Trusted teacher

Working part-time in the watch industry, I have been tutoring for several years in the context of refresher, occasional support or preparation of exams or competitions. Very experienced in relation to the difficulties encountered by students and pedagogue, I adapt to the needs of each to quickly regain the necessary confidence, the methodology of mathematical reasoning and allow a rapid improvement of results. Experienced and pedagogue, I adapt to the needs of the student to help him consolidate his knowledge methodically, to regain confidence and improve as quickly as possible its results. I teach these courses in a radius of 30 km around Geneva.

Trusted teacher

I am a dynamic and demanding teacher who gives private lessons in Physics-Chemistry as well as Mathematics. I graduated from teaching seven years ago, after a masters in physical sciences with honors, and I teach in college and high school since. I have also been preparing students for the Baccalaureate Science for many years, all of whom have been awarded very good honors. I also prepare my students for different exams (Matu, Bac, preparation for EPFL, etc...) I make sure to rework the basics so that the student can progress quickly. It is important to me that my students acquire a solid foundation of knowledge. I also give effective work methods that will allow him to progress much more quickly and so he can regain self-confidence. I can travel to the student's home or also conduct the lesson via Zoom/Google Meet.

Trusted teacher

Need a catch-up, tutoring, private lessons or help with homework in mathematics? In computer science ? In logic? I'm here for you! I offer you a personalized approach; because there is no one method that works for everyone, I adapt to the needs and requests of each student (and their parents). The first hour of class will be used to define the student's needs, deadlines and strengths. My courses are aimed at secondary school students of all levels, higher education students and anyone wishing to refresh or strengthen their knowledge of mathematics and computer science. I have been helping friends and acquaintances on a voluntary basis for a long time in the success of their studies and I hope to be able to put this experience to the benefit of your success :)

Trusted teacher

1Students

Advanced mathematics and statistics often present one of the main challenges encountered at university. Many students understand the lectures but find themselves stuck as soon as they have to solve exercises or prepare for exams on their own. For over 35 years, I have been supporting undergraduate students, BUT, PASS, business school students, as well as adults undergoing professional retraining, to help them acquire an effective work method and succeed in their exams. Subjects taught Analysis Linear algebra Matrices and linear systems Functions and optimization Descriptive statistics Probabilities Hypothesis testing Estimate Introduction to Python or SQL when the program requires it A clear and progressive method Each session is tailored to your course of study and your objectives. We work from your lectures, tutorials, exercises or past papers to precisely target the concepts that are causing problems. The goal is not just to succeed at one exercise, but to understand the method that will allow you to solve others independently. Session Procedure The courses take place entirely online with screen sharing and an interactive digital whiteboard. We alternate explanations, demonstrations and exercises with live corrections in order to immediately check understanding and progress effectively. Available formats 60-minute session Ideal for preparing for a tutorial, understanding a difficult concept or getting stuck on an exercise. 90-minute session Recommended for refresher courses, exam preparation, or in-depth study of a chapter. My commitment My goal is to help you understand mathematics in a lasting way rather than simply memorizing calculation methods. You will progress not only in your current exam, but also in the courses that will follow in your curriculum. Whether you are preparing for a midterm, a competitive exam, a semester validation or a return to studies, I will be happy to support you in your success.

Trusted teacher

Since 2010, the surveillance technologies of large companies as well as governments have considerably increased. Although you do not use any Google product and "refuse cookies", Google Analytics trackers are present on 90% of the websites and the sites you visit know your age, your browsing history as well as what time. you chat on WhatsApp, with whom and how often. These trackers form your digital footprint, in spite of you, and sell them. Your insurance, for example, can tell if you are expecting a baby in 9 months or if you develop signs of a chronic illness. I propose to teach you to: - Configure your phone and computer to use the Tor network, and protect yourself against surveillance. - How to use a VPN, which protocol to use and how to check if the VPN is monitoring you. - How to set up a kill switch so that the VPN does not leak and that the internet only works when the vpn is connected. - How to use a different operating system to stop monitoring Apple, Google and Microsoft. - How to pay on sites anonymously by purchasing prepaid credit cards with bitcoin. - How to anonymize your bitcoin - How to ensure that the government cannot afford to find you. - How to register on websites anonymously. - Buy Bitcoins (or other virtual currency) securely and anonymize them. I have worked for years with journalists, NGOs and companies to improve security and teach how to be anonymous in the eyes of big companies, malicious actors or even governments. Important: I do not teach courses on "how to make money with bitcoin", I only teach how to use it responsibly and the advanced protocols on which this system depends.

Trusted teacher

I give private lessons and help prepare for entrance tests and exams in mathematics and statistics. I have also worked in web development, website creation, applications for smartphones and mini-applications on social networks. For all levels. I travel in the canton of Geneva and surroundings and possibility of giving lessons by Webcam. References on request and guaranteed availability.

Trusted teacher

The courses are adapted to each student, his achievements, his difficulties and his objectives. They are based essentially on the practice of exercises and exam subjects, supplemented by the clarification of theoretical notions that would not have been understood. Clear explanations and effective advice allow you to acquire ease and serenity to fill gaps, better organize your work, regain self-confidence.

Trusted teacher

I accompany students from the sixth to the final year who have a need for regular support, or increased motivation and learning after dropping out of school. I teach a systematic way of working, fully focused on efficiency. Whatever the purpose of my students, I teach them first of all that to revise an exam, it is absolutely necessary to understand what is expected of them. A mathematics test at the Baccalauréat is not prepared in the same way as a return to preparatory classes. The first thing to do, even before studying the lesson, is to study the exam.

Trusted teacher

I just graduated from the HES-SO Master in Information and Communication Technologies (ICT) and I have 3 years experience as a developer in a company that develops medical devices. During my studies, I used to exchange and explain complex things. I am a patient and I like to transmit my knowledge. As far as Mathematics is concerned, I can teach students from primary to mature. For computer science, I can teach computer science students who have difficulties with programming (C, C ++, C #, JAVA, python, SQL, ADA) or who wish to have a help for understanding in different computer courses . It is also possible to introduce computers or programming to people who do not have basic knowledge.

Trusted teacher

Working part-time in the watch industry, I have been providing private lessons for several years as part of refresher courses, occasional support or preparation for exams or competitions. Very experienced in relation to the difficulties encountered by students and pedagogue, I adapt to everyone's needs in order to quickly find the necessary confidence, the methodology specific to mathematical reasoning and thus allow a rapid improvement in results. Experienced and pedagogue, I adapt to the needs of the student to help him consolidate his knowledge methodically, regain confidence and improve his results as quickly as possible. I provide these courses within a radius of 10 km around Geneva.

Trusted teacher

I give private lessons and help in the preparation of entrance tests and exams in mathematics and statistics. I have also worked in web development, website creation, applications for smartphones and mini-applications on social networks. For all levels. I move in the canton of Geneva and possibility to give courses by Webcam. References on request and availability assured.

Trusted teacher

I am a tutor available in the Coppet area. I am a native English speaker who recently finished a PhD in Physical Chemistry at the University of Cambridge. I have advanced education in math, physics, math, computer science and chemistry. I can help students in need of some extra help with their homework or exam preparation. I strongly believe that the traditional classroom environment is not for everyone. I enjoy helping students find their own approach to learning to help them succeed.

Trusted teacher

19Students

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.

Trusted teacher

6Students

If you’ve ever felt that science and math are difficult, it’s probably because no one showed you how to think like a problem solver. In my classes, you’ll learn not just formulas or code but how to truly understand concepts, apply them, and build strong logical intuition. I teach: • 🔢 Mathematics: From algebra and calculus to applied problem-solving for real-world use. • 💻 Computer Science: Coding fundamentals (Python, C++), algorithms, and logical thinking for beginners and intermediate learners. • ⚛️ Physics: Mechanics, thermodynamics, and practical examples that make abstract ideas simple and visual. As a Software Engineer and Master’s student in Engineering at Nagoya University, I bring both academic knowledge and hands-on experience from real projects. My teaching approach is interactive, visual, and deeply focused on understanding over memorization. Let’s turn complex problems into clear, step-by-step insights — and make learning something you genuinely enjoy.

Trusted teacher

1Students

I offer one-to-one Machine Learning and AI tuition for university students, postgraduates, working professionals, and serious self-learners. Lessons are available online or in person around Birmingham. What I cover: Python for data science and ML (NumPy, Pandas, Scikit-learn) Deep learning with TensorFlow and Keras Core ML concepts: regression, classification, clustering, neural networks, CNNs Computer vision and image classification (my published research area) University coursework support, dissertation help, project guidance Help with Kaggle competitions and personal portfolio projects How I teach: I focus on understanding, not memorisation. We work through real datasets and real problems — not toy examples — so you can actually apply what you learn. I'll help you build a model from scratch, debug it when it doesn't work, and explain the maths behind why it does or doesn't perform well. For university students, I can also help with assignments, dissertations, and final-year projects. Whether you're just starting out, stuck on a coursework project, or trying to break into ML professionally, I can meet you wherever you are and help you move forward.

Trusted teacher

2Students

As a Franco-Belgian management teacher, I give Excel lessons with passion! Whether remotely or face-to-face, I offer many examples and exercises to accompany you. I travel without problem throughout the region of Brussels and its surroundings, for lessons of at least 2 hours. For France, courses are only given remotely. Here are some key words that will be covered in my classes: Scenario analysis, Year, Rounding, Today, Bdnb, Bdnbval, Bdsum, Search, Column, Copy/paste in values, Copy/paste with transposition, Consolidation, Date, Datedif, Determat, Dollar, Right, Righterg, Equiv, Esterror, Estna, Frequency, Filter (simple and advanced), Format of cells, Left, Large.Value, Printing of documents, Index, Indirect, Inversemat, Day, Weekday, Line, Matrix, Max, Maxa, Max.Si, Min , Mina, Mina.If, Formatting of cells and ranges, Month, Average, Average.If, Nb, Nb.If, Nbval, Naming of cells and ranges, No, Small.value, Product, Productmat, Protection of cells, Lookup (Lookup), Lookupv (VLookup), Lookuph (HLookup), If (If), If.Not.Disp, If.Conditions, Iferror, Sum, Sumproduct, Sum.If, Sum.If.Set, Substitute , Pivot tables, Sorting, Cell locking Do not hesitate to contact me to organize your lessons according to your needs and availability. Together, we will develop your Excel skills in an efficient and personalized way.

Trusted teacher

1Students

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.