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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 July 2017
Instructor since July 2017
Hands on computers programming and general knowledge lessons for beginners or professionals
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From 84 C$ /h
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Either you want to understand how computers work in general, what are the risks of online activities or you want to start or improve your developer skills, I will be happy to help you with that.
I am specialized in Java, GOlang, Docker, Git, HTML, CSS, JS, jQuery and I work in the field for more than 20 years.
I have experience in coaching professionals as well as in introducing children and teenagers to the fascinating world of computers and especially programming.
Location
location type icon
Online from Netherlands
About Me
I am involved with computers and software development both at work and in my private life since more than 20 years. I am passionate about tutoring and sharing my knowledge and experience. I worked with students of various ages teaching them language, math, Office applications and software development.
I have solid knowledge of Golang, Javascript, Java, Docker, Kubernetes, Linux, Bash, Git, Gitlab, Jenkins.
Education
I studied extensively mathematics and physics in high school. I have a Bachelor in Computer Science from the Polytechnic University of Bucharest. I learned English at school and Spanish, German and Italian on my own.
Experience / Qualifications
Software developer and team leader. I am Docker Certified Associate and lead a devops team. I use Golang, Java and Javascript to write software for me and my clients.
I worked in many companies and with various cultures. As a tutor I always managed to help my students pass their exams with excellence as well as their fears of computers.
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
Spanish
Romanian
German
Reviews
Availability of a typical week
(GMT -04:00)
New York
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
Go (Golang) is a great option either as your first programming language or as a next step in your already established developer carrier.
Some of its concepts and idioms might seems difficult to grasp but with the right guidance you will discover that they make sense and they make development really fun and easy.
I am happy to share with you my passion for Go so just send me a message and let's start!
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Docker is an essential tool for any developer nowadays. It allows flexibility and speeds up development.
Whether you would like to start learning containerization or you would like to take your knowledge to the next level, I can help you. Docker is a great tool to not only deliver software but also to play around with different technologies and test multiple releases without burdening your local environment.
Read more
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Most kids think coding is for "smart kids" or "future programmers."
It's not. Coding is how real people solve real problems.
In this class, we skip the theory. Your child creates real things.

What they'll do:
✓ Build real projects in Scratch: a working game, an interactive animation, a story they coded
✓ Program virtual robots: solve real-world challenges (navigate a maze, automate a task, build a system)
✓ Create in Minecraft Education: design worlds, automate constructions, solve logic problems
✓ Experiment with different languages: not just learn "the right way," but understand that there are many ways to think about a problem
✓ Collaborate and share: work with other kids, get feedback, improve their work
✓ Develop logical thinking: not just for coding, but for anything: solving math problems, science challenges, real-world situations


Why this is different:
We don't teach syntax. We teach how programmers think.
Most children's coding courses say "here's the code, copy it." We teach "what problem are we trying to solve? How could we break it into steps? What options do we have?"
When your child learns to think like a programmer, they can learn any language afterward.

What they take home:
A portfolio of 3–4 completed, working projects. The ability to say "I built this." And the deep understanding that code is a tool to make real things happen.

Format: Online or Barcelona | 60–90 min sessions | Flexible pace, no prior experience needed
For curious 8-12 year olds who want to build.
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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
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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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doctoral student in engineering sciences provides support courses in analog and digital electronics at any DEUG level and engineering schools. having scientific and technical knowledge, three years of experience in the field of teaching, pedagogy and a sense of listening and analysis, I am able to help pupils and students and train them in the chapters of which they are having difficulty. for more info please contact me
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Python is a very powerful and multi purpose tool. Image analysis, data analysis. Do you want to create your own software?
Do you want to manage your own hardware?
For who may want to learn Python or need help for a project I would gladly help you with that!
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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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Experienced Teacher – Mathematics, Statistics & Computer Science

With more than 10 years of experience, I support pupils and students from middle school to university, as well as candidates for competitive exams (BCE, ECRICOME, TAGE MAGE, IAE MESSAGE, etc.).

Courses offered:

Mathematics (academic support, in-depth study, exam/competition preparation)
Applied Statistics & Probability
Computer science: Python, SQL, VBA, Data Mining
Methodological coaching (organization, efficiency, self-confidence)

Method: progressive and personalized approach, based on a diagnostic assessment, targeted exercises and regular monitoring to ensure lasting progress.

In-person or online teaching – individual or small group lessons.

Strengths:
More than 10 years of experience
Concrete results (students admitted to the best schools)
Clear, structured and motivating teaching

Prices adapted according to the level and the package chosen.
First free exchange to assess your needs.

Achieve your goals with quality support
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This course is aimed at non-Arabic speakers wishing to learn Arabic in a simple, progressive and practical way, while discovering Moroccan pronunciation (darija).
It is accessible to all beginner levels, and requires no prior knowledge.
Through an interactive method, you will learn:
The basics of the Arabic alphabet and correct pronunciation.
Essential expressions for everyday communication.
The construction of simple sentences (present, past, future).
Useful vocabulary: family, food, time, travel, emotions...
An introduction to Moroccan Darija, to understand and speak easily with Moroccans.
The course is suitable for:
Adults, students and travellers.
People wishing to discover Moroccan culture.
Learners seeking patient, clear and motivating support.
I provide :
Structured course materials (PDF + exercises).
Audio recordings to improve pronunciation.
Mini real-life scenarios for practice.
Personalized support to progress with confidence.
📚 Simple, clear and effective method
👨‍🏫 Support tailored to your pace
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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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*Goal: To understand artificial intelligence without fear, use it to simplify life, and uncover digital traps.*

### **1: Demystifying Artificial Intelligence (What Exactly Is It?)**

* **Artificial intelligence is not a "movie robot":** The fundamental difference between science fiction and practical reality.
* **How it works (simply):** Imagine a "giant library"; AI has read billions of books and uses them to predict the completion of a sentence or create a new image.
* **Where do we use it now?** The spell checker, Netflix and YouTube suggestions, GPS navigation, and voice assistants such as Siri and Alexa.

---

### **2: Using artificial intelligence to make your life easier**

* **Interacting with artificial intelligence (ChatGPT, Cloud, Gemini):**
* Writing formal emails or complex letters.
* Summarizing long articles or huge documents.
* Plan travel itineraries or create food recipes from ingredients available in the refrigerator.


* **Creativity and Memory:**
* Create creative images for greeting cards (via Midjourney or DALL-E).
Restoring and coloring old family photos.

3: The art of speaking to the machine (the Prompt skill)**

* **Context Style:** Why is the phrase "Give me a cake recipe" less effective than "I have a gluten allergy and I'm having 4 people, give me a simple chocolate cake recipe".
* **Role-taking:** Learn to ask the artificial intelligence to "speak like a tourism expert" or "answer me like a specialized agricultural engineer."

4: Precautions and Critical Thinking (A Survival Guide)**

Digital hallucinations:** Understand that artificial intelligence may confidently present false information (never rely on it for medical or legal advice without verification).
Privacy protection
Do not share sensitive data (ID numbers, passwords, bank details).
Be aware that everything you write may be used to train systems in the future.

Detecting deepfakes:**
How to identify fake photos or videos (examine hand details, strange reflections, or metallic sound).
* The golden rule: Verify by cross-referencing different sources.

5: Ethics and Impact (A Future Perspective)**

Copyright: Who owns the image created by artificial intelligence?
Environmental impact: Water and energy consumption in large data centers.
The future: Will artificial intelligence replace us or will it be an assistant to us?

Additional tip:** Since you are targeting the Gulf region, it is preferable to use terms such as "Digital Transformation" and "Innovation" at the beginning of your presentation, as they are very catchy words for decision-makers there.
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These courses are part of a structured and progressive training in Object-Oriented Programming (OOP) with JavaScript, designed for beginner or intermediate developers who want to understand in depth how the language works, write clearer, more maintainable code and prepare themselves calmly for modern frameworks like React ⚛️.

Object-Oriented Programming is often perceived as complex or abstract.

My goal is simple: to make it logical, concrete, and immediately applicable.

🎯 Training Objectives

Upon completion of this training, you will be able to:

Understanding what Object-Oriented Programming really is (and when to use it)
Create and manipulate objects in JavaScript in a clean and efficient way
Use ES6 classes, constructors, and methods with confidence
Mastering this, the prototype, and the instantiation logic
Apply encapsulation, inheritance, and polymorphism without confusion
Avoiding common mistakes made by OOP beginners
Structure your JavaScript code like a professional developer

📖 Training Plan – Object-Oriented Programming in JavaScript
1. Introduction to Object-Oriented Programming 🧠
Understanding the concept, objectives and benefits of OOP.
2. Procedural Programming vs. OOP
Why unstructured code quickly becomes unmanageable.
3. Objects in JavaScript
Properties, methods and representation of the real world.
4. The keyword this
Understanding the execution context (often poorly understood).
5. Limitations of simple objects
Why duplicating code is a bad idea.
6. Constructive functions
Create multiple objects from the same model.
7. The keyword new
What it's actually doing under the hood.
8. The prototype
Sharing methods and memory optimization.
9. ES6 Classes
Modern syntax and best practices.
10. The builder
Proper initialization of objects.
11. Data Encapsulation
Protect the internal state of objects.
12. Inheritance between classes
Reusing code intelligently.
13. The keyword super
Communication between parent and child in the classroom.
14. Polymorphism
The same behavior, several forms.
15. Composition vs. Inheritance
Choosing the right architecture.
16. Best practices in OOP
Write readable, scalable, and maintainable code.
17. Common mistakes made by beginners
Pitfalls to absolutely avoid.
18. Guided practical exercise
Creation of a concrete class (product, user, etc.).
19. Assessment Quiz (Multiple Choice Questions)
To validate the actual understanding of the concepts.

🛠️ Teaching method: Understand before writing

This training program is based on a progressive and pragmatic approach:
Clear and illustrated explanations
Concrete examples from real projects
Simple but effective exercises
Constant questioning to avoid rote learning
Adaptation to the learner's level and pace
Here, we don't "recite OOP" — we understand it.

🚀 Learner's result

At the end of the training, you will not only know how to write a JavaScript class.
You will know:

1- Why does it exist?
2- When to use it
3- and when not to use it

You will leave with:
a solid understanding of OOP
a cleaner and more professional code
an ideal foundation for learning React, Node.js or any other modern framework
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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- 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

3- 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

4- 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

5- 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

6- 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

7- 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

8- 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

9- 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

10- 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

11- 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 free 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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Whether you're just starting your computer science journey or preparing for university exams, I offer personalized tutoring tailored to your goals and learning style. I can also make the journey intuitive and interesting by teaching some design softwares as Canva and Adobe InDesign.

I hold a Bachelor's degree in Computer Science Engineering and have experience applying technical problem-solving in international organizations alongside my work in technology, accessibility, and data analysis.

I can help with:
Microsoft Excel, Powerpoint and Word
Canva, and Creative Designing using Adobe
Programming fundamentals
Python
SQL and databases
Data structures and algorithms
Object-oriented programming
Software engineering concepts
Computer networks
Information security fundamentals
Operating systems
Exam preparation
Assignments and projects
Problem-solving and coding practice

My teaching approach focuses on building a strong understanding of concepts rather than memorization. I adapt every lesson to the student's pace, using practical examples and interactive exercises to make complex topics easier to understand. We learn together by solving creative problems, and I am available to support students at any moment of their journey.

Whether you're in school, university, or simply interested in learning programming, I'll help you develop confidence and the analytical thinking skills needed to succeed.
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I'm a working MEP engineer, currently building Python automation for Revit workflows daily - plan checks, model coordination, and repetitive drafting tasks. I teach other engineers, architects, and BIM professionals how to do the same, using pyRevit and real project workflows, not toy examples.

Topics include:
pyRevit fundamentals and setup
Automating repetitive Revit tasks (model checks, plan generation, data extraction)
Writing custom scripts for your firm's specific workflows
Applying Python automation to real MEP/BIM projects
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This class covers Calculus, Linear Algebra, Probability & Statistics, and Discrete Mathematics, built around your specific course material or exam board rather than a generic syllabus. Each session works through core concepts with clear step-by-step explanations, worked examples, and practice problems, moving from the underlying logic of a topic to applying it confidently in exercises and exams. The focus is on understanding why a method works, not just memorizing steps, so concepts stick and transfer to new problems. Sessions can be structured around exam prep, homework support, or strengthening the foundation ahead of a difficult semester — whichever fits your goals best.
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Most kids think coding is for "smart kids" or "future programmers."
It's not. Coding is how real people solve real problems.
In this class, we skip the theory. Your child creates real things.

What they'll do:
✓ Build real projects in Scratch: a working game, an interactive animation, a story they coded
✓ Program virtual robots: solve real-world challenges (navigate a maze, automate a task, build a system)
✓ Create in Minecraft Education: design worlds, automate constructions, solve logic problems
✓ Experiment with different languages: not just learn "the right way," but understand that there are many ways to think about a problem
✓ Collaborate and share: work with other kids, get feedback, improve their work
✓ Develop logical thinking: not just for coding, but for anything: solving math problems, science challenges, real-world situations


Why this is different:
We don't teach syntax. We teach how programmers think.
Most children's coding courses say "here's the code, copy it." We teach "what problem are we trying to solve? How could we break it into steps? What options do we have?"
When your child learns to think like a programmer, they can learn any language afterward.

What they take home:
A portfolio of 3–4 completed, working projects. The ability to say "I built this." And the deep understanding that code is a tool to make real things happen.

Format: Online or Barcelona | 60–90 min sessions | Flexible pace, no prior experience needed
For curious 8-12 year olds who want to build.
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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
verified badge
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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doctoral student in engineering sciences provides support courses in analog and digital electronics at any DEUG level and engineering schools. having scientific and technical knowledge, three years of experience in the field of teaching, pedagogy and a sense of listening and analysis, I am able to help pupils and students and train them in the chapters of which they are having difficulty. for more info please contact me
verified badge
Python is a very powerful and multi purpose tool. Image analysis, data analysis. Do you want to create your own software?
Do you want to manage your own hardware?
For who may want to learn Python or need help for a project I would gladly help you with that!
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! :)
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Experienced Teacher – Mathematics, Statistics & Computer Science

With more than 10 years of experience, I support pupils and students from middle school to university, as well as candidates for competitive exams (BCE, ECRICOME, TAGE MAGE, IAE MESSAGE, etc.).

Courses offered:

Mathematics (academic support, in-depth study, exam/competition preparation)
Applied Statistics & Probability
Computer science: Python, SQL, VBA, Data Mining
Methodological coaching (organization, efficiency, self-confidence)

Method: progressive and personalized approach, based on a diagnostic assessment, targeted exercises and regular monitoring to ensure lasting progress.

In-person or online teaching – individual or small group lessons.

Strengths:
More than 10 years of experience
Concrete results (students admitted to the best schools)
Clear, structured and motivating teaching

Prices adapted according to the level and the package chosen.
First free exchange to assess your needs.

Achieve your goals with quality support
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This course is aimed at non-Arabic speakers wishing to learn Arabic in a simple, progressive and practical way, while discovering Moroccan pronunciation (darija).
It is accessible to all beginner levels, and requires no prior knowledge.
Through an interactive method, you will learn:
The basics of the Arabic alphabet and correct pronunciation.
Essential expressions for everyday communication.
The construction of simple sentences (present, past, future).
Useful vocabulary: family, food, time, travel, emotions...
An introduction to Moroccan Darija, to understand and speak easily with Moroccans.
The course is suitable for:
Adults, students and travellers.
People wishing to discover Moroccan culture.
Learners seeking patient, clear and motivating support.
I provide :
Structured course materials (PDF + exercises).
Audio recordings to improve pronunciation.
Mini real-life scenarios for practice.
Personalized support to progress with confidence.
📚 Simple, clear and effective method
👨‍🏫 Support tailored to your pace
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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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*Goal: To understand artificial intelligence without fear, use it to simplify life, and uncover digital traps.*

### **1: Demystifying Artificial Intelligence (What Exactly Is It?)**

* **Artificial intelligence is not a "movie robot":** The fundamental difference between science fiction and practical reality.
* **How it works (simply):** Imagine a "giant library"; AI has read billions of books and uses them to predict the completion of a sentence or create a new image.
* **Where do we use it now?** The spell checker, Netflix and YouTube suggestions, GPS navigation, and voice assistants such as Siri and Alexa.

---

### **2: Using artificial intelligence to make your life easier**

* **Interacting with artificial intelligence (ChatGPT, Cloud, Gemini):**
* Writing formal emails or complex letters.
* Summarizing long articles or huge documents.
* Plan travel itineraries or create food recipes from ingredients available in the refrigerator.


* **Creativity and Memory:**
* Create creative images for greeting cards (via Midjourney or DALL-E).
Restoring and coloring old family photos.

3: The art of speaking to the machine (the Prompt skill)**

* **Context Style:** Why is the phrase "Give me a cake recipe" less effective than "I have a gluten allergy and I'm having 4 people, give me a simple chocolate cake recipe".
* **Role-taking:** Learn to ask the artificial intelligence to "speak like a tourism expert" or "answer me like a specialized agricultural engineer."

4: Precautions and Critical Thinking (A Survival Guide)**

Digital hallucinations:** Understand that artificial intelligence may confidently present false information (never rely on it for medical or legal advice without verification).
Privacy protection
Do not share sensitive data (ID numbers, passwords, bank details).
Be aware that everything you write may be used to train systems in the future.

Detecting deepfakes:**
How to identify fake photos or videos (examine hand details, strange reflections, or metallic sound).
* The golden rule: Verify by cross-referencing different sources.

5: Ethics and Impact (A Future Perspective)**

Copyright: Who owns the image created by artificial intelligence?
Environmental impact: Water and energy consumption in large data centers.
The future: Will artificial intelligence replace us or will it be an assistant to us?

Additional tip:** Since you are targeting the Gulf region, it is preferable to use terms such as "Digital Transformation" and "Innovation" at the beginning of your presentation, as they are very catchy words for decision-makers there.
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These courses are part of a structured and progressive training in Object-Oriented Programming (OOP) with JavaScript, designed for beginner or intermediate developers who want to understand in depth how the language works, write clearer, more maintainable code and prepare themselves calmly for modern frameworks like React ⚛️.

Object-Oriented Programming is often perceived as complex or abstract.

My goal is simple: to make it logical, concrete, and immediately applicable.

🎯 Training Objectives

Upon completion of this training, you will be able to:

Understanding what Object-Oriented Programming really is (and when to use it)
Create and manipulate objects in JavaScript in a clean and efficient way
Use ES6 classes, constructors, and methods with confidence
Mastering this, the prototype, and the instantiation logic
Apply encapsulation, inheritance, and polymorphism without confusion
Avoiding common mistakes made by OOP beginners
Structure your JavaScript code like a professional developer

📖 Training Plan – Object-Oriented Programming in JavaScript
1. Introduction to Object-Oriented Programming 🧠
Understanding the concept, objectives and benefits of OOP.
2. Procedural Programming vs. OOP
Why unstructured code quickly becomes unmanageable.
3. Objects in JavaScript
Properties, methods and representation of the real world.
4. The keyword this
Understanding the execution context (often poorly understood).
5. Limitations of simple objects
Why duplicating code is a bad idea.
6. Constructive functions
Create multiple objects from the same model.
7. The keyword new
What it's actually doing under the hood.
8. The prototype
Sharing methods and memory optimization.
9. ES6 Classes
Modern syntax and best practices.
10. The builder
Proper initialization of objects.
11. Data Encapsulation
Protect the internal state of objects.
12. Inheritance between classes
Reusing code intelligently.
13. The keyword super
Communication between parent and child in the classroom.
14. Polymorphism
The same behavior, several forms.
15. Composition vs. Inheritance
Choosing the right architecture.
16. Best practices in OOP
Write readable, scalable, and maintainable code.
17. Common mistakes made by beginners
Pitfalls to absolutely avoid.
18. Guided practical exercise
Creation of a concrete class (product, user, etc.).
19. Assessment Quiz (Multiple Choice Questions)
To validate the actual understanding of the concepts.

🛠️ Teaching method: Understand before writing

This training program is based on a progressive and pragmatic approach:
Clear and illustrated explanations
Concrete examples from real projects
Simple but effective exercises
Constant questioning to avoid rote learning
Adaptation to the learner's level and pace
Here, we don't "recite OOP" — we understand it.

🚀 Learner's result

At the end of the training, you will not only know how to write a JavaScript class.
You will know:

1- Why does it exist?
2- When to use it
3- and when not to use it

You will leave with:
a solid understanding of OOP
a cleaner and more professional code
an ideal foundation for learning React, Node.js or any other modern framework
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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- 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

3- 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

4- 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

5- 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

6- 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

7- 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

8- 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

9- 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

10- 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

11- 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 free 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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Whether you're just starting your computer science journey or preparing for university exams, I offer personalized tutoring tailored to your goals and learning style. I can also make the journey intuitive and interesting by teaching some design softwares as Canva and Adobe InDesign.

I hold a Bachelor's degree in Computer Science Engineering and have experience applying technical problem-solving in international organizations alongside my work in technology, accessibility, and data analysis.

I can help with:
Microsoft Excel, Powerpoint and Word
Canva, and Creative Designing using Adobe
Programming fundamentals
Python
SQL and databases
Data structures and algorithms
Object-oriented programming
Software engineering concepts
Computer networks
Information security fundamentals
Operating systems
Exam preparation
Assignments and projects
Problem-solving and coding practice

My teaching approach focuses on building a strong understanding of concepts rather than memorization. I adapt every lesson to the student's pace, using practical examples and interactive exercises to make complex topics easier to understand. We learn together by solving creative problems, and I am available to support students at any moment of their journey.

Whether you're in school, university, or simply interested in learning programming, I'll help you develop confidence and the analytical thinking skills needed to succeed.
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I'm a working MEP engineer, currently building Python automation for Revit workflows daily - plan checks, model coordination, and repetitive drafting tasks. I teach other engineers, architects, and BIM professionals how to do the same, using pyRevit and real project workflows, not toy examples.

Topics include:
pyRevit fundamentals and setup
Automating repetitive Revit tasks (model checks, plan generation, data extraction)
Writing custom scripts for your firm's specific workflows
Applying Python automation to real MEP/BIM projects
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This class covers Calculus, Linear Algebra, Probability & Statistics, and Discrete Mathematics, built around your specific course material or exam board rather than a generic syllabus. Each session works through core concepts with clear step-by-step explanations, worked examples, and practice problems, moving from the underlying logic of a topic to applying it confidently in exercises and exams. The focus is on understanding why a method works, not just memorizing steps, so concepts stick and transfer to new problems. Sessions can be structured around exam prep, homework support, or strengthening the foundation ahead of a difficult semester — whichever fits your goals best.
Good-fit Instructor Guarantee
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