Title: "Javascript Mastery: Unlocking the Potential of Programming"

From 29 € /h

Are you ready to dive into the fascinating world of JavaScript programming? Whether you're a beginner with no coding experience or an experienced developer looking to expand your skills, our tutoring sessions are designed to empower you with the knowledge and confidence to harness the full potential of JavaScript.
What will you get?
*Expert Guidance
*Hands-On Learning
*Comprehensive Curriculum
*Real-World Applications
*Problem-Solving Skill
*Individualized Progress Tracking
Whether you're aspiring to become a professional JavaScript developer, or simply looking to enhance your coding skills, our JavaScript tutoring sessions will equip you with the knowledge, confidence, and practical experience to excel in the world of programming.

Location

Online from Germany

Age

Children (7-12 years old)

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

French

Arabic

Skills

Javascript

Computer programming

Availability of a typical week

(GMT -05:00)

New York

Online via webcam

Mon

Tue

Wed

Thu

Fri

Sat

Sun

00-04

04-08

08-12

12-16

16-20

20-24

Expressive English: Mastering Language Fluency and Communication Skills

29 € /h

Are you ready to embark on a transformative journey towards mastering the English language? Look no further! Our dynamic and engaging tutoring sessions are designed to empower you with the skills and confidence you need to communicate fluently and express yourself effectively in English.
What will you get in our class?
*Expert Guidance
*Interactive and Engaging Lessons
*Comprehensive Language Skills
*Real-World Relevance
*Individualized Progress Tracking

Title: "Python Mastery: Unlocking the Potential of Programming"

29 € /h

Are you ready to dive into the fascinating world of Python programming? Whether you're a beginner with no coding experience or an experienced developer looking to expand your skills, our tutoring sessions are designed to empower you with the knowledge and confidence to harness the full potential of Python.
What will you get ?
*Expert Guidance
*Hands-On Learning
*Comprehensive Curriculum
*Real-World Applications
*Problem-Solving Skill
*Individualized Progress Tracking
Whether you're aspiring to become a professional Python developer, seeking to automate tasks, or simply looking to enhance your coding skills, our Python tutoring sessions will equip you with the knowledge, confidence, and practical experience to excel in the world of programming.

Youssef

4.85

(13)

Hello, I am a doctoral student in electrical engineering and associate professor in engineering sciences, experienced in the field of electrical engineering, I offer support courses in the subjects of engineering sciences (Electronics, automatics, electrical engineering, automation, programming).

Digital electronics
Analog electronic
electromagnetism (propagation of high frequency waves)
Automatic (continuous, sampled)
electrical engineering (transformers, electrical machines, switching power supply)
C / c ++ programming, Assembler, ARM, STM32
renewable energy (wind, PV)
engineering Sciences
RDM
Python,VHDL
PIC Microprocessor and Microcontroller
Signal processing and data acquisition
Engineering Sciences

These courses allow the student to get up to speed and regain confidence in all scientific subjects, just as they prepare him effectively for the Baccalaureate, the Preparatory Classes or various examinations of the engineering classes.

COURSE OBJECTIVES AND PEDAGOGICAL APPROACH

Resumption and deepening of fundamental concepts through exercises with course reminders.

Put the student in a situation of questioning and research.

Respond to individual issues and questions

Exercise training in order to achieve real mastery of the content.

Learn to build theoretical reasoning from observable facts or hypotheses.

Specific preparation for higher education requirements (in-depth content, increase in work capacity, enrichment of scientific background)

This educational approach is effective since it has often led me to interesting results with my students.

Associate professor provides support courses in electrical engineering

Enrique

4.85

(13)

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.

Amin

4.85

(13)

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.

Gaëlle

4.85

(13)

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?"

Giuliano

4.85

(13)

Python is a powerful and versatile programming language with countless possibilities. You can use it for data analysis, image processing, automation, software development, hardware control, and much more.

Do you want to create your own software?
Work with data or images?
Automate repetitive tasks?
Control or manage your own hardware?

Whether you are just starting to learn Python or already have a specific project and need some guidance, I would be happy to help you.

My goal is to explain things clearly, adapt to your level, and help you understand not only how to make something work, but also why it works.

Let's turn your ideas into working Python projects!

Salah

4.85

(13)

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.

Roger

4.85

(13)

Are you looking to deepen your knowledge of physics or master advanced techniques in Python programming? This course is designed to help you achieve a level of academic and technical excellence, whether you are a high school student, university student or professional looking to develop your skills.

With an interactive and effective teaching approach, you will benefit from personalized support to overcome obstacles, grasp complex concepts and improve your performance. Whether it is to succeed in difficult exams, high-level competitions or to create powerful applications in Python, this course will provide you with all the tools necessary to achieve your goals.

🎯 Why Choose This Course?
Advanced and Expertise Level: In-depth content and effective methodology to master complex topics in physics and programming.
Personalized Courses: Sessions adapted to your needs, your pace and your level.
Interactive Online Learning: Dynamic online courses with screen sharing and audio interaction for enjoyable and engaging learning.
Concrete Projects and Practical Applications: Development of practical projects to implement theoretical concepts.
Intensive Preparation for Exams and Competitions: Rigorous training with complex exercises and exam simulations to guarantee your success.
Flexibility and Comfort: Learn from home, according to your schedule, without having to travel.

🔬 Advanced Physics – From High School to University
This module offers a complete and in-depth program to prepare you for demanding secondary school exams, preparatory classes and scientific university courses:

1. Secondary Physics (High School and Preparatory Classes)
⚙️ Classical Mechanics: Kinematics, dynamics, Newton's laws, energy and work, oscillations.
🌊 Waves and Vibrations: Wave propagation, interference, diffraction, acoustics.
⚡ Electricity and Magnetism: Electric circuits, electrostatics, magnetostatics, electromagnetic induction.
🔦 Optics: Geometric optics (lenses, mirrors), wave optics (interference, diffraction).
🌡️ Thermodynamics: Laws of thermodynamics, thermodynamic cycles, entropy, changes of state.

2. University and Advanced Physics
🔄 Analytical Mechanics: Lagrangian, Hamiltonian, and generalized coordinates.
🌐 Advanced Electromagnetism: Maxwell's equations and the propagation of electromagnetic waves.
🧪 Quantum Physics: The postulates of quantum mechanics, the wave function, and the Schrödinger equation.
☢️ Nuclear and Particle Physics: The structure of the nucleus, radioactivity, and fundamental interactions.
🌌 Special Relativity: Lorentz transformations, time dilation, and length contraction.

3. Intensive Preparation for Exams and Competitions
📘 Scientific methodology: Learn to analyze statements, structure responses and write clearly and precisely.
📝 Application exercises and past papers: Intensive training to master the concepts and pass your exams.
🔎 Solve complex problems with detailed explanations and effective strategies.
⏰ Time management: Practical tips to improve your time management during exams.

🐍 Advanced Python Programming – Focused on Efficiency
This module will teach you how to program efficiently and effectively in Python, with an emphasis on best practices and advanced techniques:

1. Mastering Advanced Concepts in Python
🔠 Advanced Syntax and Best Practices: Deepening of Python concepts.
📦 Object-Oriented Programming (OOP): Abstract classes, interfaces, and design patterns in Python.
🔄 Functional Programming: Using lambda, map, filter, reduce, generators and iterators.
⚡ Asynchronous Programming: Implementing asyncio for fast and responsive applications.
🧪 Unit Testing and Code Quality: Use of pytest, code coverage, and CI/CD.

2. Performance Optimization
🚀 Algorithm Optimization: Analysis of algorithmic complexity and use of efficient data structures.
⚙️ Profiling and Debugging: Performance evaluation with cProfile and code improvement.
🔒 Security and Robustness: Writing secure code and handling exceptions appropriately.
3. Practical Projects and Advanced Applications
🌐 Web Applications: Building high-performance web applications using Flask and FastAPI.
📊 Data Science and Machine Learning: Exploitation of Pandas, NumPy, Scikit-learn and TensorFlow.
🕸️ Advanced Web Scraping: Complex data extraction using BeautifulSoup and Selenium.
🤖 Automation and Efficient Scripts: Automation of tasks and development of efficient scripts.

🧑‍🏫 Methodology and Pedagogical Approach:
Learning by doing: Each theoretical concept is directly implemented through practical exercises.
Interactive Online Teaching: Using audio and screen sharing for seamless communication and dynamic learning.
Personalized monitoring: Regular support to assess your progress and answer all your questions.
Concrete projects: Development of complete projects to apply your programming skills.
Motivation and Confidence: A positive and encouraging approach to build your confidence in your abilities.

🎓 For whom?
This course is intended for:

- High school and preparatory class students who aspire to academic excellence.
- University students in science and computer science wishing to deepen their knowledge.
- Candidates for scientific competitions who are preparing for physics and programming tests.
- Developers looking to improve their advanced Python skills.
- Researchers and engineers who use Python for complex scientific applications.

🔔 Register now! Don't miss the opportunity to master advanced physics while developing skills in optimized and efficient Python. Join our program "🚀 Advanced Courses - 🔬 Physics from High School to University & 🐍 Advanced Python Programming Focused on Efficiency!" and progress at your own pace with confidence and motivation!

Baia

4.85

(13)

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.

Hayat

4.85

(13)

This course is designed for anyone interested in learning data science using Python. It provides a hands-on introduction to fundamental data analysis tools such as NumPy, pandas, matplotlib, and seaborn. You'll learn how to manipulate datasets, create visualizations, and lay the foundations for statistical analysis and machine learning.

The course combines theory and practical exercises for effective, practical progress. No prior programming experience is necessary: we'll start with the basics to build solid, usable skills quickly.

Mariem

4.85

(13)

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.

Amr

4.85

(13)

Private Programming Lessons for you / your family / your company employees
Programming Tutor – IGCSE & Computer Science Subjects
Deeper understanding, stronger results

• Lecturer at the American University AUC
• Over 20 years of experience in training students for government employees, oil companies (BP), food companies (Nestle), banks (CIB), and telecommunications companies (Vodafone).

• Teaching curricula, syllabuses, courses:
o IGCSE (Computer Science 0478, ICT 0417)
o Programming and computer courses for all educational levels (from primary to university)
o Microsoft Windows, Word, Excel, PowerPoint, Outlook, MS-Project
o Programming, C, C++, VB.NET, C#, Python, Database, SQL, MQL, VBA
o HTML, CSS, JavaScript, Angular
o Different database systems
o Data analysis using Excel
o Computer and Information Colleges Curricula
o Using artificial intelligence in life and work

• Master office applications to improve your job performance.
• Prepare yourself to work as a Front-End / Back-End / Full Stack Developer
• Theoretical and practical training for market requirements
• Don't miss out on technology. Lessons are designed for the elderly, in a simple and understandable way (use of computers and their programs, use of mobile phones, dealing with the Internet and social media).
• Lessons are available in person or online.

Farouk

4.85

(13)

This module is a crucial step for any web developer wishing to move from simple DOM manipulation to mastering modern frameworks. The objective is clear: to understand the "invisible foundations" of the language in order to write shorter, more readable code and, above all, be ready to code professionally in React.

🎯 Training Objectives

1- Demystify the modern syntax (ES6+) often used in React.
2- Increase efficiency by using the most powerful syntactic shortcuts.
3- Secure your code to avoid frequent bugs related to missing data.
4- Mastering asynchronicity to manage data calls (API).

📖 Detailed program content

The course is divided into 13 key concepts, illustrated by comparative examples (classic syntax vs. modern syntax) and concrete use cases in React:

1- Ease of writing: Use of Template Literals (`backticks`) for dynamic character strings and Shorthand property names to simplify the creation of objects.

2- Logic and Functions: Mastery of Arrow => Functions (arrow functions) and their implicit return, essential for React components and hooks.

Data manipulation:

1- Destructuring (decomposition) to properly extract data from objects and arrays (e.g., Props and States).

2- Rest & Spread Operators (...) to copy arrays or merge objects without modifying the original (concept of immutability).

Code robustness:

1- Managing default parameter values.

2- Advanced security with Optional Chaining (?.) and Nullish Coalescing (??) to prevent application crashes.

3- Functional Programming: Intensive use of array methods (.map(), .filter(), .reduce(), .find()) to transform data into user interfaces.

4- Architecture and Asynchronism: Code organization via modules (Import/Export) and API request management with Promises and Async/Await.

🛠️ Teaching method: "Learning by doing"

This course is not just about theory. It includes:

The "Interstellar Dashboard" Exercise: A 15-minute thematic case study where students manipulate data from space missions. This allows them to immediately apply destructuring, filtering, and asynchronicity to a real-world project.

The Interactive Quiz: A series of 10 questions designed to validate understanding of each concept before moving on. Each question presents real-world scenarios that developers will encounter in React.

🚀 Learner's result

By the end of this course, students will not only "know" JavaScript; they will understand why and how each syntax is used to build efficient React components. They will leave with a solid foundation to confidently tackle Hooks (useState, useEffect) and complex state management.

Format: Clean visual presentation, coloured syntax for code, and focus on readability.

Ammar

4.85

(13)

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.

منال

4.85

(13)

📊Microsoft Office: To establish your office skills, manage data via Excel, write professional reports with Word, and prepare impressive presentations with PowerPoint.

📐 AutoCAD: To learn engineering drawing and design two-dimensional and three-dimensional plans with high accuracy and speed.

🛣️ Civil 3D: To learn road design, network design, surveying, and quantity surveying in a scientific and practical way

Aya

4.85

(13)

You have a kid that's interested in programming?? Set up a class for him with me. Aya a software engineer turned teacher. I was a software engineer for 3 years before I joined the teaching industry and I currently teach computer science in Chichester College in United Kingdom. I want to advocate for computer science and help familiarise kids at a young age with programming in Python.

Send me a message let's chat about what you want your kid to learn and what I can offer! :)