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I teach Python specifically for finance and data applications - the kind used in economics, business analytics, and quantitative programs. This isn't a general "learn to code" course; it's built around real financial data, benchmarking, and the workflows you'll actually use in coursework or early career work. Topics include: Python fundamentals through a finance lens (data structures, functions, control flow). Working with financial data and datasets. Performance benchmarking and writing efficient code. Applying concepts from Hilpisch's Python for Finance.

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Python is the most in-demand programming language in the world right now — and one of the easiest to learn with the right guidance. Whether you've never written a line of code or you're a student who needs to pass a programming course, this is a practical, no-fluff introduction that gets you writing real code from session one. What we can cover depending on your goals: Python fundamentals: variables, loops, functions, data structures - Object-oriented programming (OOP) - Data manipulation with pandas and NumPy - Introduction to machine learning with scikit-learn - Database management with SQL - C and Java upon request - MATLAB and R available for engineering/science students Why learn with me? I'm not a student teaching on the side — I'm a professional engineer who uses Python daily for data analysis, modeling, and automation. I know exactly which concepts matter in the real world and which ones you can skip for now. Sessions are 100% personalized: I adapt the pace, the examples, and the exercises to your background and your goal — whether that's passing your university exam, building a project, or landing a job.

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5Students

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.

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You will learn Systematic Reasoning & Logical Thinking which is a requirement for entering Computer Science program in many universities. The book “Delftse Foundations of Computation” especially its second chapter will be the main source of our lesson, but other more in-depth books will be also covered if you want to improve even further on logical thinking. The topics in our lesson include: • Propositional Logic: Logical operators; Precedence rules; Logical equivalence; Implications in English; Exclusive or; Universal operators; Classifying propositions • Boolean Algebra: Substitution laws • Logic Circuits: Logic gates; Combining gates to create circuits; From circuits to propositions; Disjunctive Normal Form; Binary addition. • Predicate Logic: Predicates; Quantifiers; Tarski’s world and formal structures; • Deduction: Valid arguments and proofs; Proofs in predicate logic If you have any additional questions before starting a class, please feel free to ask me. I am here to assist! :)

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Objective: To understand AI without fear, to use it to simplify one's life, to know how to identify digital traps, and to use Word, Excel, etc. without difficulty. 1: Demystifying AI (What exactly is it?) AI is not a movie robot: Difference between fiction and reality. How it works (simply): The image of the "giant library": AI has read billions of books and uses them to predict the continuation of a sentence or create an image. Where is it already present? Spell checkers, Netflix/YouTube suggestions, GPS, and voice assistants (Siri/Alexa). 2: Using AI to make life easier Conversing with AI (ChatGPT, Claude, Gemini): Ask him to write an administrative email or a complex letter. Summarize a long newspaper article or document. Plan a travel itinerary or find recipe ideas with what's left in the fridge. AI for creativity and memory: Generate images to illustrate a birthday card (Midjourney, DALL-E). Using AI to restore or colorize old family photos. 3: Learning to "talk" to AI (The Art of the Prompt) The context method: Why "Give me a cake recipe" is less effective than "I am allergic to gluten and I am hosting 4 people, give me a simple chocolate cake recipe". The expert's role: Learning to tell AI "Act like a travel guide" or "Act like an expert gardener". 4: Precautions and Critical Thinking (The Survival Guide) "Hallucinations": Understand that AI can make false claims with complete certainty (never take medical or legal advice from AI without verification). Privacy protection: Never give sensitive data (social security number, passwords, bank details) to an AI. Knowing that everything we write to the AI is potentially used to train it. Spotting "Deepfakes": How to recognize a doctored image or video (details on the hands, strange reflections, slightly metallic voice). Verify the information: the golden rule of cross-referencing sources. 5: Ethics and Impacts (To go further) Copyright: Who owns an image created by AI? The environmental impact: The water and energy consumption of AI servers. The future: Will AI replace us or assist us?

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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.

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This course introduces students to the fundamentals of Information and Communication Technology (ICT) and its role in modern society. Topics include computer hardware and software, digital communication tools, internet technologies, data management, cybersecurity, and emerging trends. Students will gain practical skills in using productivity software, conducting online research, and understanding the ethical and responsible use of digital resources. The course emphasizes both technical proficiency and digital literacy, preparing learners to confidently navigate and contribute to a technology-driven world.

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Experienced and patient teacher of logic for computer science. I have taught logic, formal languages and automata theory to undergraduates for six years. My tutoring is adapted to the student's level and goals. Whether you need to learn logic for your studies, or you would simply like to know more about the subject, I will be more than happy to help you improve your understanding and skills. Logic The sciences presuppose a certain standard of rationality. An ability to distinguish between correct reasoning and claims that do not follow from the assumptions. In this class we study the basic principles of logic and apply mathematical techniques to the study thereof. Topics include: Propositional and Predicate Logic Syntax and semantics Natural deduction Semantic tableaux Correctness and soundness Completeness Formal languages and automata A formal language is an abstraction of general characteristics of programming languages. Such a languages consists of a set of symbols together with some rules to determine whether a string made up out of those symbols is a member of the language. Topics include: Regular languages, context-free languages Finite automata, pushdown automata, Turing machines Regular expressions Regular grammar, context-sensitive grammar Pumping lemmas for regular and context-free languages

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Session 1: Revolutionizing your Scientific Writing with LaTeX & AI Duration: 2 Hours | Level: Beginner | Tools: Overleaf + AI** First Hour: Foundations and Cloud Environment (60 min) 1. Introduction to LaTeX Philosophy (15 min) - The "WYSIWYM" concept:** Explain the difference between Word (*What You See Is What You Get*) and LaTeX (*What You See Is What You Mean*). Why content takes precedence over form. - Key advantages:** Unrivaled typographic quality, automatic reference management, stability on long documents (theses), and free of charge. - The structure of a file:** Distinction between the **preamble** (the brain: settings and packages) and the **body of the document** (the heart: text). 2. Immersion in Overleaf (25 min) - Configuration:** Creation of an account and first project "Blank Project". - Exploring the interface:** The file panel (left), the code editor (middle) and the PDF preview (right). - Real-time collaboration:** How to share a project and leave comments (like on Google Docs). - History and versions:** How to revert to a previous version in case of a compilation error. 3. Practical Workshop: My First Document (20 min) * Writing basic commands: `\documentclass`, `\usepackage[french]{babel}`, `\title`, `\author`. * Compilation of the document and observation of the result. * Structuring: Use of `\section` and `\subsection`. Second Hour: Mathematics and the Magic of AI (60 min) 4. The Power of Mathematics (20 min) - Mathematical modes:** Difference between the text (`$...$`) and the centered block (`\[...\]`). - Essential syntax:** Fractions `\frac{}{}`, exponents `^`, indices `_`, and roots `\sqrt{}`. - Introduction to AMS packages: Why amsmath and amssymb are essential for professional rendering. 5. From hand to screen: AI at the service of LaTeX (30 min) - Presentation of OCR tools:** Use of **Mathpix Snip** (the leader) or models like Gemini/ChatGPT to transform a photo into code. - Concrete demonstration: 1. Take a picture of a complex handwritten formula (e.g., an integral with matrices). 2. Use AI to generate the corresponding LaTeX code. 3. Correction and insertion: Learn to check the AI-generated code before copying and pasting it into Overleaf. 6. Conclusion and Q&A (10 min) * Summary of achievements. * Resources for further exploration * Definition of the exercise for the next session.

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This course provides a foundational understanding of Information Technology, data centers, covering architecture, power & cooling, networking, storage, virtualization, security and lots more. Learn best practices for efficiency, scalability, and reliability while exploring emerging data center solutions. Ideal for IT professionals, engineers, and facility managers involved in data center deployment or management. This course offers a comprehensive exploration of Information Technology, data center infrastructure, guiding students through the entire lifecycle—from initial design and planning to day-to-day operations and long-term performance optimization. Students will learn the critical components of data center design, including site selection, power and cooling systems, space planning, networking, and physical security. The course also covers operational best practices, monitoring tools, energy efficiency strategies, disaster recovery planning, and emerging trends. By integrating technical, environmental, and management perspectives, students will gain the knowledge and skills required to build and maintain high-performance, cost-effective, and sustainable data center environments.

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Ever wondered what really happens when you open a website or hit "send"? Let's find out together. I've spent 3 years working hands-on with real networks: analyzing live traffic, managing firewalls, and troubleshooting network issues for government, financial, and telecom organizations. I'm Fortinet certified (FCA, FCF) and hold the CNSP (Certified Network Security Practitioner) certification. I'll teach you networking the way it's actually used on the job. No boring theory dumps, just live, hands-on learning you can use right away. You'll learn: How the internet works: IP addresses, DNS, DHCP, and HTTP/HTTPS The OSI and TCP/IP models, made simple Subnetting, routing, switches, and firewalls TCP vs. UDP, ports, and how connections work How to read real traffic with Wireshark and test networks with ping, traceroute, and Nmap How to spot suspicious traffic and keep a network healthy Perfect for: beginners, career changers, students, developers, and anyone preparing for Network+ or CCNA. You'll walk away with a clear picture of how data travels, the confidence to troubleshoot real network problems, and a rock-solid foundation for your IT career. No experience needed, just curiosity and a computer. Book your first session and let's dive in!

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As a Master's student in Data Science at EPFL, a graduate of CentraleSupélec (ranked in the top 3% of my class) and holder of a Bachelor's degree in microtechnology from EPFL, I offer tutoring in mathematics, physics and computer science, from primary school to university level. My teaching experience I was a student teaching assistant at EPFL for 8 courses, working with over 400 students. I currently lead the linear algebra and ICC (Information, Computation, Communication) exercise sessions. Each week, I adapt my explanations to each student's level: that's what I love most about teaching. What I propose • Primary and secondary school: consolidate the basics (calculation, fractions, geometry, equations), regain confidence and improve methodology. • Gymnasium / high school (maturity, baccalaureate): functions, analysis, probabilities, vectors, mechanics, electricity, exam preparation. • University / EPF / preparatory classes: analysis, linear algebra, probability and statistics, numerical analysis, programming (Python, C/C++). My method I begin by identifying the real obstacle: a misunderstanding of the concept, a lack of methodology, or stress. Then, I build the sessions based on the student's lessons and exercises. The goal isn't just to pass the next test, but to understand the material and become independent. Whether you need occasional homework help, regular support, or intensive exam preparation, I adapt to your needs.

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A 34-year-old university graduate, business engineer, with 12 years of professional experience, offers her teaching services. Lessons (1 hour online only) - 1.5 or 2 hours depending on the subject/level/location Educational and organized teacher with excellent revision and organizational techniques Microsoft Office - Excel/Word/PowerPoint - email - typing - ... Educational and patient with a good methodology adapted to each student 97% success rate with regular monitoring Feel free to contact me for more information! See you soon

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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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Is artificial intelligence just for adults? No! A course for children and teenagers who already see AI in Netflix, games or ChatGPT and want to understand what it is, how it "thinks" and how to use it without getting into trouble. In class, the student acts as a detective: • Myth Busters: What is real AI and what just looks like AI • Train a toy AI: simple examples of machine learning (data, hits, biases) • Asks its first well-formulated questions to a generative tool for a short story or image • Learn the rules at home and at school: privacy, copying homework, what not to paste into a tool You don't need to know how to program. It's good enough to test things out. If it works out, we'll continue with projects (stories, art, games) at its own pace. Recommended age: 10–14 years. Also 8–9 if they read fluently and can handle an online class; 15–17 if they want to start from scratch with a critical mind, not just "try ChatGPT".

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Whether you're involved in finance, management, planning, project management, human resources, or perhaps an ambitious student looking to hone your professional dashboarding skills, you've come to the right place. If you're looking for a solution that goes beyond the limitations of Excel and PowerPoint, then you've come to the right place: allow me to introduce you to Power BI. With Power BI, I offer you much more than just a tool. It's a gateway to interactive reporting, efficient data management, and advanced analytics. Here's what I can offer you: - Expert creation and management of interactive reports. - Careful transformation and cleaning of data for maximum accuracy. - Use of powerful DAX formulas for advanced data analysis. - Creation of custom visualizations and impactful dashboards. - Secure sharing and publishing of your reports for seamless collaboration. -Automation of repetitive tasks with Power BI & Power Query. Whatever your specific needs—whether they relate to professional projects, studies, or personal aspirations—I'm here to offer you a tailor-made solution. Together, we'll create a program tailored to your goals, guiding you through every step of your learning journey. Whether you're a beginner looking to master the basics or an expert looking to deepen your knowledge of data analysis, I'm here to provide the expertise and support you need to succeed.

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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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6Students

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.