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Learn Object-Oriented Programming in JavaScript 🧠⚙️
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From 33 C$ /h
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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
Extra information
i️ Practical information

Prerequisite:
JavaScript basics (variables, functions, conditions)

Necessary material :
💻 Computer with web browser
🧑‍💻 Code editor (Visual Studio Code recommended)
🎧 Microphone + webcam
🌐 Stable internet connection
Location
location type icon
Online from Algeria
About Me
Hi! I'm Farouk, from Algiers, Algeria 🇩🇿. I'm naturally curious and passionate about learning—especially when it comes to HTML, CSS, and JavaScript 💻✨. Right now, I'm focused on creating courses that are both effective and engaging, with a strong emphasis on pedagogy 📚🎯.

In my free time, I love to read 📖, play video games 🎮, travel ✈️, and cook 🍳. I'm always looking for new ways to grow—both personally and professionally 🚀🌱. I'm motivated, open-minded, and always ready to take on new challenges 💪🧠.

Looking forward to learning and sharing with you! 🤝😊
Education
1. Informal Training – State-accredited center, Algiers 🇩🇿
2008
Certificate of internship in dynamic website creation: HTML, CSS, JavaScript, PHP, MySQL 💻
Computer training applied to web development.

2. Houari Boumediene University of Science and Technology (USTHB) – Algiers
2004 - 2005
Common Core in Electronic Sciences and Computer Technology 🧠⚙️

3. Yahya Ould El Turki High School – Bou Ismaïl
2001 - 2002
Baccalaureate – Scientific stream with honors ✅🔬
Experience / Qualifications
Mentor – Since 2021 🎓

Supporting students in various academic paths:

• Web Developer
• Web Integrator
• Application Developer – JavaScript / React

Main responsibilities:

1- Personalized educational support

2- Project review and feedback

3- Technical and methodological coaching

4- Assistance in preparing for technical interviews


Freelance – Since 2015 💼

Platforms: Upwork, Fiverr, Comeup

• Creation of static and dynamic websites
• Responsive integration (HTML/CSS/JavaScript)
• Maintenance and optimization of web projects
• Collaboration with international clients
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
30 minutes
45 minutes
60 minutes
90 minutes
120 minutes
The class is taught in
French
Arabic
English
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 module is a crucial step for any web developer wishing to move from simple DOM manipulation to mastering modern frameworks. The objective is clear: to understand the "invisible foundations" of the language in order to write shorter, more readable code and, above all, be ready to code professionally in React.

🎯 Training Objectives

1- Demystify the modern syntax (ES6+) often used in React.
2- Increase efficiency by using the most powerful syntactic shortcuts.
3- Secure your code to avoid frequent bugs related to missing data.
4- Mastering asynchronicity to manage data calls (API).

📖 Detailed program content

The course is divided into 13 key concepts, illustrated by comparative examples (classic syntax vs. modern syntax) and concrete use cases in React:

1- Ease of writing: Use of Template Literals (`backticks`) for dynamic character strings and Shorthand property names to simplify the creation of objects.

2- Logic and Functions: Mastery of Arrow => Functions (arrow functions) and their implicit return, essential for React components and hooks.

Data manipulation:

1- Destructuring (decomposition) to properly extract data from objects and arrays (e.g., Props and States).

2- Rest & Spread Operators (...) to copy arrays or merge objects without modifying the original (concept of immutability).

Code robustness:

1- Managing default parameter values.

2- Advanced security with Optional Chaining (?.) and Nullish Coalescing (??) to prevent application crashes.

3- Functional Programming: Intensive use of array methods (.map(), .filter(), .reduce(), .find()) to transform data into user interfaces.

4- Architecture and Asynchronism: Code organization via modules (Import/Export) and API request management with Promises and Async/Await.

🛠️ Teaching method: "Learning by doing"

This course is not just about theory. It includes:

The "Interstellar Dashboard" Exercise: A 15-minute thematic case study where students manipulate data from space missions. This allows them to immediately apply destructuring, filtering, and asynchronicity to a real-world project.

The Interactive Quiz: A series of 10 questions designed to validate understanding of each concept before moving on. Each question presents real-world scenarios that developers will encounter in React.

🚀 Learner's result

By the end of this course, students will not only "know" JavaScript; they will understand why and how each syntax is used to build efficient React components. They will leave with a solid foundation to confidently tackle Hooks (useState, useEffect) and complex state management.

Format: Clean visual presentation, coloured syntax for code, and focus on readability.
Read more
These courses are part of a practical and accessible introductory training course in web development 🌐💻, designed for those who want to learn how to create a website from A to Z.
Using fundamental web technologies—HTML 🧱, CSS 🎨, and JavaScript ⚙️—you'll learn how to structure pages, style them, and make them interactive.

My teaching approach is hands-on: each concept is accompanied by concrete examples and progressive exercises to consolidate your knowledge. You'll discover how to build a responsive interface 📱💡, manage user events 🖱️, and apply simple animations ✨ to improve the user experience.

Whether you are a beginner or looking to consolidate your foundations, this training will guide you step by step towards autonomy in creating your own web projects 🚀

Training plan in 10 modules:

1. Introduction to programming 🧠💡
Understand the basics: logic, Linux commands, simple instructions and algorithms.

2. Introduction to HTML 🧱📄
Structure of a web page, main tags, links, images, tables, forms.

3. Accessibility and SEO ♿🔍
Create inclusive and well-referenced sites: semantic tags, ARIA attributes, good SEO practices.

4. Introduction to CSS 🎨🖌️
Formatting, colors, typography, boxes, flexbox and responsive layout.

5. Git & GitHub 🗂️⚙️
Version your code and collaborate effectively: Git commands, creating repositories, push/pull, pull requests.

6. JavaScript - Data Types 🔢📝
Numbers, strings, booleans, objects, arrays... Learn to manipulate data.

7. JavaScript - Functions and Methods ⚙️🧩
Define and call functions, understand scope, use native methods.

8. JavaScript - Terms ❓🔁
Master the if, else, switch statements to handle specific cases.

9. JavaScript - Arrays and Loops 🔄📊
Iterate efficiently with for, while, forEach, manipulate arrays like a pro.

10. DOM Manipulation & Closures 🌐✨
Edit HTML/CSS from JS, add events, understand closures for advanced interactions.
Read more
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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- 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

3- 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

4- 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

5- 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

6- MODEL EVALUATION AND IMPROVEMENT
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• TensorFlow, Keras, or PyTorch depending on the learner’s project and working environment

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• Computer vision, image classification, fundamental principles of object detection, and image preprocessing
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• Jupyter Notebook, Anaconda, Visual Studio Code, Git, GitHub, SQL, Excel, and Power BI when useful to the project
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11- PROJECTS, RESEARCH, AND INTERVIEW PREPARATION
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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.

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Teaching python to beginners!

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I have experience in teaching python to university peers.
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Are you studying Web Development, Computer Engineering, or other technology-related fields and need help with web development?

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* application deployment;
* Development of internships and complete projects.

We can also work with the specific technologies, frameworks, or tools you are using in your training or project.

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In addition to the classes, you will have access to our educational platform with its own documentation, notes, examples, exercises, practices and other resources to continue working between sessions.
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What we can cover depending on your goals:

Python fundamentals: variables, loops, functions, data structures
- Object-oriented programming (OOP)
- Data manipulation with pandas and NumPy
- Introduction to machine learning with scikit-learn
- Database management with SQL
- C and Java upon request
- MATLAB and R available for engineering/science students

Why learn with me?
I'm not a student teaching on the side — I'm a professional engineer who uses Python daily for data analysis, modeling, and automation. I know exactly which concepts matter in the real world and which ones you can skip for now.
Sessions are 100% personalized: I adapt the pace, the examples, and the exercises to your background and your goal — whether that's passing your university exam, building a project, or landing a job.
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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.
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* This digital training aims to introduce you to the Scratch tool and through the game world, and gradually, to discover programming concepts such as loops, conditions or variables. It is aimed at anyone who is new to Scratch and who wants to create games and animations.

* Learning programming will allow students to develop their skills and will certainly allow them to meet the expectations of the future working world and emerging careers.

* In addition, learning programming allows the development of algebraic, algorithmic and computational thinking. Programming also helps to improve and develop students' sequencing ability, as well as their communication skills. Thus, there are several advantages to teaching programming, but the important thing is to remember that this learning teaches students that digital is not only for entertainment, but that it is possible to become creators. active and creative content.
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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.

Do you want to create your own software?
Work with data or images?
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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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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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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Private Programming Lessons for you / your family / your company employees
Programming Tutor – IGCSE & Computer Science Subjects
Deeper understanding, stronger results

• Lecturer at the American University AUC
• Over 20 years of experience in training students for government employees, oil companies (BP), food companies (Nestle), banks (CIB), and telecommunications companies (Vodafone).

• Teaching curricula, syllabuses, courses:
o IGCSE (Computer Science 0478, ICT 0417)
o Programming and computer courses for all educational levels (from primary to university)
o Microsoft Windows, Word, Excel, PowerPoint, Outlook, MS-Project
o Programming, C, C++, VB.NET, C#, Python, Database, SQL, MQL, VBA
o HTML, CSS, JavaScript, Angular
o Different database systems
o Data analysis using Excel
o Computer and Information Colleges Curricula
o Using artificial intelligence in life and work

• Master office applications to improve your job performance.
• Prepare yourself to work as a Front-End / Back-End / Full Stack Developer
• Theoretical and practical training for market requirements
• Don't miss out on technology. Lessons are designed for the elderly, in a simple and understandable way (use of computers and their programs, use of mobile phones, dealing with the Internet and social media).
• Lessons are available in person or online.
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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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Бажаєш навчитися будувати власні розумні пристрої, зчитувати дані з датчиків та програмувати апаратне забезпечення? У цьому курсі ми поринемо у світ вбудованих систем (Embedded Systems).

Що ти вивчиш:

- Основи електроніки та проєктування схем.

- Програмування Arduino, ESP32 та STM32 на C/C++.

- Підключення датчиків (температури, звуку, руху) та виконавчих механізмів.

Практична реалізація: крок за кроком ми розроблятимемо твої власні проєкти у сферах робототехніки та IoT (інтернету речей).
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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- 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

3- 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

4- 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

5- 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

6- 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

7- 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

8- 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

9- 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

10- 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

11- 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.

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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Teaching python to beginners!

In these classes, you will learn the basics of python programming, functions, lists, sets, and much more with practice assignments and assessments...

I have experience in teaching python to university peers.
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Are you studying Web Development, Computer Engineering, or other technology-related fields and need help with web development?

The classes are online, one-on-one, and fully tailored to your syllabus, level, and goals. We can start from scratch, prepare for a subject or exam, solve practice problems, work on an assignment, or progress with a complete project.

We can work on content such as:

* HTML and CSS;
* JavaScript and client-side programming;
* PHP and backend development;
* frontend and backend;
* forms, sessions and authentication;
* consumption and creation of REST APIs;
* connection to databases and SQL;
* organization and architecture of web applications;
* Git and version control;
* debugging and error resolution;
* Frameworks and libraries according to your subject;
* application deployment;
* Development of internships and complete projects.

We can also work with the specific technologies, frameworks, or tools you are using in your training or project.

The classes are primarily hands-on. We'll analyze the problem, propose a solution, and work through the code so you understand what's happening and why.

My goal is not for you to copy a solution, but for you to develop the autonomy to analyze errors, organize an application, and tackle new problems on your own.

In addition to the classes, you will have access to our educational platform with its own documentation, notes, examples, exercises, practices and other resources to continue working between sessions.
Good-fit Instructor Guarantee
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