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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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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.

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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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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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While adults are still debating whether kids should use AI, they are already using it. The question isn't "should they?" it's "how do we do it intelligently?" In this course, your child will discover: ✓ What AI actually is: not magic, not mystery. How machines think, what they can do, what they can't ✓ How ChatGPT really works: not just "ask a question and get an answer," but why it responds that way, where it fails, when to trust it ✓ What LLMs are (Large Language Models): in language they understand, not tech jargon ✓ Create with AI: custom avatars, interactive stories, real projects using real tools ✓ Think critically about AI: Bias, privacy, creativity. What does AI do better than humans? What can't it do? ✓ Real-world applications: How AI transforms medicine, education, art, gaming, everyday life Why this is different: Most AI courses for kids teach "here's the tool, use it." I teach how to think about AI. Your child will learn to see AI not as black magic or a solution to everything, but as a powerful tool with real limits. And, more importantly: that they can control how they use it. What they take home: Real projects they created (custom avatar, interactive app, analysis of a real AI case study). A genuine understanding of how it works. And the ability to use AI responsibly and creatively. Format: Online | 60–90 min sessions | Flexible, adapted to their age and pace For curious kids asking "How does ChatGPT actually know things?"

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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 ------------------------------------------------------------------------------------------------------------------------------------------------------------------------------- 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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Engineer and senior professor of engineering sciences provides support courses in analog and digital electronics at all levels, engineering schools. having a scientific and technical knowledge, five years of experience in the field of teaching, teaching and a sense of listening and analysis, I am able to help pupils and students and train them in the chapters of which they have difficulties. for more info please contact me

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doctoral student in engineering sciences provides support courses in analog and digital electronics at any DEUG level and engineering schools. having scientific and technical knowledge, three years of experience in the field of teaching, pedagogy and a sense of listening and analysis, I am able to help pupils and students and train them in the chapters of which they are having difficulty. for more info please contact me

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I am a certified computer science professor who helps graduates and students with exam retakes and competitions. I tutor preparatory classes (MPSI, MP, PSI, ECS, etc.) up to university level (Bachelor's & Master's in Science or Economics). My method is based on understanding the lessons, practicing correctly, organizing the concepts, and completing exercises and problems of your choice. Each session includes verbal exercises, methodological tips, and subsequent personalized advice. You will receive a video recording and an annotation in PDF format after each session. The online courses are conducted via Google Meet, 5 days a week, with flexible scheduling. I am available between sessions to answer questions. Contact me for an initial consultation.

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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.

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Primary School Teacher. I offer personalized guidance in developing lesson plans and learning activities adapted to current educational regulations. During our sessions, you will learn to structure and write a complete lesson plan, including specific competencies, assessment criteria, core knowledge, methodology, addressing diversity, evaluation, and learning situations. My goal is to help you understand each section so you can independently develop a coherent, rigorous, and high-quality lesson plan. You will learn to design practical, creative proposals, developing the necessary skills to apply them in the classroom or in competitive examination processes.

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🐍 Python Course – Learn to code and create your projects! This course is for anyone who wants to: ✅ Learn Python from the beginning ✅ Strengthen their programming skills 📚 On the program: Variables Loops Functions Data structures Practical projects for implementation 💡 How does the course work? Clear explanations to understand the programming logic Targeted exercises adapted to your level Concrete projects to create your own applications 🎯 My goal: Helping you understand the logic behind the code Progress at your own pace Create your own projects in Python and gain independence

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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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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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This computer science support course is designed for students and learners wishing to strengthen their foundations or improve their level in computer science and programming. I support participants in a pedagogical and progressive manner, adapting to their level and objectives (university courses, training, practical work, exams, projects). The goal is to understand, practice and gain autonomy through clear explanations and concrete examples.

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🚀 Want to become a web development expert? Join my courses to learn how to master MERN and MEAN stacks, the modern technologies used by leading companies to develop robust and scalable web applications. I am a Full-Stack developer with several years of experience building web applications using MERN (MongoDB, Express, React, Node.js) and MEAN (MongoDB, Express, Angular, Node.js) technologies. I will guide you through practical projects and fundamental concepts to enable you to become a successful, independent developer. The training program includes: MERN Stack: - Introduction to MongoDB, Express, React, Node.js - Creation of RESTful APIs with Express and Node.js - Integration of NoSQL databases with MongoDB - Front-end development with React (hooks, state management, routing) - Authentication and session management with JWT - Deployment of MERN applications on services like Heroku, Netlify, or AWS MEAN Stack: - Discovery of Angular and its concepts (directives, services, modules, etc.) - Using Express to develop RESTful APIs - Connection with MongoDB and data management - Development of dynamic interfaces with Angular - Integration of web development best practices

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With 7 years of experience as a developer in a Factory, I now develop Wordpress websites for large groups. In the training program, you will learn to: - Install, configure, and deploy WordPress sites - Develop custom Wordpress themes and plugins - Use powerful tools like ACF Pro, Gravity Forms, WPML, AIOS Security, WP rocket... - Create custom post types and tailor-made taxonomies - Develop pages using the right methods in HTML, CSS, Javascript & PHP - Administer and manage a site database - Contribute to the good natural referencing (SEO) of your site - Use WP-Cli to speed up the maintenance of your sites - Use Docker to containerize your local/prod projects and facilitate their management - Administer your WP sites the right way - And much more... For any questions, you can contact me by PM. See you soon, Matthew

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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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Python is a simple, powerful, and versatile programming language, ideal for beginners looking to learn or change careers in computer science. This course will help you understand the basics of programming (variables, loops, conditions, functions) through practical, hands-on exercises. You'll learn how to create your first scripts, manipulate data, and automate simple tasks. All in an accessible, interactive, and practical setting. This course is aimed at anyone who is a beginner, curious about digital technology, or who wishes to develop skills useful in many professional sectors.

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Understanding algorithms is essential for anyone pursuing computer science or programming. In this course, I provide a structured approach to learning algorithms—from fundamental concepts like sorting and searching to advanced techniques such as dynamic programming and graph theory. Whether you're preparing for exams, coding interviews, or aiming to improve your problem-solving skills, this course is designed to build strong algorithmic thinking. Through practical examples and step-by-step explanations, I help students master the logic and techniques needed to write efficient and elegant code.

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I created this course especially for students having difficulty progressing in their computer programming courses/projects. I support students of all university levels. My help covers many others: - Analysis and planning of projects - Technological choice in languages and tools/framework - Algorithmic and programming support - Assistance with debugging and code correction - Data modeling (MCD/MLD diagram, UML diagrams) Why choose my courses? My method is different and more adapted than that of traditional teachers because it is: * Personalized: Adapted to your level and your specific needs. * Interactive: Promotes interaction and visualization of concepts. * Practical: Oriented towards practice with concrete exercises and projects. * Proven: I have already managed to help more than 200 students in the space of 2 years.

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I teach machine learning, AI and Python online to university students, postgraduates, career changers and serious beginners across the UK and Europe. Lessons are in English. I hold an MSc in Electronics and Electrical Engineering with Distinction and I teach as a Visiting Lecturer on a Master's level module covering data analytics, machine learning and generative AI at a UK university. I also have two accepted international conference papers on deep learning for image classification. I set and mark postgraduate assignments myself, so I know where marks are won and lost on this kind of work. Who this is for Undergraduates and postgraduates on AI, ML, data science or computer science modules at any European university. Final year, Master's and thesis students working on a machine learning project. IB and A Level students moving into computing or engineering. Professionals retraining for data roles. Complete beginners who want to learn Python properly rather than copying it from videos. I work with students on UK, IB and continental European programmes. I have tutored engineering students in Germany and international school students across several countries, so an unfamiliar syllabus or a module taught in a different structure is not a problem. Send me the material and I will work from it. What we cover Python for data science with NumPy, Pandas, Matplotlib and scikit-learn. Deep learning using TensorFlow and Keras. Core theory including regression, classification, clustering, decision trees, random forests, neural networks and CNNs, together with the linear algebra, calculus and statistics underneath them. Computer vision and image classification, which is my published research area. Model evaluation, overfitting and hyperparameter tuning. Writing machine learning work up to academic standard, covering methodology, results and critical evaluation. How lessons work Send me your module handbook, assignment brief, thesis spec or the code that will not run, and I plan the session around it before we meet. Nothing generic. In the lesson I explain the concept with a worked example, then you take the keyboard while I watch and correct, because you learn far more doing it than watching me do it. You finish with annotated notes and a clear next step, and you can message me between sessions with questions. Practical details Online over Google Meet or Zoom with screen sharing and a shared whiteboard. Sessions run 60 or 90 minutes. I am based in the UK and teach across GMT and Central European time, with evening and weekend slots that suit students anywhere in Europe. Tell me your course, your deadline and exactly where you are stuck, and I will come back with a plan for the first session.