I will teach you how.

You will learn

- text reading strategies
- case studies with the aim of learning from experts
- methodology in philosophy
- writing an essay
- writing a text commentary
- a work on the philosophers of your choice
- an overview of the history of philosophy
- the general culture necessary to be able to philosophize

I will adapt to your individual needs. Each course is tailor-made. We will analyze where your difficulties lie and together develop a course program that will make you perform as quickly as possible. The basic principle of the courses I offer is dialectics, like Plato's dialogues: reflecting together, making theoretical contributions, asking questions and seeking answers, and testing the validity of reasoning.

For the past 10 years, I have been teaching German using the philosophy methodology, having studied philosophy at the Master's level at Aix-Marseille University. It turns out that the analytical mind is very useful even outside the confines of philosophy. Today, there are even fields of activity such as management with philosophy or philotherapy. In recent years, some German students have asked me to also teach them philosophy courses, and that is why I decided to offer philosophy courses directly.

I look forward to meeting you during a first lesson.
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Python is today one of the most widely used programming languages in the world, both in Data Science, Artificial Intelligence, Web Development and for task automation.
In this course, I will guide you step by step according to your level:

Beginner: basics of the language (variables, loops, conditions, functions).

Intermediate: data manipulation (Pandas, NumPy), file management, object-oriented programming.

Advanced: practical projects (data analysis, machine learning, automation, API, web scraping).

My goal is to make learning clear, practical, and motivating. You'll not only learn how to code in Python, but also how to structure your projects and apply your knowledge to real-life scenarios.
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The authenticity of an exchange. In a society increasingly rooted in a competitive approach, where automated exchanges with Artificial Intelligence cannot replace the need for human interaction, this is precisely what we lack.
As a lawyer by training and an independent legal consultant, creating "Le Droit" is a breath of fresh air. This private tutoring program is aimed directly at high school students, undergraduate and graduate law students, and more generally at anyone intrigued by the beauty of legal language (you'll discover it soon enough).
Moreover, being currently preparing for the entrance exam to the National School of Magistrates, a solid mastery of legal fundamentals as well as the methods required in legal studies remains.

🎓 It is now necessary to elaborate somewhat on my experience:
- 4 years already dedicated to private lessons (which is significant) via the organization Complétude as well as independently (law, French, science, history and languages).
Regarding the law, and to clarify my point, the teaching that was provided covered and still covers a broad spectrum within the legal field, namely:
- Legal methodology (essential for success: legal essay, practical case study, case commentary and summary note)
- Civil Law (fundamental concepts, contract law, family law, tort law, property law, civil procedure, etc.)
- Criminal Law (fundamental concepts, special criminal law, criminal procedure, criminal law of property and business)
- Administrative Law (fundamental concepts, review of the vast body of existing case law on the subject)
- Labour Law (history of trade unionism, study of the employment contract)
- Public Law (Constitutional Law, Law of Local Authorities, Law of Social Welfare and Action, Constitutional Litigation)
- European Union Law (primary and secondary law, European Union litigation)
- The Law of English-speaking and Spanish-speaking countries
- ... and other subjects directly related to the program of the entrance examination to the National School of the Judiciary.

👋 What about my teaching approach, you might ask?
Beyond this desire for authenticity, it seems particularly crucial to dismantle the prejudices that poison the perception of legal studies. Law can then, and in my humble opinion must, be considered within the delicate balance between discipline and flexibility, between rigor and adaptability.

💬 Wouldn't you be interested?
Please feel free to contact me by message and I remain available to discuss the frequency of classes and their modalities (in-person in Tours, videoconference and possibility of travel if necessary).

In the meantime, Madam/Sir, it would be a real pleasure for me to support you as best I can on your path to success because, as its name suggests: you have the Right 😉
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Do you want your child to consolidate their learning and gain confidence during the school holidays?

I offer personalized private lessons for children aged 6 to 12, in a caring and motivating environment.

As a teacher for 20 years, I put my expertise at the service of each student.

To help your child consolidate their learning, regain confidence and start the new school year calmly.

Course objectives:

- Refresher and reinforcement of essential foundations in French, mathematics, Dutch and early learning.

- Acquisition of an effective work method (organization, memorization, understanding of instructions).

- Regain confidence and learn with pleasure!


My pedagogy:

A playful, structured and reassuring approach.

Content adapted to the pace and needs of each child.

Various tools: manipulations, educational games, visual aids and targeted exercises.

Holidays are the perfect time to learn in a different way, without pressure, and to start afresh on a good footing!

Feel free to contact me to discuss your child's needs and define a tailored support plan together.
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These courses are part of a structured and progressive training in Object-Oriented Programming (OOP) with JavaScript, designed for beginner or intermediate developers who want to understand in depth how the language works, write clearer, more maintainable code and prepare themselves calmly for modern frameworks like React ⚛️.

Object-Oriented Programming is often perceived as complex or abstract.

My goal is simple: to make it logical, concrete, and immediately applicable.

🎯 Training Objectives

Upon completion of this training, you will be able to:

Understanding what Object-Oriented Programming really is (and when to use it)
Create and manipulate objects in JavaScript in a clean and efficient way
Use ES6 classes, constructors, and methods with confidence
Mastering this, the prototype, and the instantiation logic
Apply encapsulation, inheritance, and polymorphism without confusion
Avoiding common mistakes made by OOP beginners
Structure your JavaScript code like a professional developer

📖 Training Plan – Object-Oriented Programming in JavaScript
1. Introduction to Object-Oriented Programming 🧠
Understanding the concept, objectives and benefits of OOP.
2. Procedural Programming vs. OOP
Why unstructured code quickly becomes unmanageable.
3. Objects in JavaScript
Properties, methods and representation of the real world.
4. The keyword this
Understanding the execution context (often poorly understood).
5. Limitations of simple objects
Why duplicating code is a bad idea.
6. Constructive functions
Create multiple objects from the same model.
7. The keyword new
What it's actually doing under the hood.
8. The prototype
Sharing methods and memory optimization.
9. ES6 Classes
Modern syntax and best practices.
10. The builder
Proper initialization of objects.
11. Data Encapsulation
Protect the internal state of objects.
12. Inheritance between classes
Reusing code intelligently.
13. The keyword super
Communication between parent and child in the classroom.
14. Polymorphism
The same behavior, several forms.
15. Composition vs. Inheritance
Choosing the right architecture.
16. Best practices in OOP
Write readable, scalable, and maintainable code.
17. Common mistakes made by beginners
Pitfalls to absolutely avoid.
18. Guided practical exercise
Creation of a concrete class (product, user, etc.).
19. Assessment Quiz (Multiple Choice Questions)
To validate the actual understanding of the concepts.

🛠️ Teaching method: Understand before writing

This training program is based on a progressive and pragmatic approach:
Clear and illustrated explanations
Concrete examples from real projects
Simple but effective exercises
Constant questioning to avoid rote learning
Adaptation to the learner's level and pace
Here, we don't "recite OOP" — we understand it.

🚀 Learner's result

At the end of the training, you will not only know how to write a JavaScript class.
You will know:

1- Why does it exist?
2- When to use it
3- and when not to use it

You will leave with:
a solid understanding of OOP
a cleaner and more professional code
an ideal foundation for learning React, Node.js or any other modern framework
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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.
Good-fit Instructor Guarantee
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