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Since February 2021
Instructor since February 2021
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Private lesson learning the python language.
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From 19 € /h
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The python programming language is used in a lot of applications, web, servers, video games, data analysis...
Whether it is to learn a language and get started in a project or for tutoring, I offer you as an independent developer and full stack developer student at Zone01 Rouen, a course to understand all the fundamentals of the Python language and OOP (object-oriented programming)
Location
location type icon
Online from France
About Me
I am a developer, with a real interest in back-end and software.
I offer my services in software development as well as as a programming tutor/teacher.
I registered on Apprentus so that I could share my knowledge while putting it to good use.
Education
Self-taught - I have been developing this skill, which is programming, since I was very young, before the age of 10.
-Lycée les Fontenelles in Louviers (Scientific and digital curriculum)
- Zone01 - FullStack Developer (Apprenticeship)
Experience / Qualifications
I have already given several private lessons but I want more than anything to improve myself in order to produce the best possible content for my lessons, for that I will be very grateful if you give me your opinions.

Besides my former and current students, I am currently a full-stac developer.
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
60 minutes
The class is taught in
French
English
Skills
Reviews
Availability of a typical week
(GMT -05:00)
Chicago
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
As a programmer and having already developed several games, notably for GameJams (video game creation competitions), and still currently working on a video game.

I offer support in the creation of your projects.
Whether it be:
- Introduction to video game creation
- Improvement
- Support for a particular game

To help with this process, access to a learning platform (De ma facture) is included, where you will find a written and summarized version of our courses and interviews as well as additional exercises to continue working between our courses.

Feel free to ask questions or request more details about the course offered, I will be happy to answer them!
Read more
Similar classes
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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.

This popularity means that Python is constantly evolving. It offers a wide range of tools and libraries, which are free and very varied.

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.
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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:
- 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
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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Hello,

My name is Hassane, and I've been passionate about computers for over 20 years. With two decades of teaching experience, I've had the privilege of supporting learners of all ages and levels in developing their computer skills and achieving their professional and personal goals.

Computer science is an essential skill today, opening the door to countless opportunities. Whether you want to learn programming, website design, data analysis, or complex problem-solving, I'm here to guide you every step of the way.

What I propose:
In my classes, we explore a wide range of topics to meet the needs of both beginners and advanced learners:

Computer fundamentals: master the basics to get started, Hardware, Software, Binary, Operating system.
Programming: learn to code efficiently in different languages (C#, Python, VBA).
Web development: creating modern websites and applications.
Databases: understanding, managing and analyzing data, UML, MERISE.
Project management: Ms-Project, Agil, Scrum, Kanban

Teaching methods:
I adopt a dynamic and interactive approach to ensure a rich and enjoyable learning experience:

Interactive courses: clear explanations adapted to your pace.
Practical exercises: to immediately apply the concepts learned.
Collaborative projects: developing real solutions as a team.
Personalized monitoring: answer your questions and support your progress.
Why choose me?
20 years of experience in computer teaching.
Proven methods suitable for all levels.
Personalized support to help you achieve your goals.
A passion for passing on skills that make a difference.
Whether you are a student, a professional looking to retrain, or simply curious, my courses will provide you with the tools you need to succeed in this rapidly evolving field.

Join me today!
Please contact me to learn more or to discuss your specific needs. Together, let's build your digital future.

Hassane
Experienced computer teacher and trainer
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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.
verified badge
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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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.
verified badge
Personalized support courses for final year NSI students wishing to prepare effectively for the Baccalaureate.

Goals :

quickly understand the important concepts,
improve algorithmic logic,
gaining confidence before exams
to correct difficulties in Python
practice with exercises adapted to the Baccalaureate level.

The course may include:

data structures,
databases,
recursion,
algorithms,
Python programming
examination methodology.

I favour a clear, simple and results-oriented approach in order to help the student progress quickly without unnecessary stress.

Courses available in French, English or Arabic.
verified badge
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.

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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Learn Python with a structured, hands-on approach! Whether you are a absolute beginner looking to start coding, a student needing help with coursework, or a professional aiming to automate tasks, these lessons are tailored for you.What we will cover:
Core Fundamentals: Variables, loops, functions, and data structures.Object-Oriented Programming: Building reusable and clean code.Real-World Projects: Creating scripts, data analysis, or web scraping based on your goals.

Problem Solving: Learning how to debug and think like a programmer. Lessons are highly interactive. We will write code together from day one, and you will receive practical exercises after every session to build your confidence.
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I work as a data consultant and hold a master's degree in Data Science and Statistics from UCLouvain. I use Python and data manipulation and analysis tools daily in a professional context.

I offer Python and data analysis courses for students, beginners and people wishing to develop practical skills in programming and data.

The lessons are tailored to your level and your goal. We can work on, among other things:

* the basics of Python and programming logic;
* variables, conditions, loops and functions;
* Data manipulation with Python and pandas;
* data cleaning and transformation;
* data exploration and visualization;
* applied statistics;
* solving practical exercises and projects;
* Understanding and debugging your code.

I prefer a practical approach: we start with a concrete problem or dataset, gradually build the solution, and analyze the errors encountered together.

The goal is to understand what you are doing rather than simply reproducing code, in order to gradually become self-reliant.

I can also support a project or student work by explaining the approach, the code and the methods used, without doing the work for you.
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Overview

Transitioning from learning data science theory to solving actual business problems is the hardest step for any aspiring data professional. [Insert Chosen Course Title] is an intensive, mentor-led program designed to simulate a real-world data team environment. Instead of working through synthetic, pre-cleaned textbook datasets, you will take on messy, complex industry scenarios and turn them into end-to-end data products.

What You’ll Experience

End-to-End Execution: Walk through the full data lifecycle—from problem scoping and data extraction to exploratory analysis, modeling, and executive stakeholder presentation.

Industry-Standard Workflows: Work with messy real-world datasets, practice Git-based version control, write production-ready code, and structure reports that business leaders actually care about.

1-on-1 & Group Mentorship: Receive continuous code reviews, architectural feedback, and project guidance mirroring the experience of working under a Senior Data Scientist or Analytics Lead.

Portfolio-Ready Deliverables: Graduate with 2–3 complete, polished projects that demonstrate actual business value to hiring managers—not just another churn prediction copy-pasted from Kaggle.

Who This Is For
Aspiring Data Analysts, Data Scientists, and recent graduates who know Python, but want the practical experience, confidence, and portfolio needed to land high-impact roles in the industry.
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This Python class is designed for anyone interested in learning programming, regardless of their previous experience or background.

You will learn Python from the basics, starting with variables, data types, operators, conditions, loops, functions, and data structures. As you progress, you will also learn how to work with files, handle errors, and build practical programs.

The class focuses on understanding programming concepts through simple explanations, examples, and hands-on practice. Whether you are a complete beginner, a student, a professional, or simply curious about coding, this class will help you build a strong foundation in Python programming.
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Python is one of the easiest and most in-demand programming languages in today's job market, used in artificial intelligence, data analysis, web development, and game development. As an IT teacher with experience in school teaching, I designed these lessons to be practical and interactive:

Programming basics (variables, conditions, loops)
Solve realistic exercises and small projects
A simplified approach perfectly suited for beginners with no prior experience.
Suitable for students who want support with their school curriculum (IGCSE/British/American) or anyone who wants to start programming from scratch
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Contact Simon
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1st lesson is backed
by our
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Similar classes
arrow icon previousarrow icon next
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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.

This popularity means that Python is constantly evolving. It offers a wide range of tools and libraries, which are free and very varied.

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
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
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!
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
Hello,

My name is Hassane, and I've been passionate about computers for over 20 years. With two decades of teaching experience, I've had the privilege of supporting learners of all ages and levels in developing their computer skills and achieving their professional and personal goals.

Computer science is an essential skill today, opening the door to countless opportunities. Whether you want to learn programming, website design, data analysis, or complex problem-solving, I'm here to guide you every step of the way.

What I propose:
In my classes, we explore a wide range of topics to meet the needs of both beginners and advanced learners:

Computer fundamentals: master the basics to get started, Hardware, Software, Binary, Operating system.
Programming: learn to code efficiently in different languages (C#, Python, VBA).
Web development: creating modern websites and applications.
Databases: understanding, managing and analyzing data, UML, MERISE.
Project management: Ms-Project, Agil, Scrum, Kanban

Teaching methods:
I adopt a dynamic and interactive approach to ensure a rich and enjoyable learning experience:

Interactive courses: clear explanations adapted to your pace.
Practical exercises: to immediately apply the concepts learned.
Collaborative projects: developing real solutions as a team.
Personalized monitoring: answer your questions and support your progress.
Why choose me?
20 years of experience in computer teaching.
Proven methods suitable for all levels.
Personalized support to help you achieve your goals.
A passion for passing on skills that make a difference.
Whether you are a student, a professional looking to retrain, or simply curious, my courses will provide you with the tools you need to succeed in this rapidly evolving field.

Join me today!
Please contact me to learn more or to discuss your specific needs. Together, let's build your digital future.

Hassane
Experienced computer teacher and trainer
verified badge
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.
verified badge
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.
verified badge
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.
verified badge
Personalized support courses for final year NSI students wishing to prepare effectively for the Baccalaureate.

Goals :

quickly understand the important concepts,
improve algorithmic logic,
gaining confidence before exams
to correct difficulties in Python
practice with exercises adapted to the Baccalaureate level.

The course may include:

data structures,
databases,
recursion,
algorithms,
Python programming
examination methodology.

I favour a clear, simple and results-oriented approach in order to help the student progress quickly without unnecessary stress.

Courses available in French, English or Arabic.
verified badge
A- TOPICS YOU CAN EXPLORE AND MASTER:
1- PYTHON FOUNDATIONS
• Variables, data types, operators, conditional structures, loops, functions, modules, files, exceptions, and object-oriented programming
• Lists, tuples, dictionaries, sets, comprehensions, debugging, and writing clear, reusable, well-structured code
• Jupyter Notebook, Anaconda, Visual Studio Code, virtual environments, and package management

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

My goal is not simply to help you run an algorithm. It is to help you understand why it is appropriate, how it learns from data, how to evaluate it correctly, why it may fail, and how to build a reliable, interpretable, and scientifically rigorous solution.
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Learn Python with a structured, hands-on approach! Whether you are a absolute beginner looking to start coding, a student needing help with coursework, or a professional aiming to automate tasks, these lessons are tailored for you.What we will cover:
Core Fundamentals: Variables, loops, functions, and data structures.Object-Oriented Programming: Building reusable and clean code.Real-World Projects: Creating scripts, data analysis, or web scraping based on your goals.

Problem Solving: Learning how to debug and think like a programmer. Lessons are highly interactive. We will write code together from day one, and you will receive practical exercises after every session to build your confidence.
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I work as a data consultant and hold a master's degree in Data Science and Statistics from UCLouvain. I use Python and data manipulation and analysis tools daily in a professional context.

I offer Python and data analysis courses for students, beginners and people wishing to develop practical skills in programming and data.

The lessons are tailored to your level and your goal. We can work on, among other things:

* the basics of Python and programming logic;
* variables, conditions, loops and functions;
* Data manipulation with Python and pandas;
* data cleaning and transformation;
* data exploration and visualization;
* applied statistics;
* solving practical exercises and projects;
* Understanding and debugging your code.

I prefer a practical approach: we start with a concrete problem or dataset, gradually build the solution, and analyze the errors encountered together.

The goal is to understand what you are doing rather than simply reproducing code, in order to gradually become self-reliant.

I can also support a project or student work by explaining the approach, the code and the methods used, without doing the work for you.
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Overview

Transitioning from learning data science theory to solving actual business problems is the hardest step for any aspiring data professional. [Insert Chosen Course Title] is an intensive, mentor-led program designed to simulate a real-world data team environment. Instead of working through synthetic, pre-cleaned textbook datasets, you will take on messy, complex industry scenarios and turn them into end-to-end data products.

What You’ll Experience

End-to-End Execution: Walk through the full data lifecycle—from problem scoping and data extraction to exploratory analysis, modeling, and executive stakeholder presentation.

Industry-Standard Workflows: Work with messy real-world datasets, practice Git-based version control, write production-ready code, and structure reports that business leaders actually care about.

1-on-1 & Group Mentorship: Receive continuous code reviews, architectural feedback, and project guidance mirroring the experience of working under a Senior Data Scientist or Analytics Lead.

Portfolio-Ready Deliverables: Graduate with 2–3 complete, polished projects that demonstrate actual business value to hiring managers—not just another churn prediction copy-pasted from Kaggle.

Who This Is For
Aspiring Data Analysts, Data Scientists, and recent graduates who know Python, but want the practical experience, confidence, and portfolio needed to land high-impact roles in the industry.
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This Python class is designed for anyone interested in learning programming, regardless of their previous experience or background.

You will learn Python from the basics, starting with variables, data types, operators, conditions, loops, functions, and data structures. As you progress, you will also learn how to work with files, handle errors, and build practical programs.

The class focuses on understanding programming concepts through simple explanations, examples, and hands-on practice. Whether you are a complete beginner, a student, a professional, or simply curious about coding, this class will help you build a strong foundation in Python programming.
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Python is one of the easiest and most in-demand programming languages in today's job market, used in artificial intelligence, data analysis, web development, and game development. As an IT teacher with experience in school teaching, I designed these lessons to be practical and interactive:

Programming basics (variables, conditions, loops)
Solve realistic exercises and small projects
A simplified approach perfectly suited for beginners with no prior experience.
Suitable for students who want support with their school curriculum (IGCSE/British/American) or anyone who wants to start programming from scratch
Good-fit Instructor Guarantee
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