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Since June 2026
Instructor since June 2026
Learn Logic, Strategy, and Problem-Solving Through Programming
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From 164 C$ /h
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In this class, students will learn how to think clearly, solve problems step by step, and approach challenges with confidence through coding.

Many students struggle not because a problem is too hard, but because they do not know how to break it down. This class teaches students how to take large, confusing problems and divide them into smaller, manageable pieces. Using programming as the main learning tool, students will practice logic, planning, pattern recognition, debugging, and structured problem-solving.

Students do not need to be advanced coders to benefit from this class. The focus is not just on writing code, but on learning how to think like a problem solver. Each lesson will guide students through practical coding exercises that teach them how to ask better questions, organize their ideas, test solutions, fix mistakes, and build confidence when facing difficult tasks.

By the end of the class, students will have a stronger foundation in coding and, more importantly, a practical way to approach problems in school, technology, and everyday life.

Students will learn how to:

Break large problems into smaller steps
Think logically and organize ideas clearly
Use coding to practice problem-solving
Recognize patterns and build efficient solutions
Debug mistakes without getting frustrated
Develop confidence when facing unfamiliar challenges
Apply structured thinking beyond programming

Ideal for:
Beginners and students who want to improve their coding, logic, math confidence, and overall problem-solving skills.
Location
location type icon
Online from United States
Age
Children (7-12 years old)
Teenagers (13-17 years old)
Student level
Beginner
Intermediate
Advanced
Duration
60 minutes
The class is taught in
English
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
In this class, students will learn how to use PowerShell and Bash scripting to automate tasks, solve technical problems, and become more confident working from the command line.

PowerShell and Bash are two of the most useful scripting tools in technology. PowerShell is widely used in Windows environments, Microsoft 365, Azure, and IT administration, while Bash is commonly used in Linux, macOS, servers, cloud systems, cybersecurity, and DevOps. Learning both gives students a strong foundation for real-world technology work.

This course focuses on practical scripting, not just memorizing commands. Students will learn how to break down repetitive or complex tasks into clear steps, write scripts to automate those steps, troubleshoot errors, and understand how computers process commands. Each lesson will include hands-on examples that build real problem-solving skills.

Students do not need to be advanced programmers to benefit from this class. The course is designed to help beginners and developing technical students become comfortable with command-line tools, scripting logic, variables, loops, conditions, files, folders, permissions, processes, and automation workflows.

By the end of the class, students will understand how to write useful PowerShell and Bash scripts, automate common tasks, and approach technical problems with a structured mindset.

Students Will Learn How To
Use the command line confidently in Windows, Linux, and macOS environments
Write beginner-friendly PowerShell and Bash scripts
Understand variables, conditions, loops, functions, and parameters
Automate repetitive computer and administrative tasks
Work with files, folders, permissions, processes, and system information
Read, filter, and manipulate text output from commands
Troubleshoot scripts and fix common errors
Break technical problems into smaller, scriptable steps
Use scripting as a foundation for IT, cybersecurity, cloud, and DevOps skills
Build practical scripts that can be used in real-world scenarios
Ideal For

This class is ideal for beginners, students interested in IT or cybersecurity, aspiring system administrators, future DevOps or cloud engineers, and anyone who wants to learn how to automate computer tasks using PowerShell and Bash.

No advanced coding experience is required. Students should be comfortable using a computer and willing to practice hands-on scripting exercises.
Read more
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Most kids think coding is for "smart kids" or "future programmers."
It's not. Coding is how real people solve real problems.
In this class, we skip the theory. Your child creates real things.

What they'll do:
✓ Build real projects in Scratch: a working game, an interactive animation, a story they coded
✓ Program virtual robots: solve real-world challenges (navigate a maze, automate a task, build a system)
✓ Create in Minecraft Education: design worlds, automate constructions, solve logic problems
✓ Experiment with different languages: not just learn "the right way," but understand that there are many ways to think about a problem
✓ Collaborate and share: work with other kids, get feedback, improve their work
✓ Develop logical thinking: not just for coding, but for anything: solving math problems, science challenges, real-world situations


Why this is different:
We don't teach syntax. We teach how programmers think.
Most children's coding courses say "here's the code, copy it." We teach "what problem are we trying to solve? How could we break it into steps? What options do we have?"
When your child learns to think like a programmer, they can learn any language afterward.

What they take home:
A portfolio of 3–4 completed, working projects. The ability to say "I built this." And the deep understanding that code is a tool to make real things happen.

Format: Online or Barcelona | 60–90 min sessions | Flexible pace, no prior experience needed
For curious 8-12 year olds who want to build.
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With 7 years of experience as a developer in a Factory, I now develop Wordpress websites for large groups.

In the training program, you will learn to:

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doctoral student in engineering sciences provides support courses in analog and digital electronics at any DEUG level and engineering schools. having scientific and technical knowledge, three years of experience in the field of teaching, pedagogy and a sense of listening and analysis, I am able to help pupils and students and train them in the chapters of which they are having difficulty. for more info please contact me
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Are you a university student, engineer, or professional who needs to actually use data — not just learn theory about it?
This course is built around real problems and real code. We skip the textbook formulas and go straight to applying statistics and data science the way professionals do: with Python (pandas, NumPy, scikit-learn, matplotlib) and R (RStudio).
What we cover, adapted to your level and goals:
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- Time series and forecasting basics
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You will learn Systematic Reasoning & Logical Thinking which is a requirement for entering Computer Science program in many universities.
The book “Delftse Foundations of Computation” especially its second chapter will be the main source of our lesson, but other more in-depth books will be also covered if you want to improve even further on logical thinking.
The topics in our lesson include:
• Propositional Logic: Logical operators; Precedence rules; Logical equivalence; Implications in English; Exclusive or; Universal operators; Classifying propositions
• Boolean Algebra: Substitution laws
• Logic Circuits: Logic gates; Combining gates to create circuits; From circuits to propositions; Disjunctive Normal Form; Binary addition.
• Predicate Logic: Predicates; Quantifiers; Tarski’s world and formal structures;
• Deduction: Valid arguments and proofs; Proofs in predicate logic

If you have any additional questions before starting a class, please feel free to ask me. I am here to assist! :)
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Master Python with Personalized Courses

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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:

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Discover programming lessons suitable for children! With a fun and educational approach, my lessons allow young minds to dive into the fascinating world of programming. Provide your children with an enriching learning opportunity in a fun and stimulating environment.
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Experienced and patient teacher of logic for computer science.

I have taught logic, formal languages and automata theory to undergraduates for six years. My tutoring is adapted to the student's level and goals. Whether you need to learn logic for your studies, or you would simply like to know more about the subject, I will be more than happy to help you improve your understanding and skills.

Logic
The sciences presuppose a certain standard of rationality. An ability to distinguish between correct reasoning and claims that do not follow from the assumptions. In this class we study the basic principles of logic and apply mathematical techniques to the study thereof.
Topics include:
Propositional and Predicate Logic
Syntax and semantics
Natural deduction
Semantic tableaux
Correctness and soundness
Completeness

Formal languages and automata
A formal language is an abstraction of general characteristics of programming languages. Such a languages consists of a set of symbols together with some rules to determine whether a string made up out of those symbols is a member of the language.

Topics include:
Regular languages, context-free languages
Finite automata, pushdown automata, Turing machines
Regular expressions
Regular grammar, context-sensitive grammar
Pumping lemmas for regular and context-free languages
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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.

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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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Do you dream of creating your own website but don't know where to start? 🙋‍♂️🙋‍♀️ This course is for you! This private tutoring program is designed for beginners, students, or professionals changing careers who want to master the essential basics of website creation. 📚

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HTML5: Structuring the content of a web page in a clean and semantic way.
CSS3: Style your pages, manage layout (Flexbox, Grid) and create responsive designs adapted to mobile devices.
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Practical Projects: Create your own projects from A to Z to build your portfolio.

💡 My 100% Personalized Methodology: The pace adapts completely to your strengths and difficulties.
Practical: 20% theory to 80% live coding and concrete exercises.
Continuous Monitoring: Sharing of resources, answer keys and mini-challenges between sessions.

See you soon to create your first website together! 😄👨‍🏫👩‍🏫
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This course shows students how AI is the engine behind modern video games. It’s an engaging, project-based track ideal for advanced concepts in a fun, relatable environment.

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Generative Assets: Learning how game studios use generative AI tools to rapidly create textures, background stories, or simple game environments.

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SEN Alignment: The visual and immediate feedback loop of game design environments is highly effective for kinetic learners and helps maintain focus.
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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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I offer one-to-one Programming tuition in Python, C, and C++, for GCSE Computer Science, A-Level Computing, and university students studying engineering, computer science, or related subjects. Lessons are available online or in person around Birmingham.

What I cover:

Python for beginners and intermediate learners
C and C++ programming
GCSE and A-Level Computer Science (all exam boards)
University coursework support, debugging help, and project guidance
Core concepts: variables, loops, functions, data structures, object-oriented programming, file handling, basic algorithms

How I teach:
I start by understanding exactly where you are — whether that's "I've never coded before" or "I'm stuck on a specific assignment." Then I build lessons around small, practical examples you can actually run and modify yourself. I'm patient with errors (everyone gets them), and I make sure you understand the why behind the code, not just how to copy it. For university students, I can also help with debugging, code reviews, and explaining tricky concepts in plain English.
If you or your child is preparing for exams, working on coursework, or just wants to finally feel comfortable with coding, I'd love to help.
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Do you want to learn to program or discover software development?
I offer programming courses focused on the essential basics of development with Python, one of the most widely used languages today.
In the program :
- Variables and data types;
- Conditions and loops;
- The functions;
- Data structures;
- The basics of object-oriented programming;
- Practical exercises and small projects.
The courses are suitable for students, secondary school students and adults wishing to acquire skills in computer development.
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A- SUJETS QUE VOUS POUVEZ EXPLORER ET MAÎTRISER :

1- FONDEMENTS DE PYTHON
• Variables, types de données, opérateurs, structures conditionnelles, boucles, fonctions, modules, fichiers, exceptions et programmation orientée objet
• Listes, tuples, dictionnaires, ensembles, compréhensions, débogage et écriture d’un code clair, réutilisable et bien structuré
• Jupyter Notebook, Anaconda, Visual Studio Code, environnements virtuels et gestion des packages

2- PRÉPARATION ET EXPLORATION DES DONNÉES
• NumPy et pandas pour importer, nettoyer, transformer, filtrer, regrouper, restructurer et fusionner les données
• Valeurs manquantes, doublons, valeurs aberrantes, formats incohérents, fuite de données (data leakage) et validation de la qualité des données
• Analyse exploratoire des données à l’aide de statistiques descriptives, Matplotlib, Seaborn et interprétation graphique

3- FONDEMENTS MATHÉMATIQUES
• Algèbre linéaire, vecteurs, matrices, dérivées, optimisation, probabilités et statistiques
• Fonctions de perte, gradients, mesures de distance, régularisation, vraisemblance et complexité des modèles
• Les concepts mathématiques sont expliqués en fonction du niveau de l’apprenant et des exigences des algorithmes sélectionnés

4- APPRENTISSAGE AUTOMATIQUE SUPERVISÉ
• Régression linéaire et polynomiale, régression logistique et modèles régularisés
• k plus proches voisins (k-nearest neighbours), arbres de décision, forêts aléatoires, gradient boosting, machines à vecteurs de support et classificateur naïf de Bayes
• Classification, régression, hypothèses des modèles, frontières de décision, importance des variables et interprétation des résultats

5- APPRENTISSAGE NON SUPERVISÉ
• Regroupement (clustering) par k-means, classification hiérarchique et méthodes fondées sur la densité
• Analyse en composantes principales, réduction de dimensionnalité, détection d’anomalies et découverte de structures ou de motifs
• Sélection des méthodes, évaluation de la structure des données et interprétation des résultats sans étiquettes prédéfinies

6- ÉVALUATION ET AMÉLIORATION DES MODÈLES
• Jeux d’entraînement, de validation et de test ; validation croisée ; optimisation des hyperparamètres
• Exactitude (accuracy), précision, rappel (recall), spécificité, score F1, ROC–AUC, matrices de confusion, MAE, MSE, RMSE et R2
• Sous-apprentissage, surapprentissage, compromis biais–variance, déséquilibre des classes, ingénierie des variables, sélection des variables, mise à l’échelle et régularisation

7- APPRENTISSAGE PROFOND
• Fondements des réseaux de neurones, fonctions d’activation, propagation avant, rétropropagation et descente de gradient
• Perceptrons multicouches, réseaux de neurones convolutifs, réseaux récurrents et fondements des Transformers
• TensorFlow, Keras ou PyTorch selon le projet et l’environnement de travail de l’apprenant

8- APPLICATIONS DE L’INTELLIGENCE ARTIFICIELLE
• Traitement automatique du langage naturel, classification de textes, plongements vectoriels (embeddings), analyse de sentiments et fondements des modèles de langage
• Vision par ordinateur, classification d’images, principes fondamentaux de la détection d’objets et prétraitement des images
• Systèmes de recommandation, prévision, détection d’anomalies, automatisation intelligente et applications d’aide à la décision

9- IA GÉNÉRATIVE ET GRANDS MODÈLES DE LANGAGE
• Architecture Transformer, tokens, embeddings, mécanismes d’attention, ingénierie des prompts, génération augmentée par récupération (Retrieval-Augmented Generation – RAG) et évaluation des modèles
• Utilisation d’API d’intelligence artificielle, de bases de données vectorielles, de systèmes de recherche documentaire et de flux de travail structurés utilisant l’IA lorsque cela est pertinent
• Fiabilité, hallucinations, biais, confidentialité, utilisation responsable et validation humaine appropriée

10- OUTILS ET BIBLIOTHÈQUES
• Python, NumPy, pandas, Matplotlib, Seaborn, scikit-learn, SciPy, Statsmodels, TensorFlow, Keras et PyTorch
• Jupyter Notebook, Anaconda, Visual Studio Code, Git, GitHub, SQL, Excel et Power BI lorsqu’ils sont utiles au projet
• Des bibliothèques supplémentaires peuvent être introduites en fonction de la spécialisation choisie et du jeu de données utilisé

11- PROJETS, RECHERCHE ET PRÉPARATION AUX ENTRETIENS
• Projets complets couvrant la préparation des données, le développement des modèles, leur évaluation, leur interprétation et la présentation des résultats
• Travaux universitaires, mémoires, thèses, projets de recherche, projets de portfolio, entretiens techniques et applications professionnelles
• Revue de code, débogage, documentation, reproductibilité, comparaison de modèles et communication des résultats

B- TUTORAT PERSONNALISÉ : APPRENDRE À RAISONNER
L’apprentissage automatique et l’intelligence artificielle deviennent beaucoup plus accessibles lorsque les mathématiques, les algorithmes, le code Python, les données et les applications concrètes sont clairement reliés entre eux.

Mes cours vous aident à aller au-delà de la simple copie de code ou de l’utilisation de modèles comme des « boîtes noires ». Vous apprendrez à définir correctement le problème, préparer les données, sélectionner un algorithme approprié, comprendre son fonctionnement, entraîner et évaluer le modèle, diagnostiquer les erreurs, améliorer ses performances et interpréter les résultats de manière rigoureuse et responsable.

Chaque cours est personnalisé en fonction de votre niveau actuel, de vos connaissances mathématiques, de votre expérience en programmation, de votre jeu de données, de votre travail universitaire, de votre projet de recherche, de votre préparation à un entretien ou de votre objectif professionnel. Nous commençons par identifier vos connaissances existantes, votre environnement logiciel, les résultats attendus ainsi que vos principales difficultés conceptuelles ou techniques. Nous établissons ensuite un plan d’apprentissage structuré.

Le premier cours gratuit combine une discussion portant sur votre parcours, vos objectifs et vos besoins en tutorat, une première évaluation de vos connaissances actuelles, une planification et une organisation personnalisées des séances, ainsi qu’un court cours d’essai afin de déterminer la méthode de travail la plus efficace.

Une séance type peut comprendre une explication conceptuelle, le développement de l’intuition mathématique, de la programmation en direct, une mise en œuvre guidée, l’évaluation des modèles, la résolution de problèmes techniques et une synthèse concise des prochaines étapes.

Vous pouvez travailler avec votre propre jeu de données, travail universitaire, projet de recherche ou problématique professionnelle, à condition que les informations confidentielles soient traitées de manière appropriée. Je peux également fournir des exemples structurés et des jeux de données adaptés à votre niveau.

Mon objectif n’est pas simplement de vous aider à exécuter un algorithme. Il est de vous permettre de comprendre pourquoi il est approprié, comment il apprend à partir des données, comment l’évaluer correctement, pourquoi il peut échouer et comment construire une solution fiable, interprétable et scientifiquement rigoureuse.
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Most kids think coding is for "smart kids" or "future programmers."
It's not. Coding is how real people solve real problems.
In this class, we skip the theory. Your child creates real things.

What they'll do:
✓ Build real projects in Scratch: a working game, an interactive animation, a story they coded
✓ Program virtual robots: solve real-world challenges (navigate a maze, automate a task, build a system)
✓ Create in Minecraft Education: design worlds, automate constructions, solve logic problems
✓ Experiment with different languages: not just learn "the right way," but understand that there are many ways to think about a problem
✓ Collaborate and share: work with other kids, get feedback, improve their work
✓ Develop logical thinking: not just for coding, but for anything: solving math problems, science challenges, real-world situations


Why this is different:
We don't teach syntax. We teach how programmers think.
Most children's coding courses say "here's the code, copy it." We teach "what problem are we trying to solve? How could we break it into steps? What options do we have?"
When your child learns to think like a programmer, they can learn any language afterward.

What they take home:
A portfolio of 3–4 completed, working projects. The ability to say "I built this." And the deep understanding that code is a tool to make real things happen.

Format: Online or Barcelona | 60–90 min sessions | Flexible pace, no prior experience needed
For curious 8-12 year olds who want to build.
verified badge
With 7 years of experience as a developer in a Factory, I now develop Wordpress websites for large groups.

In the training program, you will learn to:

- Install, configure, and deploy WordPress sites
- Develop custom Wordpress themes and plugins
- Use powerful tools like ACF Pro, Gravity Forms, WPML, AIOS Security, WP rocket...
- Create custom post types and tailor-made taxonomies
- Develop pages using the right methods in HTML, CSS, Javascript & PHP
- Administer and manage a site database
- Contribute to the good natural referencing (SEO) of your site
- Use WP-Cli to speed up the maintenance of your sites
- Use Docker to containerize your local/prod projects and facilitate their management
- Administer your WP sites the right way
- And much more...

For any questions, you can contact me by PM.

See you soon,
Matthew
verified badge
doctoral student in engineering sciences provides support courses in analog and digital electronics at any DEUG level and engineering schools. having scientific and technical knowledge, three years of experience in the field of teaching, pedagogy and a sense of listening and analysis, I am able to help pupils and students and train them in the chapters of which they are having difficulty. for more info please contact me
verified badge
Are you a university student, engineer, or professional who needs to actually use data — not just learn theory about it?
This course is built around real problems and real code. We skip the textbook formulas and go straight to applying statistics and data science the way professionals do: with Python (pandas, NumPy, scikit-learn, matplotlib) and R (RStudio).
What we cover, adapted to your level and goals:
- Descriptive and inferential statistics (the ones that actually matter)
- Data cleaning, exploration, and visualization
- Regression, classification, and intro to machine learning
- Time series and forecasting basics
- R for statistical analysis and academic research

Who this is for:
- University students in statistics, economics, engineering, or biology
- Professionals wanting to move into data analysis or data science
- Researchers who need to process and present data properly

I use Python and R professionally as a working engineer — everything I teach comes from real application, not just academic exercises.
verified badge
You will learn Systematic Reasoning & Logical Thinking which is a requirement for entering Computer Science program in many universities.
The book “Delftse Foundations of Computation” especially its second chapter will be the main source of our lesson, but other more in-depth books will be also covered if you want to improve even further on logical thinking.
The topics in our lesson include:
• Propositional Logic: Logical operators; Precedence rules; Logical equivalence; Implications in English; Exclusive or; Universal operators; Classifying propositions
• Boolean Algebra: Substitution laws
• Logic Circuits: Logic gates; Combining gates to create circuits; From circuits to propositions; Disjunctive Normal Form; Binary addition.
• Predicate Logic: Predicates; Quantifiers; Tarski’s world and formal structures;
• Deduction: Valid arguments and proofs; Proofs in predicate logic

If you have any additional questions before starting a class, please feel free to ask me. I am here to assist! :)
verified badge
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.
verified badge
Discover programming lessons suitable for children! With a fun and educational approach, my lessons allow young minds to dive into the fascinating world of programming. Provide your children with an enriching learning opportunity in a fun and stimulating environment.
verified badge
Experienced and patient teacher of logic for computer science.

I have taught logic, formal languages and automata theory to undergraduates for six years. My tutoring is adapted to the student's level and goals. Whether you need to learn logic for your studies, or you would simply like to know more about the subject, I will be more than happy to help you improve your understanding and skills.

Logic
The sciences presuppose a certain standard of rationality. An ability to distinguish between correct reasoning and claims that do not follow from the assumptions. In this class we study the basic principles of logic and apply mathematical techniques to the study thereof.
Topics include:
Propositional and Predicate Logic
Syntax and semantics
Natural deduction
Semantic tableaux
Correctness and soundness
Completeness

Formal languages and automata
A formal language is an abstraction of general characteristics of programming languages. Such a languages consists of a set of symbols together with some rules to determine whether a string made up out of those symbols is a member of the language.

Topics include:
Regular languages, context-free languages
Finite automata, pushdown automata, Turing machines
Regular expressions
Regular grammar, context-sensitive grammar
Pumping lemmas for regular and context-free languages
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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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Do you dream of creating your own website but don't know where to start? 🙋‍♂️🙋‍♀️ This course is for you! This private tutoring program is designed for beginners, students, or professionals changing careers who want to master the essential basics of website creation. 📚

The Coaching Program includes:
HTML5: Structuring the content of a web page in a clean and semantic way.
CSS3: Style your pages, manage layout (Flexbox, Grid) and create responsive designs adapted to mobile devices.
JavaScript: Make your sites dynamic, manage user interactions (buttons, forms) and manipulate the DOM.
Practical Projects: Create your own projects from A to Z to build your portfolio.

💡 My 100% Personalized Methodology: The pace adapts completely to your strengths and difficulties.
Practical: 20% theory to 80% live coding and concrete exercises.
Continuous Monitoring: Sharing of resources, answer keys and mini-challenges between sessions.

See you soon to create your first website together! 😄👨‍🏫👩‍🏫
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This course shows students how AI is the engine behind modern video games. It’s an engaging, project-based track ideal for advanced concepts in a fun, relatable environment.

Behavioral AI: Using simple visual programming environments (like Scratch or similar platforms) to program smarter Non-Player Characters (NPCs) that react realistically to the player's actions.

Generative Assets: Learning how game studios use generative AI tools to rapidly create textures, background stories, or simple game environments.

Interactive Storytelling: Exploring decision-tree logic and how AI can adapt game narratives based on player choices, making the game feel dynamic and intelligent.

SEN Alignment: The visual and immediate feedback loop of game design environments is highly effective for kinetic learners and helps maintain focus.
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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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I offer one-to-one Programming tuition in Python, C, and C++, for GCSE Computer Science, A-Level Computing, and university students studying engineering, computer science, or related subjects. Lessons are available online or in person around Birmingham.

What I cover:

Python for beginners and intermediate learners
C and C++ programming
GCSE and A-Level Computer Science (all exam boards)
University coursework support, debugging help, and project guidance
Core concepts: variables, loops, functions, data structures, object-oriented programming, file handling, basic algorithms

How I teach:
I start by understanding exactly where you are — whether that's "I've never coded before" or "I'm stuck on a specific assignment." Then I build lessons around small, practical examples you can actually run and modify yourself. I'm patient with errors (everyone gets them), and I make sure you understand the why behind the code, not just how to copy it. For university students, I can also help with debugging, code reviews, and explaining tricky concepts in plain English.
If you or your child is preparing for exams, working on coursework, or just wants to finally feel comfortable with coding, I'd love to help.
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Do you want to learn to program or discover software development?
I offer programming courses focused on the essential basics of development with Python, one of the most widely used languages today.
In the program :
- Variables and data types;
- Conditions and loops;
- The functions;
- Data structures;
- The basics of object-oriented programming;
- Practical exercises and small projects.
The courses are suitable for students, secondary school students and adults wishing to acquire skills in computer development.
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A- SUJETS QUE VOUS POUVEZ EXPLORER ET MAÎTRISER :

1- FONDEMENTS DE PYTHON
• Variables, types de données, opérateurs, structures conditionnelles, boucles, fonctions, modules, fichiers, exceptions et programmation orientée objet
• Listes, tuples, dictionnaires, ensembles, compréhensions, débogage et écriture d’un code clair, réutilisable et bien structuré
• Jupyter Notebook, Anaconda, Visual Studio Code, environnements virtuels et gestion des packages

2- PRÉPARATION ET EXPLORATION DES DONNÉES
• NumPy et pandas pour importer, nettoyer, transformer, filtrer, regrouper, restructurer et fusionner les données
• Valeurs manquantes, doublons, valeurs aberrantes, formats incohérents, fuite de données (data leakage) et validation de la qualité des données
• Analyse exploratoire des données à l’aide de statistiques descriptives, Matplotlib, Seaborn et interprétation graphique

3- FONDEMENTS MATHÉMATIQUES
• Algèbre linéaire, vecteurs, matrices, dérivées, optimisation, probabilités et statistiques
• Fonctions de perte, gradients, mesures de distance, régularisation, vraisemblance et complexité des modèles
• Les concepts mathématiques sont expliqués en fonction du niveau de l’apprenant et des exigences des algorithmes sélectionnés

4- APPRENTISSAGE AUTOMATIQUE SUPERVISÉ
• Régression linéaire et polynomiale, régression logistique et modèles régularisés
• k plus proches voisins (k-nearest neighbours), arbres de décision, forêts aléatoires, gradient boosting, machines à vecteurs de support et classificateur naïf de Bayes
• Classification, régression, hypothèses des modèles, frontières de décision, importance des variables et interprétation des résultats

5- APPRENTISSAGE NON SUPERVISÉ
• Regroupement (clustering) par k-means, classification hiérarchique et méthodes fondées sur la densité
• Analyse en composantes principales, réduction de dimensionnalité, détection d’anomalies et découverte de structures ou de motifs
• Sélection des méthodes, évaluation de la structure des données et interprétation des résultats sans étiquettes prédéfinies

6- ÉVALUATION ET AMÉLIORATION DES MODÈLES
• Jeux d’entraînement, de validation et de test ; validation croisée ; optimisation des hyperparamètres
• Exactitude (accuracy), précision, rappel (recall), spécificité, score F1, ROC–AUC, matrices de confusion, MAE, MSE, RMSE et R2
• Sous-apprentissage, surapprentissage, compromis biais–variance, déséquilibre des classes, ingénierie des variables, sélection des variables, mise à l’échelle et régularisation

7- APPRENTISSAGE PROFOND
• Fondements des réseaux de neurones, fonctions d’activation, propagation avant, rétropropagation et descente de gradient
• Perceptrons multicouches, réseaux de neurones convolutifs, réseaux récurrents et fondements des Transformers
• TensorFlow, Keras ou PyTorch selon le projet et l’environnement de travail de l’apprenant

8- APPLICATIONS DE L’INTELLIGENCE ARTIFICIELLE
• Traitement automatique du langage naturel, classification de textes, plongements vectoriels (embeddings), analyse de sentiments et fondements des modèles de langage
• Vision par ordinateur, classification d’images, principes fondamentaux de la détection d’objets et prétraitement des images
• Systèmes de recommandation, prévision, détection d’anomalies, automatisation intelligente et applications d’aide à la décision

9- IA GÉNÉRATIVE ET GRANDS MODÈLES DE LANGAGE
• Architecture Transformer, tokens, embeddings, mécanismes d’attention, ingénierie des prompts, génération augmentée par récupération (Retrieval-Augmented Generation – RAG) et évaluation des modèles
• Utilisation d’API d’intelligence artificielle, de bases de données vectorielles, de systèmes de recherche documentaire et de flux de travail structurés utilisant l’IA lorsque cela est pertinent
• Fiabilité, hallucinations, biais, confidentialité, utilisation responsable et validation humaine appropriée

10- OUTILS ET BIBLIOTHÈQUES
• Python, NumPy, pandas, Matplotlib, Seaborn, scikit-learn, SciPy, Statsmodels, TensorFlow, Keras et PyTorch
• Jupyter Notebook, Anaconda, Visual Studio Code, Git, GitHub, SQL, Excel et Power BI lorsqu’ils sont utiles au projet
• Des bibliothèques supplémentaires peuvent être introduites en fonction de la spécialisation choisie et du jeu de données utilisé

11- PROJETS, RECHERCHE ET PRÉPARATION AUX ENTRETIENS
• Projets complets couvrant la préparation des données, le développement des modèles, leur évaluation, leur interprétation et la présentation des résultats
• Travaux universitaires, mémoires, thèses, projets de recherche, projets de portfolio, entretiens techniques et applications professionnelles
• Revue de code, débogage, documentation, reproductibilité, comparaison de modèles et communication des résultats

B- TUTORAT PERSONNALISÉ : APPRENDRE À RAISONNER
L’apprentissage automatique et l’intelligence artificielle deviennent beaucoup plus accessibles lorsque les mathématiques, les algorithmes, le code Python, les données et les applications concrètes sont clairement reliés entre eux.

Mes cours vous aident à aller au-delà de la simple copie de code ou de l’utilisation de modèles comme des « boîtes noires ». Vous apprendrez à définir correctement le problème, préparer les données, sélectionner un algorithme approprié, comprendre son fonctionnement, entraîner et évaluer le modèle, diagnostiquer les erreurs, améliorer ses performances et interpréter les résultats de manière rigoureuse et responsable.

Chaque cours est personnalisé en fonction de votre niveau actuel, de vos connaissances mathématiques, de votre expérience en programmation, de votre jeu de données, de votre travail universitaire, de votre projet de recherche, de votre préparation à un entretien ou de votre objectif professionnel. Nous commençons par identifier vos connaissances existantes, votre environnement logiciel, les résultats attendus ainsi que vos principales difficultés conceptuelles ou techniques. Nous établissons ensuite un plan d’apprentissage structuré.

Le premier cours gratuit combine une discussion portant sur votre parcours, vos objectifs et vos besoins en tutorat, une première évaluation de vos connaissances actuelles, une planification et une organisation personnalisées des séances, ainsi qu’un court cours d’essai afin de déterminer la méthode de travail la plus efficace.

Une séance type peut comprendre une explication conceptuelle, le développement de l’intuition mathématique, de la programmation en direct, une mise en œuvre guidée, l’évaluation des modèles, la résolution de problèmes techniques et une synthèse concise des prochaines étapes.

Vous pouvez travailler avec votre propre jeu de données, travail universitaire, projet de recherche ou problématique professionnelle, à condition que les informations confidentielles soient traitées de manière appropriée. Je peux également fournir des exemples structurés et des jeux de données adaptés à votre niveau.

Mon objectif n’est pas simplement de vous aider à exécuter un algorithme. Il est de vous permettre de comprendre pourquoi il est approprié, comment il apprend à partir des données, comment l’évaluer correctement, pourquoi il peut échouer et comment construire une solution fiable, interprétable et scientifiquement rigoureuse.
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