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Since November 2020
Instructor since November 2020
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Computer courses, computer help, initiation to programming (Java 8+, C / C ++, Objective C, HTML, PHP, Javascript)
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From 51 $ /h
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I am passionate about information systems and new technologies. I have the chance to develop my skills within the companies where I work and also through technological monitoring. Currently working at BNP CARDIF, I would know with the experience that I have already acquired as a professional and pedagogical speaker find the words and the strategy adapted to meet your needs and those of your children who are in exam class. .
Extra information
In order to offer you a better experience during my classes, I make course materials that I send you before each session so that you can soak up them.
Location
location type icon
Online from France
About Me
I am passionate about information systems and new technologies. I have the chance to develop my skills within the companies where I work and also through technological monitoring. Currently working at BNP CARDIF, I am also passionate about the teaching profession and I do not hesitate to exercise it at the slightest opportunity.
Education
Ingésup
Name of diploma: Master 2 Expert in Computer Science and Information Systems
Field of Study: Computer and Information Sciences and Related Services
Years attended or expected graduation date 2017 - 2018

Mohamed Premier University of Oujda
Name of degree: Master 2 Field of study: Marketing and Communication
Years attended or expected graduation date 2015 - 2016

Private Higher School of Engineering and Technology - ESPRIT
Degree name: Engineering degree Field of study: Telecommunications and embedded and mobile systems
Years attended or expected graduation date 2010 - 2015
Experience / Qualifications
=> IT Project Manager
Company name BNP Paribas Cardif
Dates of employment Jul. 2019 - Present
Duration of employment 1 year 5 months
Location Paris region, France
• Costing of the need
• Piloting and management of multiple projects in parallel
• Parameterization and design
• Support on the different applications
• Validation of test plans
• Establishment of Deployment Plans
• Start of production
• Systems administration
• Planning
• Budget management
• Development via Tibco


=> Java / Java EE, Spring & DevOps Consultant
Company name Actemium France
Dates of employment 2018 - June 2019
Duration of employment7 months
Location Paris region, France
Tasks: Integration into the team organized according to the AGILE SCRUM method
Participation in Poker Planning meetings
Code review during Merge request
Participation in the delivery phases (delivery of the different versions of the dev and master branches)
CI & CD with Jenkins
Source code quality analysis with Sonar
Development of changes requested by the customer.
Using Git Tools

=> Java EE Study and Development Engineer
Company name Klee Group
Dates of employment. 2017 - Sep 2018
Duration of employment11 months
Location La Boursidière Business Center, Le Plessis Robinson
Integration into the team organized according to the Agile Scrum methodology:

Participation in costing meetings, planning
Development of multiple features and evolutions throughout the sprints
Data recovery
Reporting and fixing bugs
Management of anomalies and creation of tickets with Jira
Participation in the deployment phases (Pull Request)
Source code versioning management with Stash
Using Git Tools
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
French
English
Availability of a typical week
(GMT -05:00)
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
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-------------------------------------------------------------------------------------------------------------------------------------------------------------------------------
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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


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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?"
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verified badge
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As an aeronautical engineer, I like to share my knowledge and derive satisfaction from it by teaching and motivating others.

I'm used to working with people of different ages. I believe in the importance of segmenting learning, visualizing progress, setting concrete goals and practicing regularly.

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Are you looking for personalized support to succeed in mathematics, physics or computer science? Whether you are a middle school, high school, university student or simply curious to learn, this multidisciplinary program is for you!

💡 Why Choose this Program?
This course offers comprehensive, tailored support to help you:

Strengthen your foundations and fill in your gaps.
Understand theoretical concepts in depth.
Master problem-solving methods.
Develop your computer skills, from introductory to advanced programming.
Prepare effectively for your exams and competitions.
With a human, motivating and caring approach, you will learn at your own pace in a calm and encouraging environment, without pressure or judgment.

📘 Mathematics – For All Levels
Mathematics may seem complex and abstract, but with the right method and clear explanations, it becomes logical and accessible.
This module covers:

Middle school level: Arithmetic, fractions, proportions, basic geometry, statistics.
High school level: Algebra, functions, equations, analytical geometry, probabilities.
Preparation for exams: Brevet, Bac, entrance exams for grandes écoles.
Advanced Mathematics: Differential and integral calculus, matrices, sequences and series for university level.
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Physics allows us to understand the world around us, from the laws of motion to electromagnetic phenomena.
This module will guide you through:

Middle and high school level: Mechanics, electricity, optics, thermodynamics.
University Level: Analytical mechanics, advanced electromagnetism, quantum physics, statistical thermodynamics.
Scientific Methodology: Knowing how to analyze a problem, formulate a hypothesis, apply physical laws and interpret the results.
Practical Applications: Virtual experiences, interactive simulations to better understand theoretical concepts.
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In an increasingly digital world, mastering IT is essential. This module adapts to your level and your objectives:

Introduction to Computers: Understand how a computer works, use office software (Word, Excel, PowerPoint).
Programming Beginner: Learn to code in Python, JavaScript or C/C++ with clear explanations and practical exercises.
Advanced Programming: Optimized algorithms, complex data structures, object-oriented programming.
Project Development: Creation of web applications, automated scripts, simple video games.
Preparation for NSI Exams: Complete support to pass the Digital and Computer Science tests.
🎯 Interactive and Motivating Teaching
Dynamic Online Course: Learn from home with an interactive format using audio and screen sharing.
Method Adapted to Your Pace: Each course is designed according to your level and your objectives.
Practical Exercises and Concrete Projects: To apply theoretical concepts and learn while having fun.
Personalized Monitoring: Regular support to monitor your progress and adapt the program to your needs.
Encouragement and Motivation: A positive approach to building your confidence in your abilities.
🔔 For Who?
This program is aimed at:

Middle school and high school students wishing to strengthen their foundations or aim for excellence.
University students in science or computer science looking to deepen their knowledge.
Candidates for exams and competitions preparing for the Brevet, the Bac, or entrance exams to the grandes écoles.
Passionate self-taught people who want to learn to program or better understand the scientific world.
Adults in professional retraining wishing to acquire IT skills.
🚀 Ready to Succeed?
Join the "🎓 Multidisciplinary Program – 📘 Mathematics, 🔬 Physics & 💻 Computer Science for All Levels!" and benefit from personalized support to achieve your goals. Whether you want to improve your grades, pass your exams or develop programming skills, this program will give you knowledge, confidence and motivation.

Register today and take the first step towards success!
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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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Understanding algorithms is essential for anyone pursuing computer science or programming. In this course, I provide a structured approach to learning algorithms—from fundamental concepts like sorting and searching to advanced techniques such as dynamic programming and graph theory. Whether you're preparing for exams, coding interviews, or aiming to improve your problem-solving skills, this course is designed to build strong algorithmic thinking. Through practical examples and step-by-step explanations, I help students master the logic and techniques needed to write efficient and elegant code.
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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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I teach coding to beginners and intermediate students.
Lessons focus on logic, basic programming, and practical exercises.
Classes are adapted to the student’s pace.
Students can choose between website or mobile app development.Hands on dev
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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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Primary School Teacher. I offer personalized guidance in developing lesson plans and learning activities adapted to current educational regulations. During our sessions, you will learn to structure and write a complete lesson plan, including specific competencies, assessment criteria, core knowledge, methodology, addressing diversity, evaluation, and learning situations. My goal is to help you understand each section so you can independently develop a coherent, rigorous, and high-quality lesson plan.

You will learn to design practical, creative proposals, developing the necessary skills to apply them in the classroom or in competitive examination processes.
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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.
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What if you could think like a hacker, so you can stop one? Let's learn cybersecurity the real way.

I'm a cybersecurity engineer with 3 years of experience and 150+ penetration tests and vulnerability assessments for government, financial, and telecom organizations. I hold CRTP, eWPT, and eJPT certifications, and I'll teach you what actually works in the field. No boring theory dumps, just live, hands-on learning.

You'll learn:

How attackers think: the hacking process from recon to exploitation
Common web attacks like SQL injection and XSS, and how to stop them
Passwords, phishing, and social engineering: why people are the weakest link
Vulnerability scanning and ethical hacking basics with Nmap, Burp Suite, and Nessus
How defenders work: firewalls, SIEM, EDR, and incident response
How to protect yourself, your team, and your business

Perfect for: beginners, career changers, students, developers, IT staff, and anyone curious about ethical hacking or preparing for Security+, CEH, or eJPT.

You'll walk away with a clear understanding of real threats, the skills to spot and fix common vulnerabilities, and a solid foundation for a cybersecurity career.

No experience needed, just curiosity and a computer. Book your first session and let's dive in!
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📊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
Good-fit Instructor Guarantee
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