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Since September 2026
Instructor since September 2026
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Computer Programming: Fullstack Developer (Java, Python, Node JS) & AI (LLM, ChatGPT, Claude, etc.) | Web (HTML, React, Vue, etc.)
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From 54 $ /h
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Experienced Web & AI Developer: creation of your custom applications and websites and programming courses.

The following questions:
- Do you have a digital idea or project you'd like to bring to life? (Perhaps a small e-commerce website, a WhatsApp-style chat application)
- Do you want to create your own platform or learn to code at your own pace with a professional?
Are you looking for someone to hire to create your dream solution?
- Do you want a mobile | web | desktop application?
Are you looking for a developer for a permanent contract or freelance work?
- Private lessons for Web/Mobile apps?

Me:
As a freelance software engineer, I offer my technical expertise to individuals, project leaders, creators, and very small businesses. A patient, responsive, and attentive communicator, I support you from design to deployment.

1. DEVELOPMENT OF YOUR CUSTOM PROJECTS
I design modern, fast, mobile-friendly, and secure solutions. Here are some examples of possible solutions:

- E-commerce & Online Sales Platforms: creation of complete stores (catalog, shopping cart, secure Stripe/CB payment, stock and order management, customer area).
- Instant messaging & Chat applications: development of WhatsApp/Messenger type applications (real-time messaging, document sharing, statuses, live notifications).
- Custom AI Assistants & Chatbots: integration of artificial intelligences (like ChatGPT/Claude) trained on your own documents or configured to automatically respond to your customers, sort requests or automate your daily tasks.
- Business tools and private portals: booking platforms, online calendars, interactive dashboards or automation tools.
- Maintenance & Evolution: graphic redesign, addition of new features or resolution of bugs on your existing projects.

Development pricing:
- Freelance: €350 - €520 excluding VAT / day (or turnkey package on quote after review of your specifications).
- Permanent contract: 3700 Euros / month in Paris, minimum 2-year contract (after review of your duties).

2. PRIVATE PROGRAMMING LESSONS & COACHING FOR YOU OR YOUR LOVED ONES
Whether you are a complete beginner with no prior knowledge, a computer science student preparing for exams, or undergoing career retraining, I offer practical and personalized courses:

- Frontend Web Development: HTML5, CSS3, modern JavaScript, React.js to design dynamic and attractive web interfaces.
- Server & Backend Development: Node.js (with Express), Python, Java to learn how to create APIs, manage requests and manipulate databases (SQL, MongoDB).
- Artificial Intelligence & Automation: introduction to Python for AI, use of AI APIs, data processing.
- Practical support: help with your personal projects, getting unstuck with school/university assignments, preparation for technical interviews.

WHY ENTRUST ME WITH YOUR PROJECT?
- Clear approach: simple explanations, without unnecessary jargon.
- Complete expertise: mastery of the entire chain (design, code, server, security, online deployment).
- Security & Data: strict adherence to security and confidentiality standards (GDPR).
- Trust & Clarity: transparent framing of deadlines and costs.

LEGAL INFORMATION & BILLING

- Service declared with systematic delivery of a professional invoice.
Extra information
Laptop requires a minimum of 32 GB of RAM and a 512 GB SSD.
Powerful processor (equivalent to at least i7 7th generation).
Have a good internet connection
Location
location type icon
Online from France
About Me
Full-stack engineer specializing in the end-to-end delivery of critical solutions for the international market (Africa,
Europe, USA, Canada). Mastering a highly versatile ecosystem combining server architectures
distributed enterprise, native integration of Artificial Intelligence (LLM, RAG) and modern client interfaces.
Focused on technological innovation for 2026+, ensuring architectural resilience, updates, the
Application security (IAM, encryption), compliance (GDPR, AI Act), observability (DevOps) and analytics
Engineering to reduce operational costs and maximize business value.
Education
Master's in Data Marketing & AI | HETIC School 2023 - 2025
Paris, France
Initial coursework during the day. Activity at DeepSquare maintained with staggered/evening hours.
• Key skills acquired: Statistical modeling, Deep Learning, Natural Language Processing (NLP), pipelines
large-scale data and business valuation strategies for AI algorithms.
Master's Degree in Software Engineering | ESPITA University 2021 - 2023
Sousse, Tunisia
Higher education course completed entirely through evening classes, alongside my position at DeepSquare.
• Key skills acquired: Design patterns, microservices-oriented distributed architectures,
agile methodologies (Scrum), and codebase quality and maintainability management (SOLID/DRY).
Bachelor's Degree in Robotics & IoT | EPM Tunis 2020 - 2021
Tunis, Tunisia
• Key skills acquired: Low-level programming of microcontrollers (Arduino, Raspberry Pi), simulation and validation
Hardware under ModelSim, integration of automated systems and industrial mechatronics.
Bachelor's Degree in Computer Networks & Security | UPS University 2017 - 2020
Sousse, Tunisia
• Key skills acquired: Advanced administration of Linux/Unix system architectures, implementation and security of
network protocols, software security auditing and fundamental principles of cryptography.
Experience / Qualifications
Fullstack Software Engineer, AI & DevOps - Senior | DeepSquare (IT Services Company) 06/2021 - Present
Tunisia (On-site until 2023) then Remote from Paris, France. Full-time / Long-term collaboration
Development, architecture and deployment of critical software solutions for various international clients.
Design of complete infrastructures (Web, Mobile, Desktop, Backend, Cloud, AI, Security):
- Ryvo-Line (01/2026 - Ongoing) - Canada: Cross-platform ride-hailing service (Alternative to Uber)
Missions:
• Fullstack & Cloud architecture:
- Implementation of the client system on Web (Next JS) and Mobile/Desktop (Flutter).
- Backend design via Supabase and Node JS Functions with strict access control (RBAC).
- Third-party integrations: Google Maps SDK, Stripe & Paypal payments.
• DevOps & Infrastructure:
- Distributed architecture deployed on Linux via Docker Compose.
- Event stream management (Queue) with Kafka and Cache via Redis. AWS S3 storage.
- CI/CD pipelines via GitHub Actions on AWS EC2.
• Security & Observability:
- AWS IAM implementation, JWT/SSL/TLS protocols.
- Monitoring and observability of the infrastructure via Prometheus and Grafana.
• AI & Data Engineering:
- Integration of a customer service managed by multimodal AI agents (Chat & Voice) using LiveKit (STT + VAD + LLM)
+ TTS) in Python.
- Implementation of Data pipelines (DBT / Snowflake) for AI-powered automated processing and intelligent recall of
customer suggestions/promotions.
• Data Viz: Implementation of dashboards for data visualization for analytics with Next JS interface.
Techs: Jira, Photoshop, Figma/Canva, Next JS, Flutter, iOS Swift, Kotlin Jetpack Compose, Supabase with PostgreSQL/SQL, Rust (
Actix Web), Node JS Functions, Python with FastAPI REST API, GitHub Actions, Gitlab, Terraform/Kubernetes/Docker, AWS EC2/S3,
Kafka, Redis, LLM(Gemini), LiteLLM, LiveKit/WebRTC/Websocket, Stripe/Paypal API, Prometheus/Grafana, DBT/Snowflake, PowerBI.
Age
Adults (18-64 years old)
Seniors (65+ years old)
Student level
Beginner
Intermediate
Advanced
Duration
60 minutes
The class is taught in
French
English
German
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
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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
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• Loss functions, gradients, distance measures, regularization, likelihood, and model complexity
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• k-nearest neighbours, decision trees, random forests, gradient boosting, support vector machines, and Naive Bayes classifiers
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6- UNSUPERVISED LEARNING
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• Method selection, evaluation of data structure, and interpretation of results without predefined labels

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• 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

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11- TOOLS AND LIBRARIES
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• 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
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-------------------------------------------------------------------------------------------------------------------------------------------------------------------------------
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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.

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Hello,

I am 26 years experienced Online Tutor and Assignment Helper for Computer Science. I teach PHP, MySQL, Python, Machine Learning, Programming in C, C++, Java, ASP, C#.NET, Visual Basic, Oracle, HTML, VBScript, JavaScript, Data Structures, JQuery, Bootstrap , MS Office. I have teaching experience of teaching IT Professionals , students from different grades, graduate and post graduate classes for more than 22 years.

Presently I am teaching students online, providing homework assignment help, provide help in online tests for the students from USA ,UK, Canada, New Zealand, Germany, Australia, Malaysia, Austria, Malta, Saudi Arab etc. Also, I am in Software Development and Web Designing. I have helped more than 1200 students from different countries in last 26 years.

Regarding my teaching methodology, I always start teaching the concepts right from the scratch so that the students can learn concepts easily. I would like to describe you how do I teach through Internet . There is 100 % interaction between me and my students using Internet.

For starting the lessons with me all that you need is PC with Internet Connection and Headphone and Mic. Rest I will guide you about everything when you start learning with me. My lessons are also customized, planned and prepared according to the needs of individual student. I can also provide old student references if the student needs that.


If you join the course with me, I assure you that it will be value for your time and money.


Thanks
Harry
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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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Description:
This course is ideal for beginners or intermediate learners who want to learn programming using languages like C#, Java, or Python. With a step-by-step approach, you'll be guided from basic algorithms to object-oriented programming.

Goals :

Introduction to algorithms and their implementation.
Master the basics of C#, Java, and Python languages.
Understand the concepts of classes, objects, and error management.
Course methods and format:

Video lessons: Clear explanations and practical exercises.
Flexibility: Personalized support to meet your expectations.
For who ?
Students or professionals starting out in programming, or preparing for exams.
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This course is designed to introduce students aged 7 to 16 to the world of programming through two of the most widely used and industry-relevant languages: C++ and Python.

The class provides a structured, age-appropriate pathway into programming, whether the student is a complete beginner or already exploring coding through platforms like Scratch or Code.org. Emphasis is placed on understanding logic, building problem-solving skills, and writing real code in a supportive, project-based environment.

Taught by an engineering student with hands-on experience in both C++ and Python, this course empowers students to explore the power of code and build a strong foundation in computational thinking — essential for future studies in engineering, robotics, AI, or game development.
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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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This course is for anyone who wants to learn to program in Python, whether you are a student, a professional, or simply curious.
Python is one of the most widely used languages today, thanks to its simplicity and power. You'll learn how to write your first programs, manipulate data, automate tasks, and understand the essential foundations of modern programming.
The objective is to make you independent in developing your own projects (scripts, small software, data analysis, etc.) and acquire a skill sought after in the academic and professional world.
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PhD Candidate in Informatics – Private Lessons & Pancyprian Exams

I am a PhD Candidate in Informatics and I offer private lessons in Informatics to High School students (Pancyprian Exams) as well as to University students, with an emphasis on correct understanding and methodical thinking.

Pancyprian Exams – Informatics

Systematic preparation with an emphasis on:
• understanding of the material
• correct algorithmic thinking
• methodology for solving problems
• analysis of old Pancyprian exam questions

We cover, for example: pseudocode, tables, repetitions, control structures and common exam errors.

Students & General Computing

Support in:
• Programming (C / C++ / Python)
• Operating Systems
• Computer Architecture
• Code Understanding & Debugging

In-person or online courses, with emphasis on understanding and proper study organization.

English text below

PhD Candidate in Computer Science – Private Tutoring & Pancyprian Exams

I am a PhD candidate in Computer Science offering private tutoring for high school students (Pancyprian Exams – Computer Science) and university students.

Pancyprian Exams – Computer Science

Structured exam preparation focusing on:
• understanding the syllabus
• correct algorithmic thinking
• exam-oriented problem-solving
• analysis of past Pancyprian exams

Topics include pseudocode, arrays, loops, control structures, and common exam mistakes.

University & General Computer Science

Support in:
Programming (C/C++/Python)
• Operating Systems
• Computer Architecture
• Code understanding and debugging

Lessons are available in person or online, with emphasis on understanding concepts rather than memorization.
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These courses are part of a structured and progressive training in Object-Oriented Programming (OOP) with JavaScript, designed for beginner or intermediate developers who want to understand in depth how the language works, write clearer, more maintainable code and prepare themselves calmly for modern frameworks like React ⚛️.

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

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

🎯 Training Objectives

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

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

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

🛠️ Teaching method: Understand before writing

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

🚀 Learner's result

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

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

You will leave with:
a solid understanding of OOP
a cleaner and more professional code
an ideal foundation for learning React, Node.js or any other modern framework
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A- TOPICS YOU CAN EXPLORE AND MASTER:
1- PYTHON FOUNDATIONS
• Variables, data types, operators, conditional structures, loops, functions, modules, files, exceptions, and object-oriented programming
• Lists, tuples, dictionaries, sets, comprehensions, debugging, and writing clear, reusable, well-structured code
• Jupyter Notebook, Anaconda, Visual Studio Code, virtual environments, and package management

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

My goal is not simply to help you run an algorithm. It is to help you understand why it is appropriate, how it learns from data, how to evaluate it correctly, why it may fail, and how to build a reliable, interpretable, and scientifically rigorous solution.
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I'm a working MEP engineer, currently building Python automation for Revit workflows daily - plan checks, model coordination, and repetitive drafting tasks. I teach other engineers, architects, and BIM professionals how to do the same, using pyRevit and real project workflows, not toy examples.

Topics include:
pyRevit fundamentals and setup
Automating repetitive Revit tasks (model checks, plan generation, data extraction)
Writing custom scripts for your firm's specific workflows
Applying Python automation to real MEP/BIM projects
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Professeur agrégé de informatique, j’aide élèves et étudiants à réussir examens et concours. J’interviens aux classes préparatoires (MPSI, MP, PSI, ECS...) et jusqu’à l’université (Licence & Master en sciences ou économie). Ma méthode : comprendre le cours, pratiquer avec rigueur, structurer le raisonnement et ha des exercices et problèmes bien choisis. Chaque séance inclut exercices ciblés, conseils méthodologiques, et suivi personnalisé. Vous recevez un enregistrement vidéo plus un PDF annoté après chaque cours. Cours en ligne via Google Meet, 5 jours sur 7, avec flexibilité horaire. Je reste joignable entre les séances pour répondre aux questions. Contactez-moi pour un premier échange.
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