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This teacher has a fast response time and rate, demonstrating a high quality of service to their students.
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Since March 2025
Instructor since March 2025
Learn Data Communication and Networking! From the fundamentals to the deeper concepts!
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From 34 $ /h
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Learn Data Communication & Networking!🌐

Are you interested in understanding how data moves across networks, how the internet works, and how to build efficient communication systems? I’m excited to announce that I will be offering Data Communication and Networking classes!

📌 What You’ll Learn:
✅ Networking fundamentals and protocols
✅ OSI and TCP/IP models explained
✅ Wired vs. wireless communication
✅ IP addressing and subnetting
✅ Network security basics
✅ Real-world applications and hands-on practice

📌 Who Is This For?
🔹 Students, tech enthusiasts, and IT professionals
🔹 Anyone looking to improve their networking skills
🔹 Those preparing for networking certifications

📌 Why Join?
✔️ Practical, easy-to-understand lessons
✔️ Hands-on exercises and real-world examples
✔️ Learn from an experienced instructor

If you’re interested, feel free to reach out for more details. Let’s dive into the world of networking together! 🚀
Location
location type icon
Online from Lebanon
About Me
Hi there! My name is Rony, a coding instructor from Lebanon! I have more than two years of tutoring experience and my teaching style revolves around making classes fun, energetic, and engaging! Looking forward to making your learning experience the best it can be!
Education
High School - Maroun Aboud Secondary School | Graduated in 2022

Modern University of Business and Science - Computer Science - 2022 - Present | Graduated in 2025 - GPA 3.6
Experience / Qualifications
2+ years of tutoring experience:
• Designed and delivered interactive programming lessons, focusing on Java, Python, and other relevant
languages.
• Assisted students in developing coding projects, debugging, and optimizing their work.
• Simplified complex programming concepts for beginners, enhancing comprehension and retention.
• Conducted assessments to evaluate student progress and provide personalized feedback.
Age
Teenagers (13-17 years old)
Adults (18-64 years old)
Seniors (65+ years old)
Student level
Beginner
Intermediate
Advanced
Duration
60 minutes
The class is taught in
English
Availability of a typical week
(GMT -05:00)
Chicago
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
Empower young minds to create their own mobile apps with this fun and interactive course! Designed for children aged 9 to 13, this course introduces app development using MIT App Inventor, a beginner-friendly platform that makes coding easy and exciting. Students will learn the basics of programming, user interface design, and problem-solving as they build their own functional Android apps. Through hands-on projects and creative challenges, they will develop logical thinking and digital skills while bringing their ideas to life. No prior experience is needed—just curiosity and a passion for technology!
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Dive into the exciting world of game development in this beginner-friendly course designed for kids aged 9 to 13! Using fun and interactive tools, students will learn the fundamentals of coding, game design, and animation as they create their own playable games. They will explore key concepts like logic, storytelling, and user interaction while developing problem-solving and creativity skills. Through hands-on projects, they will gain confidence in programming and bring their game ideas to life. Whether they’re aspiring game designers or just love playing games, this course is the perfect start to their game development journey!v
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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.
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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 :)
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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
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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.
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> 🧠 “If I had an hour to solve a problem, I would spend 55 minutes defining the question.”

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🧰 Exclusive methods taught

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Action
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Format

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✅ Professionals from all sectors wishing to integrate AI into their daily lives (automation, analysis, resolution).
✅ Students and curious people wanting to master a strategic skill for the future of work. 🧑‍💼📈

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✔️ Understand the functioning and capabilities of LLMs (ChatGPT, Gemini, Claude, etc.) 🤓
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✔️ Create powerful visual prompts with the IMAGES method 🖌️
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Is artificial intelligence just for adults? No!

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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...)

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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.
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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.
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• Teaching methodology and techniques: I favour a personalized approach, adapting the courses according to the profile and academic background of each student.
• Typical course structure: tutoring in economics, econometrics, statistics and probability, financial mathematics, trading, investment, or political economy. Courses can take place at home, via videoconference, or at a pre-selected location, ideally quiet, free, and conducive to learning.
• Specifics as a teacher: I offer support throughout the school year, with free corrections of exercises outside of class, regular availability, and the guarantee of being accessible until the end of the year, subject to the general conditions of Superprof.
• Target audience: all levels, regardless of diploma, class or specific characteristics.
-------
The path and the method are in there; take a little bit of each.

Holding a degree in mathematics from EPFL, I offer private lessons in Geneva or online.

I graduated from EPFL with a degree in mathematics, having completed all the Bachelor's level courses in this discipline. I have gained significant experience tutoring students from middle school to university level (mathematics and physics). I have also assisted with teaching at EPFL, particularly in specialized courses such as analytic geometry (advanced mathematics course), analysis (first and second year Bachelor's level), and linear algebra (first year Bachelor's level). My in-depth mastery of the theory in these disciplines provides me with the skills and teaching abilities necessary to effectively support high school and university students, helping them understand the theoretical concepts in their courses and apply them practically in their exercises.

Typical course: a quick review (adapted to needs) of the essential concepts of the course, followed by practical exercises and oral role-playing (going to the board, discussion on the physical meaning, etc.), as in a competitive oral exam.

All my lessons are prepared in advance based on the topics covered in class (the student specifies their needs from one session to the next). I also create a handout containing sample exercises illustrating different methods, fully corrected and explained by me.

My commitment to my students' success is absolute. I only prioritize motivated students who are ready to put in the necessary effort to progress.

My main focus is on in-depth understanding and the quality of work. Depending on the student's request, I can also suggest exercises to do between sessions (not mandatory, depending on available time and homework already assigned by their school).
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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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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.
verified badge
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.
verified badge
Microsoft Excel is very powerful data analysis software. It is a practical solution in the short to medium and long term to automate your calculations, to have a global and detailed overview on your activities, and to analyze your data.

As an accountant, marketer, commercial agent, secretary, merchant, salesperson or company manager, a good mastery of this software will improve your efficiency, your competitiveness, and will save you a lot of time and money. Whatever your field of activity, this software is designed to help you.

During this training you will learn:
- best practices, functionalities and tools;
- functions and their use;
- handling of Dynamic Cross Tables, dynamic graphics,
- the design of dashboards,
- and you will acquire reflexes that will be useful for your entire career.

Duration of training: 1 month
Number of hours: 24 hours

I am expecting many of you because we have a lot to share.
verified badge
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 :)
verified badge
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! :)
verified badge
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
verified badge
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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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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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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Are you using ChatGPT, Gemini, or other AIs, but feel like you're only scratching the surface of their potential? Are your results often generic, inaccurate, or disappointing? It's time to move from a simple user to a true AI pilot. 🤖✨

This 4-hour intensive course, "Prompt Engineering: Mastering the Art of Communicating with AI," is designed to give you the keys to effective and powerful communication with language models (LLM).

> 🧠 “If I had an hour to solve a problem, I would spend 55 minutes defining the question.”

This is the essence of Prompt Engineering: the art of asking the right question to get the best answer. 🎯

🧰 Exclusive methods taught

During this practical and immersive training, you will discover two structured methods to transform your ideas into tangible results:

🔹 The ACTIF method
👉 A foolproof approach to building powerful text prompts. You'll learn how to define:

Action
Context
Tone
Identify
Format

...in order to obtain clear, targeted and impactful content, analyses or strategies. 📄💡

🔹 The IMAGES method
👉 Your visual passport to create high-value graphic prompts. Based on 6 pillars:

Intention
Pattern
Atmosphere
Grain
Aesthetic
Style

...it will allow you to generate images that faithfully reflect your creative vision. 🖼️🎨

👥 Who is this course for?

✅ Entrepreneurs and marketers who want to create targeted content and relevant strategies.
✅ Content creators, writers, designers who want to boost their creativity and productivity.
✅ Professionals from all sectors wishing to integrate AI into their daily lives (automation, analysis, resolution).
✅ Students and curious people wanting to master a strategic skill for the future of work. 🧑‍💼📈

🧠 What you will master in 4 hours:

✔️ Understand the functioning and capabilities of LLMs (ChatGPT, Gemini, Claude, etc.) 🤓
✔️ Structure impactful text requests with the ACTIF method 📝
✔️ Create powerful visual prompts with the IMAGES method 🖌️
✔️ Move from simple interaction to intelligent co-creation with AI 🧩
✔️ Put it into practice with concrete exercises, dedicated tools, and realistic use cases 🛠️📊

🎓 Join us!

Stop being subjected to AI... and start leading it.
🎯 Master the art of dialogue with artificial intelligence,
💼 and unleash their full potential to serve your projects!
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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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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.
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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.
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• Teaching methodology and techniques: I favour a personalized approach, adapting the courses according to the profile and academic background of each student.
• Typical course structure: tutoring in economics, econometrics, statistics and probability, financial mathematics, trading, investment, or political economy. Courses can take place at home, via videoconference, or at a pre-selected location, ideally quiet, free, and conducive to learning.
• Specifics as a teacher: I offer support throughout the school year, with free corrections of exercises outside of class, regular availability, and the guarantee of being accessible until the end of the year, subject to the general conditions of Superprof.
• Target audience: all levels, regardless of diploma, class or specific characteristics.
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The path and the method are in there; take a little bit of each.

Holding a degree in mathematics from EPFL, I offer private lessons in Geneva or online.

I graduated from EPFL with a degree in mathematics, having completed all the Bachelor's level courses in this discipline. I have gained significant experience tutoring students from middle school to university level (mathematics and physics). I have also assisted with teaching at EPFL, particularly in specialized courses such as analytic geometry (advanced mathematics course), analysis (first and second year Bachelor's level), and linear algebra (first year Bachelor's level). My in-depth mastery of the theory in these disciplines provides me with the skills and teaching abilities necessary to effectively support high school and university students, helping them understand the theoretical concepts in their courses and apply them practically in their exercises.

Typical course: a quick review (adapted to needs) of the essential concepts of the course, followed by practical exercises and oral role-playing (going to the board, discussion on the physical meaning, etc.), as in a competitive oral exam.

All my lessons are prepared in advance based on the topics covered in class (the student specifies their needs from one session to the next). I also create a handout containing sample exercises illustrating different methods, fully corrected and explained by me.

My commitment to my students' success is absolute. I only prioritize motivated students who are ready to put in the necessary effort to progress.

My main focus is on in-depth understanding and the quality of work. Depending on the student's request, I can also suggest exercises to do between sessions (not mandatory, depending on available time and homework already assigned by their school).
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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.
Good-fit Instructor Guarantee
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