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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 46 € /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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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
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• 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

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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
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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 — 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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This course is designed for students and adolescents who want to build a strong beginner-friendly foundation in Computer Science.
Whether you're completely new to Computer Science or need help with a specific programming subject, the course can be customized to match your needs.
Need help with C++ or programming? You can provide me with your syllabus, course outline, or the topics you're studying, and I'll tailor the lessons around what you need to learn.
Learning with friends? Group lessons are also available, allowing you to learn together while following the same customized course.
Good-fit Instructor Guarantee
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Contact Ivan Joel