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Since December 2024
Instructor since December 2024
Translated by GoogleSee original
Cybersecurity, practical work, practice exams, etc.
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From 23 € /h
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1 Discover the pillars of Cybersecurity
2 Identify terminology related to Cybersecurity
3 Understand the different postures of Cybersecurity
4 Understanding the term Cybersecurity,
5 Identify Cybersecurity terminologies,
6 Know the tactics, techniques and procedures used by attackers,
7 Practical workshops
Extra information
RAS
Location
location type icon
Online from Morocco
About Me
Hello,

I have been passionate about computers for over 20 years. With two decades of teaching experience, I have had the privilege of supporting learners of all ages and levels in developing their computer skills and achieving their professional and personal goals.

Computer science is an essential skill today, opening the door to countless opportunities. Whether you want to learn programming, website design, data analysis, or complex problem-solving, I'm here to guide you every step of the way.
Education
PhD in Computer Science (Artificial Intelligence), Master in E-commerce, Python Certified, Adobe Certified, Microsoft Certified, Several Scientific Publications,
Experience / Qualifications
20 years of experience in computer teaching.
Proven methods suitable for all levels.
Personalized support to help you achieve your goals.
A passion for passing on skills that make a difference.
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
90 minutes
The class is taught in
French
Arabic
English
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
Description:
Get started with web development and learn how to create modern applications. This course takes you from the basics (HTML/CSS) to advanced concepts (security, APIs).

Goals :

Master HTML, CSS and JavaScript.
Understand the basics of authentication and web services.
Explore the concepts of security and load testing.
Course methods and format:

Video course: Creation of interactive mini-web projects.
Flexibility: Adapted to specific needs (beginner or advanced).
For who ?
Students, budding developers or professionals wishing to get started in the web.
Read more
Description:
This course is a comprehensive introduction to database management, including design, administration, and integration into applications.

Goals :

Understand relational models and the use of the SQL language.
Create and administer efficient and secure databases.
Integrating foundations into modern applications.
Course methods and format:

Video courses: Guided practice on tools like MySQL or PostgreSQL.
Flexibility: Exercises adapted to your specific projects.
For who ?
Students, developers or professionals wishing to master databases.
Read more
Show more
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Whether you've never written a line of code or you're a student who needs to pass a programming course, this is a practical, no-fluff introduction that gets you writing real code from session one.
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Experienced and patient teacher of logic for computer science.

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Logic
The sciences presuppose a certain standard of rationality. An ability to distinguish between correct reasoning and claims that do not follow from the assumptions. In this class we study the basic principles of logic and apply mathematical techniques to the study thereof.
Topics include:
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A formal language is an abstraction of general characteristics of programming languages. Such a languages consists of a set of symbols together with some rules to determine whether a string made up out of those symbols is a member of the language.

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Regular expressions
Regular grammar, context-sensitive grammar
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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.

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In today's rapidly evolving technological landscape, **Python programming** has emerged as one of the most **critical skill sets** for professionals across industries. With applications spanning web development, data science, artificial intelligence, automation, and more, Python continues to dominate as the **language of choice** for developers and organizations worldwide. This proposal outlines a comprehensive Python course designed and delivered by **Amr**, a developer and instructor with over **20 years of experience** in the field. The course combines fundamental programming concepts with practical, real-world applications, ensuring students gain not just theoretical knowledge but **marketable skills** that align with current industry demands. By leveraging cutting-edge teaching methodologies and extensive professional experience, this course offers an unparalleled learning opportunity for aspiring programmers and experienced developers alike.

## 1 Introduction to Python Programming

Python has established itself as a **powerhouse programming language** across various domains, from web development and data analysis to artificial intelligence and automation. As of 2025, the demand for Python skills continues to soar, with industry giants like Cisco, IBM, and Google leveraging its capabilities for their projects . Python's dominance in the technology sector is undeniable – it remains the **most requested programming language** in job postings across multiple industries, including finance, healthcare, technology, and entertainment.

The language's popularity stems from several key factors: its **user-friendly syntax** that resembles natural English, making it exceptionally accessible for beginners; its **versatile nature** that supports multiple programming paradigms; and its **extensive ecosystem** of libraries and frameworks that simplify complex programming tasks. Python's cross-platform compatibility ensures code runs seamlessly on Windows, macOS, and Linux environments, while its open-source nature has fostered a massive community of contributors who continuously expand its capabilities . These attributes make Python not just a programming language but a **comprehensive toolset** for solving diverse computational problems.

For professionals looking to future-proof their careers, Python offers **exceptional value**. According to industry data, Python developers in the United States earn an average of **$116,028 per year**, reflecting the high market demand for these skills . Beyond financial rewards, Python proficiency opens doors to cutting-edge fields like machine learning, natural language processing, and data analytics – domains that are shaping the future of technology across industries.

## 2 Course Overview & Learning Objectives

### 2.1 Course Philosophy
This Python programming course is designed with a **practice-oriented approach** that emphasizes hands-on learning and real-world application. Unlike traditional programming courses that focus heavily on theory, this program balances conceptual understanding with **practical implementation**, ensuring students develop the skills needed to solve actual business problems. The curriculum is structured to build proficiency gradually, starting with fundamental concepts and progressing to advanced applications, with each module incorporating **project-based learning** components.

### 2.2 Key Learning Objectives
Upon successful completion of this course, students will be able to:

- **Demonstrate proficiency** in core Python programming concepts including data structures, control flow, functions, and file handling
- **Develop functional applications** using Python for various domains including web development, data analysis, and automation
- **Implement object-oriented programming** principles to create modular, maintainable code
- **Utilize popular Python libraries** such as Pandas, NumPy, and BeautifulSoup for specialized tasks
- **Integrate with databases** and web APIs to create full-stack applications
- **Apply debugging and testing** techniques to ensure code quality and reliability
- **Build portfolio-worthy projects** that demonstrate marketable skills to potential employers


## 3 Instructor Qualifications & Experience

### 3.1 Professional Background
**Amr** brings an exceptional **twenty-year track record** of development and instruction experience to this Python course. His extensive background encompasses both corporate training and software development, providing a unique blend of pedagogical expertise and practical knowledge. With credentials including a **Bachelor of Computer Science and Management Technology** from Modern Academy and a **Computer Science Diploma** from Arab Academy for Science and Technology, Amr possesses the academic foundation to complement his extensive professional experience.

His career demonstrates **progressive responsibility** and expertise across multiple programming languages and frameworks. Beginning as a technical instructor at renowned institutions including NewHorizons, Knowlogy, and Informatica, he quickly established himself as a developer at Microtech and ITS, where he worked on enterprise-level systems including **ERP and banking applications**. This combination of education and hands-on development experience creates an ideal foundation for teaching programming concepts with both theoretical rigor and practical relevance.

### 3.2 Industry Client Portfolio
Amr's exceptional teaching credentials are further enhanced by his impressive roster of **corporate clients**, which includes some of the world's most recognized brands:

- **Technology Leaders**: Microsoft, IBM, Siemens, Vodafone, and Telecom Egypt
- **Financial Institutions**: National Bank of Egypt, NSGB, CIB, and Central Bank of Egypt
- **Global Consumer Brands**: Pepsi, Coca-Cola, Nestlé, Cadbury, and Americana
- **Industrial Conglomerates**: Chrysler, Valeo, 3M, ABB, and BP (British Petroleum)
- **Government Entities**: Libya Government IT Department, Sudan Army Officers, Egyptian Airports Company

This diverse client experience has provided Amr with **unparalleled insight** into how Python is applied across different industries and organizational contexts. His exposure to various business domains allows him to teach Python not as an abstract academic exercise but as a **practical tool** for solving real business problems.

### 3.3 Teaching Methodology
Amr employs a **learner-centered approach** that emphasizes interactive engagement and practical application. His teaching philosophy is based on the principle that programming is best learned through doing, rather than passive listening. Each concept is introduced through **clear explanations** followed immediately by hands-on exercises that reinforce learning. He adapts his pace and approach based on student comprehension, ensuring no one is left behind while maintaining challenging content for advanced learners.

*Table: Instructor's Recent Training Engagements (2023-2025)*

| **Year** | **Corporate Clients** | **Training Centers** | **Technologies Covered** |
|----------|-----------------------|----------------------|--------------------------|
| **2023** | International Finance Corporation, Raya Integration | Raya Academy, IT-Egypt | VBA, Office Automation, Web Technologies, Software Fundamentals with C#, SQL Server Database Design and Querying, Introduction to .NET Core Framework, Building ASP.NET Core Web API, Front-End Development Basics (HTML, CSS, JavaScript, TypeScript), Advanced Front-End Development with Angular, Integration and Deployment |
| **2024** | 3M, Pepsi | NewHorizons, Radio & Television Institute, Informatics (Lebanon), Total-Tech (KSA), Global Business Star (USA) | SQL Query (20761), SQL Development (20762), SQL Admin (20764,20765), Tabular, MQL5, ASP.NET Core MVC Web Applications (20486), Programming in C# (20483), Programming in HTML5 with JavaScript and CSS3 (20480), LINQ, EF (Entity Framework) |
| **2025** | Siemens, Vodafone | YAT, Future University | Full Stack Development, Data Analysis |

## 4 Detailed Course Curriculum

### 4.1 Module Breakdown
The Python course is structured into **eight comprehensive modules** that systematically build programming proficiency from foundation to advanced application:

1. **Python Fundamentals** (10 hours): Syntax, variables, data types, operators, and basic input/output operations. Students will write their first programs and understand how Python interprets and executes code.

2. **Control Structures & Functions** (15 hours): Conditional statements (if/elif/else), loops (for/while), function definition, parameters, return values, and scope. Emphasis on writing clean, reusable code.

3. **Data Structures** (20 hours): Lists, tuples, dictionaries, sets, and their appropriate applications. Includes comprehensive exercises on data manipulation and storage.

4. **Object-Oriented Programming** (20 hours): Classes, objects, inheritance, polymorphism, and encapsulation. Students will learn to structure code using OOP principles for better maintainability.

5. **File Handling & Modules** (10 hours): Reading/writing files, exception handling, importing modules, and creating custom modules. Practical applications for data persistence.

6. **Web Development with Python** (25 hours): Introduction to Flask/Django frameworks, REST APIs, and basic front-end integration. Students will build a functional web application.

7. **Data Analysis & Visualization** (25 hours): Using Pandas for data manipulation, NumPy for numerical computing, and Matplotlib/Seaborn for visualization. Real-world datasets will be used for analysis.

8. **Introduction to Automation & Scripting** (15 hours): Applying Python to automate repetitive tasks, web scraping with BeautifulSoup, and working with APIs.

### 4.2 Practical Projects
The curriculum includes **five portfolio projects** that allow students to apply their learning:

1. **Data Analysis Project**: Analyzing real business data to extract insights and create visualizations
2. **Web Application Project**: Building a fully functional web application with database integration
3. **Automation Script**: Creating a practical tool to automate a repetitive computer task
4. **API Integration Project**: Connecting to external services and processing returned data
5. **Final Capstone Project**: A comprehensive application that demonstrates mastery of course concepts

### 4.3 Python in Marketing Analytics
A special section of the course will focus on **Python applications in digital marketing**, covering how Python can be used for marketing automation, data analysis, and operations . Students will learn:

- **Working with APIs** to connect different software tools and automate marketing workflows
- **Web scraping** to gather data from web pages for content analysis and competitive intelligence
- **Text analysis** for sentiment analysis, content optimization, and customer feedback processing
- **Data analysis** for marketing analytics using Pandas and visualization libraries
- **Technical SEO** applications using Python libraries like advertools and EcommerceTools

This specialized content demonstrates Python's versatility beyond traditional programming roles, showing its value in business functions like marketing where data skills are increasingly crucial.

## 5 Training Methodology & Delivery

### 5.1 Interactive Learning Approach
This Python course employs a **multimodal teaching methodology** that accommodates diverse learning styles while ensuring practical skill development. Each session follows a structured pattern:

1. **Concept Introduction**: Clear explanation of programming concepts with real-world analogies
2. **Live Coding Demonstration**: Step-by-step coding examples that students can follow along
3. **Guided Practice**: Structured exercises with instructor support and immediate feedback
4. **Independent Challenge**: Problem-solving activities that require applying concepts creatively
5. **Code Review**: Collaborative analysis of solutions to identify best practices and improvements

This approach ensures that students not only understand theoretical concepts but develop the **problem-solving mindset** essential for effective programming. The emphasis is always on writing clean, efficient, and maintainable code following industry standards.

### 5.2 Hands-On Labs & Exercises
A distinctive feature of this course is the extensive **hands-on programming practice** integrated throughout the curriculum. Students will spend approximately **60% of course time** actively writing code rather than passively listening to lectures. Practical components include:

- **Coding exercises** for each new concept introduced
- **Mini-projects** that combine multiple concepts into functional applications
- **Debugging challenges** that develop problem-solving skills
- **Code optimization** activities focusing on efficiency and performance
- **Pair programming** sessions to foster collaboration and knowledge sharing

ِSend me if you have any questions,
Regars,
Amr
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The authenticity of an exchange. In a society increasingly rooted in a competitive approach, where automated exchanges with Artificial Intelligence cannot replace the need for human interaction, this is precisely what we lack.
As a lawyer by training and an independent legal consultant, creating "Le Droit" is a breath of fresh air. This private tutoring program is aimed directly at high school students, undergraduate and graduate law students, and more generally at anyone intrigued by the beauty of legal language (you'll discover it soon enough).
Moreover, being currently preparing for the entrance exam to the National School of Magistrates, a solid mastery of legal fundamentals as well as the methods required in legal studies remains.

🎓 It is now necessary to elaborate somewhat on my experience:
- 4 years already dedicated to private lessons (which is significant) via the organization Complétude as well as independently (law, French, science, history and languages).
Regarding the law, and to clarify my point, the teaching that was provided covered and still covers a broad spectrum within the legal field, namely:
- Legal methodology (essential for success: legal essay, practical case study, case commentary and summary note)
- Civil Law (fundamental concepts, contract law, family law, tort law, property law, civil procedure, etc.)
- Criminal Law (fundamental concepts, special criminal law, criminal procedure, criminal law of property and business)
- Administrative Law (fundamental concepts, review of the vast body of existing case law on the subject)
- Labour Law (history of trade unionism, study of the employment contract)
- Public Law (Constitutional Law, Law of Local Authorities, Law of Social Welfare and Action, Constitutional Litigation)
- European Union Law (primary and secondary law, European Union litigation)
- The Law of English-speaking and Spanish-speaking countries
- ... and other subjects directly related to the program of the entrance examination to the National School of the Judiciary.

👋 What about my teaching approach, you might ask?
Beyond this desire for authenticity, it seems particularly crucial to dismantle the prejudices that poison the perception of legal studies. Law can then, and in my humble opinion must, be considered within the delicate balance between discipline and flexibility, between rigor and adaptability.

💬 Wouldn't you be interested?
Please feel free to contact me by message and I remain available to discuss the frequency of classes and their modalities (in-person in Tours, videoconference and possibility of travel if necessary).

In the meantime, Madam/Sir, it would be a real pleasure for me to support you as best I can on your path to success because, as its name suggests: you have the Right 😉
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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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A- TOPICS YOU CAN EXPLORE AND MASTER:
1- PYTHON FOUNDATIONS
• Variables, data types, operators, conditional structures, loops, functions, modules, files, exceptions, and object-oriented programming
• Lists, tuples, dictionaries, sets, comprehensions, debugging, and writing clear, reusable, well-structured code
• Jupyter Notebook, Anaconda, Visual Studio Code, virtual environments, and package management

2 — PROGRAMMING, ALGORITHMS, AND COMPUTER SCIENCE FOUNDATIONS
• Algorithmic thinking, problem decomposition, pseudocode, flowcharts, procedural programming, object-oriented programming, recursion, and modular program design
• Fundamental data structures including arrays, lists, stacks, queues, dictionaries/hash tables, sets, trees, graphs, and their appropriate use
• Searching, sorting, traversal, algorithm efficiency, computational complexity, Big-O notation, debugging, testing, code organization, and problem-solving strategies
• Practical programming exercises ranging from beginner problems to university-level algorithmic and computational challenges

3- DATA PREPARATION AND EXPLORATION
• NumPy and pandas for importing, cleaning, transforming, filtering, grouping, reshaping, and merging data
• Missing values, duplicates, outliers, inconsistent formats, data leakage, and data-quality validation
• Exploratory data analysis using descriptive statistics, Matplotlib, Seaborn, and graphical interpretation

4- MATHEMATICAL FOUNDATIONS
• Linear algebra, vectors, matrices, derivatives, optimization, probability, and statistics
• Loss functions, gradients, distance measures, regularization, likelihood, and model complexity
• Mathematical concepts are explained according to the learner’s level and the requirements of the selected algorithms

5- SUPERVISED MACHINE LEARNING
• Linear and polynomial regression, logistic regression, and regularized models
• k-nearest neighbours, decision trees, random forests, gradient boosting, support vector machines, and Naive Bayes classifiers
• Classification, regression, model assumptions, decision boundaries, feature importance, and interpretation of results

6- UNSUPERVISED LEARNING
• Clustering using k-means, hierarchical clustering, and density-based methods
• Principal component analysis, dimensionality reduction, anomaly detection, and pattern or structure discovery
• Method selection, evaluation of data structure, and interpretation of results without predefined labels

7- MODEL EVALUATION AND IMPROVEMENT
• Training, validation, and test sets; cross-validation; hyperparameter optimization
• Accuracy, precision, recall, specificity, F1 score, ROC–AUC, confusion matrices, MAE, MSE, RMSE, and R2
• Underfitting, overfitting, bias–variance trade-off, class imbalance, feature engineering, feature selection, scaling, and regularization

8- DEEP LEARNING
• Neural-network foundations, activation functions, forward propagation, backpropagation, and gradient descent
• Multilayer perceptrons, convolutional neural networks, recurrent neural networks, and Transformer foundations
• TensorFlow, Keras, or PyTorch depending on the learner’s project and working environment

9- ARTIFICIAL INTELLIGENCE APPLICATIONS
• Natural language processing, text classification, embeddings, sentiment analysis, and foundations of language models
• Computer vision, image classification, fundamental principles of object detection, and image preprocessing
• Recommendation systems, forecasting, anomaly detection, intelligent automation, and decision-support applications

10- GENERATIVE AI AND LARGE LANGUAGE MODELS
• Transformer architecture, tokens, embeddings, attention mechanisms, prompt engineering, Retrieval-Augmented Generation (RAG), and model evaluation
• Use of artificial-intelligence APIs, vector databases, document-retrieval systems, and structured AI-enabled workflows when relevant
• Reliability, hallucinations, bias, privacy, responsible use, and appropriate human validation

11- TOOLS AND LIBRARIES
• Python, NumPy, pandas, Matplotlib, Seaborn, scikit-learn, SciPy, Statsmodels, TensorFlow, Keras, and PyTorch
• Jupyter Notebook, Anaconda, Visual Studio Code, Git, GitHub, SQL, Excel, and Power BI when useful to the project
• Additional libraries may be introduced depending on the selected specialization and dataset

12- PROJECTS, RESEARCH, AND INTERVIEW PREPARATION
• Complete projects covering data preparation, model development, evaluation, interpretation, and presentation of results
• University assignments, dissertations, theses, research projects, portfolio projects, technical interviews, and professional applications
• Code review, debugging, documentation, reproducibility, model comparison, and communication of results

-------------------------------------------------------------------------------------------------------------------------------------------------------------------------------
B- PERSONALIZED TUTORING: LEARNING HOW TO REASON
Machine learning and artificial intelligence become much more accessible when mathematics, algorithms, Python code, data, and real-world applications are clearly connected.

My lessons help you move beyond simply copying code or using models as “black boxes.” You will learn how to define the problem correctly, prepare the data, select an appropriate algorithm, understand how it works, train and evaluate the model, diagnose errors, improve performance, and interpret results rigorously and responsibly.

Each lesson is personalized according to your current level, mathematical background, programming experience, dataset, university work, research project, interview preparation, or professional objective. We begin by identifying your existing knowledge, software environment, expected outcomes, and main conceptual or technical difficulties. We then establish a structured learning plan.

The first lesson combines a discussion of your background, objectives, and tutoring needs; an initial assessment of your current knowledge; personalized planning and organization of future sessions; and a short trial lesson to determine the most effective learning approach.

A typical session may include conceptual explanation, development of mathematical intuition, live coding, guided implementation, model evaluation, technical problem solving, and a concise summary of the next steps.

You may work with your own dataset, university assignment, research project, or professional problem, provided that confidential information is handled appropriately. I can also provide structured examples and datasets suited to your level.

My goal is not simply to help you run an algorithm. It is to help you understand why it is appropriate, how it learns from data, how to evaluate it correctly, why it may fail, and how to build a reliable, interpretable, and scientifically rigorous solution.
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French
The law can seem difficult: technical vocabulary, lengthy texts, demanding legal reasoning. My goal is to make it clear and accessible, in the language that suits you best: Arabic, French, or English.

This course is aimed at law students (Bachelor's, Master's), candidates for competitive exams and professionals who want to strengthen their foundations.

You will learn to :

Understanding the fundamental concepts (civil law, criminal law, business law, constitutional law, etc.)
Mastering the methodology: essay, case commentary, practical case
Use legal terminology in all three languages
Prepare effectively for your exams and competitions

Each session is tailored to your level, your program and your goals.

🇬🇧 English
Law can feel hard: technical vocabulary, long texts and demanding legal reasoning. My goal is to make it clear and accessible, in the language that suits you best: Arabic, French or English.

This course is for law students (bachelor's, master's), exam candidates and professionals who want stronger foundations.

You will learn to:

Understand core concepts (civil, criminal, business and constitutional law...)
Master legal method: essays, case comments and case studies
Use legal terminology in all three languages
Prepare effectively for your exams

Each lesson is tailored to your level, your syllabus and your goals.

🇲🇦 Arabic
قد يبدو القانون صعباً: مصطلحات تقنية، نصوص طويلة، وتفكير قانوني دقيق. هدفي هو جعله واضحاً وسهلاً، باللغة التي تناسبك: الفرنسية أو الإنجليزية.

هذا الدرس موجه لطلبة القانون (الإجازة والماستر)، والمترشحين للمباريات، والمهنيين الراغبين في تقوية معارفهم.

ستتعلم:

فهم المدني، الجنائي، قانون الأعمال، الدستوري...)
Use: الحالات العملية
استعمال المصطلحات القانونية باللغات الثلاث
التحضير الجيد للامتحانات والمباريات

كل حصة مكيفة حسب مستواك وبرنامجك وأهدافك.
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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
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Microsoft Excel is a powerful Microsoft corporation application that helps one do various mathematical, statistical and logic operations on data sets. It's a powerful tool for data analysis.

In this lesson you will be introduced to Microsoft Excel, it's importance and the basic features of the Microsoft Excel user interface.
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I am a student in the Franco-British Business Law Master's program (M1 level). I specialized in business law early on and have studied various aspects of French commercial law. My strengths lie in preparing practical cases and writing legal commentaries.
Feel free to contact me!
Madeleine
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Contact Hassane
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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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Python is the most in-demand programming language in the world right now — and one of the easiest to learn with the right guidance.
Whether you've never written a line of code or you're a student who needs to pass a programming course, this is a practical, no-fluff introduction that gets you writing real code from session one.
What we can cover depending on your goals:

Python fundamentals: variables, loops, functions, data structures
- Object-oriented programming (OOP)
- Data manipulation with pandas and NumPy
- Introduction to machine learning with scikit-learn
- Database management with SQL
- C and Java upon request
- MATLAB and R available for engineering/science students

Why learn with me?
I'm not a student teaching on the side — I'm a professional engineer who uses Python daily for data analysis, modeling, and automation. I know exactly which concepts matter in the real world and which ones you can skip for now.
Sessions are 100% personalized: I adapt the pace, the examples, and the exercises to your background and your goal — whether that's passing your university exam, building a project, or landing a job.
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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 and patient teacher of logic for computer science.

I have taught logic, formal languages and automata theory to undergraduates for six years. My tutoring is adapted to the student's level and goals. Whether you need to learn logic for your studies, or you would simply like to know more about the subject, I will be more than happy to help you improve your understanding and skills.

Logic
The sciences presuppose a certain standard of rationality. An ability to distinguish between correct reasoning and claims that do not follow from the assumptions. In this class we study the basic principles of logic and apply mathematical techniques to the study thereof.
Topics include:
Propositional and Predicate Logic
Syntax and semantics
Natural deduction
Semantic tableaux
Correctness and soundness
Completeness

Formal languages and automata
A formal language is an abstraction of general characteristics of programming languages. Such a languages consists of a set of symbols together with some rules to determine whether a string made up out of those symbols is a member of the language.

Topics include:
Regular languages, context-free languages
Finite automata, pushdown automata, Turing machines
Regular expressions
Regular grammar, context-sensitive grammar
Pumping lemmas for regular and context-free languages
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In this course, you will embark on a linguistic journey to learn Arabic, one of the world’s oldest and most widely spoken languages, or Darija, a dialect of Arabic spoken in Morocco. Whether you’re a beginner or have some knowledge of Arabic, this course will cater to your needs and pace.

The course will cover the basics of Arabic or Darija, including the alphabet, vocabulary, grammar, and sentence structure. You will learn through a variety of interactive methods such as dialogues, exercises, and cultural immersion.

But this course is not just about language learning. It’s about discovering a new world. As you learn Arabic or Darija, you will also explore the rich history, culture, and traditions of the Arab world. This cultural understanding will enrich your language learning experience and give you a deeper appreciation of the Arabic-speaking world.

By the end of this course, you will have a solid foundation in Arabic or Darija and a greater understanding of the cultures where these languages are spoken. You will be able to communicate effectively in a variety of situations, opening up a new world of opportunities for travel, work, or personal enrichment.
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I teach Python specifically for finance and data applications - the kind used in economics, business analytics, and quantitative programs. This isn't a general "learn to code" course; it's built around real financial data, benchmarking, and the workflows you'll actually use in coursework or early career work.

Topics include:
Python fundamentals through a finance lens (data structures, functions, control flow).
Working with financial data and datasets.
Performance benchmarking and writing efficient code.
Applying concepts from Hilpisch's Python for Finance.
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This course introduces students to the fundamentals of Information and Communication Technology (ICT) and its role in modern society. Topics include computer hardware and software, digital communication tools, internet technologies, data management, cybersecurity, and emerging trends. Students will gain practical skills in using productivity software, conducting online research, and understanding the ethical and responsible use of digital resources. The course emphasizes both technical proficiency and digital literacy, preparing learners to confidently navigate and contribute to a technology-driven world.
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In today's rapidly evolving technological landscape, **Python programming** has emerged as one of the most **critical skill sets** for professionals across industries. With applications spanning web development, data science, artificial intelligence, automation, and more, Python continues to dominate as the **language of choice** for developers and organizations worldwide. This proposal outlines a comprehensive Python course designed and delivered by **Amr**, a developer and instructor with over **20 years of experience** in the field. The course combines fundamental programming concepts with practical, real-world applications, ensuring students gain not just theoretical knowledge but **marketable skills** that align with current industry demands. By leveraging cutting-edge teaching methodologies and extensive professional experience, this course offers an unparalleled learning opportunity for aspiring programmers and experienced developers alike.

## 1 Introduction to Python Programming

Python has established itself as a **powerhouse programming language** across various domains, from web development and data analysis to artificial intelligence and automation. As of 2025, the demand for Python skills continues to soar, with industry giants like Cisco, IBM, and Google leveraging its capabilities for their projects . Python's dominance in the technology sector is undeniable – it remains the **most requested programming language** in job postings across multiple industries, including finance, healthcare, technology, and entertainment.

The language's popularity stems from several key factors: its **user-friendly syntax** that resembles natural English, making it exceptionally accessible for beginners; its **versatile nature** that supports multiple programming paradigms; and its **extensive ecosystem** of libraries and frameworks that simplify complex programming tasks. Python's cross-platform compatibility ensures code runs seamlessly on Windows, macOS, and Linux environments, while its open-source nature has fostered a massive community of contributors who continuously expand its capabilities . These attributes make Python not just a programming language but a **comprehensive toolset** for solving diverse computational problems.

For professionals looking to future-proof their careers, Python offers **exceptional value**. According to industry data, Python developers in the United States earn an average of **$116,028 per year**, reflecting the high market demand for these skills . Beyond financial rewards, Python proficiency opens doors to cutting-edge fields like machine learning, natural language processing, and data analytics – domains that are shaping the future of technology across industries.

## 2 Course Overview & Learning Objectives

### 2.1 Course Philosophy
This Python programming course is designed with a **practice-oriented approach** that emphasizes hands-on learning and real-world application. Unlike traditional programming courses that focus heavily on theory, this program balances conceptual understanding with **practical implementation**, ensuring students develop the skills needed to solve actual business problems. The curriculum is structured to build proficiency gradually, starting with fundamental concepts and progressing to advanced applications, with each module incorporating **project-based learning** components.

### 2.2 Key Learning Objectives
Upon successful completion of this course, students will be able to:

- **Demonstrate proficiency** in core Python programming concepts including data structures, control flow, functions, and file handling
- **Develop functional applications** using Python for various domains including web development, data analysis, and automation
- **Implement object-oriented programming** principles to create modular, maintainable code
- **Utilize popular Python libraries** such as Pandas, NumPy, and BeautifulSoup for specialized tasks
- **Integrate with databases** and web APIs to create full-stack applications
- **Apply debugging and testing** techniques to ensure code quality and reliability
- **Build portfolio-worthy projects** that demonstrate marketable skills to potential employers


## 3 Instructor Qualifications & Experience

### 3.1 Professional Background
**Amr** brings an exceptional **twenty-year track record** of development and instruction experience to this Python course. His extensive background encompasses both corporate training and software development, providing a unique blend of pedagogical expertise and practical knowledge. With credentials including a **Bachelor of Computer Science and Management Technology** from Modern Academy and a **Computer Science Diploma** from Arab Academy for Science and Technology, Amr possesses the academic foundation to complement his extensive professional experience.

His career demonstrates **progressive responsibility** and expertise across multiple programming languages and frameworks. Beginning as a technical instructor at renowned institutions including NewHorizons, Knowlogy, and Informatica, he quickly established himself as a developer at Microtech and ITS, where he worked on enterprise-level systems including **ERP and banking applications**. This combination of education and hands-on development experience creates an ideal foundation for teaching programming concepts with both theoretical rigor and practical relevance.

### 3.2 Industry Client Portfolio
Amr's exceptional teaching credentials are further enhanced by his impressive roster of **corporate clients**, which includes some of the world's most recognized brands:

- **Technology Leaders**: Microsoft, IBM, Siemens, Vodafone, and Telecom Egypt
- **Financial Institutions**: National Bank of Egypt, NSGB, CIB, and Central Bank of Egypt
- **Global Consumer Brands**: Pepsi, Coca-Cola, Nestlé, Cadbury, and Americana
- **Industrial Conglomerates**: Chrysler, Valeo, 3M, ABB, and BP (British Petroleum)
- **Government Entities**: Libya Government IT Department, Sudan Army Officers, Egyptian Airports Company

This diverse client experience has provided Amr with **unparalleled insight** into how Python is applied across different industries and organizational contexts. His exposure to various business domains allows him to teach Python not as an abstract academic exercise but as a **practical tool** for solving real business problems.

### 3.3 Teaching Methodology
Amr employs a **learner-centered approach** that emphasizes interactive engagement and practical application. His teaching philosophy is based on the principle that programming is best learned through doing, rather than passive listening. Each concept is introduced through **clear explanations** followed immediately by hands-on exercises that reinforce learning. He adapts his pace and approach based on student comprehension, ensuring no one is left behind while maintaining challenging content for advanced learners.

*Table: Instructor's Recent Training Engagements (2023-2025)*

| **Year** | **Corporate Clients** | **Training Centers** | **Technologies Covered** |
|----------|-----------------------|----------------------|--------------------------|
| **2023** | International Finance Corporation, Raya Integration | Raya Academy, IT-Egypt | VBA, Office Automation, Web Technologies, Software Fundamentals with C#, SQL Server Database Design and Querying, Introduction to .NET Core Framework, Building ASP.NET Core Web API, Front-End Development Basics (HTML, CSS, JavaScript, TypeScript), Advanced Front-End Development with Angular, Integration and Deployment |
| **2024** | 3M, Pepsi | NewHorizons, Radio & Television Institute, Informatics (Lebanon), Total-Tech (KSA), Global Business Star (USA) | SQL Query (20761), SQL Development (20762), SQL Admin (20764,20765), Tabular, MQL5, ASP.NET Core MVC Web Applications (20486), Programming in C# (20483), Programming in HTML5 with JavaScript and CSS3 (20480), LINQ, EF (Entity Framework) |
| **2025** | Siemens, Vodafone | YAT, Future University | Full Stack Development, Data Analysis |

## 4 Detailed Course Curriculum

### 4.1 Module Breakdown
The Python course is structured into **eight comprehensive modules** that systematically build programming proficiency from foundation to advanced application:

1. **Python Fundamentals** (10 hours): Syntax, variables, data types, operators, and basic input/output operations. Students will write their first programs and understand how Python interprets and executes code.

2. **Control Structures & Functions** (15 hours): Conditional statements (if/elif/else), loops (for/while), function definition, parameters, return values, and scope. Emphasis on writing clean, reusable code.

3. **Data Structures** (20 hours): Lists, tuples, dictionaries, sets, and their appropriate applications. Includes comprehensive exercises on data manipulation and storage.

4. **Object-Oriented Programming** (20 hours): Classes, objects, inheritance, polymorphism, and encapsulation. Students will learn to structure code using OOP principles for better maintainability.

5. **File Handling & Modules** (10 hours): Reading/writing files, exception handling, importing modules, and creating custom modules. Practical applications for data persistence.

6. **Web Development with Python** (25 hours): Introduction to Flask/Django frameworks, REST APIs, and basic front-end integration. Students will build a functional web application.

7. **Data Analysis & Visualization** (25 hours): Using Pandas for data manipulation, NumPy for numerical computing, and Matplotlib/Seaborn for visualization. Real-world datasets will be used for analysis.

8. **Introduction to Automation & Scripting** (15 hours): Applying Python to automate repetitive tasks, web scraping with BeautifulSoup, and working with APIs.

### 4.2 Practical Projects
The curriculum includes **five portfolio projects** that allow students to apply their learning:

1. **Data Analysis Project**: Analyzing real business data to extract insights and create visualizations
2. **Web Application Project**: Building a fully functional web application with database integration
3. **Automation Script**: Creating a practical tool to automate a repetitive computer task
4. **API Integration Project**: Connecting to external services and processing returned data
5. **Final Capstone Project**: A comprehensive application that demonstrates mastery of course concepts

### 4.3 Python in Marketing Analytics
A special section of the course will focus on **Python applications in digital marketing**, covering how Python can be used for marketing automation, data analysis, and operations . Students will learn:

- **Working with APIs** to connect different software tools and automate marketing workflows
- **Web scraping** to gather data from web pages for content analysis and competitive intelligence
- **Text analysis** for sentiment analysis, content optimization, and customer feedback processing
- **Data analysis** for marketing analytics using Pandas and visualization libraries
- **Technical SEO** applications using Python libraries like advertools and EcommerceTools

This specialized content demonstrates Python's versatility beyond traditional programming roles, showing its value in business functions like marketing where data skills are increasingly crucial.

## 5 Training Methodology & Delivery

### 5.1 Interactive Learning Approach
This Python course employs a **multimodal teaching methodology** that accommodates diverse learning styles while ensuring practical skill development. Each session follows a structured pattern:

1. **Concept Introduction**: Clear explanation of programming concepts with real-world analogies
2. **Live Coding Demonstration**: Step-by-step coding examples that students can follow along
3. **Guided Practice**: Structured exercises with instructor support and immediate feedback
4. **Independent Challenge**: Problem-solving activities that require applying concepts creatively
5. **Code Review**: Collaborative analysis of solutions to identify best practices and improvements

This approach ensures that students not only understand theoretical concepts but develop the **problem-solving mindset** essential for effective programming. The emphasis is always on writing clean, efficient, and maintainable code following industry standards.

### 5.2 Hands-On Labs & Exercises
A distinctive feature of this course is the extensive **hands-on programming practice** integrated throughout the curriculum. Students will spend approximately **60% of course time** actively writing code rather than passively listening to lectures. Practical components include:

- **Coding exercises** for each new concept introduced
- **Mini-projects** that combine multiple concepts into functional applications
- **Debugging challenges** that develop problem-solving skills
- **Code optimization** activities focusing on efficiency and performance
- **Pair programming** sessions to foster collaboration and knowledge sharing

ِSend me if you have any questions,
Regars,
Amr
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The authenticity of an exchange. In a society increasingly rooted in a competitive approach, where automated exchanges with Artificial Intelligence cannot replace the need for human interaction, this is precisely what we lack.
As a lawyer by training and an independent legal consultant, creating "Le Droit" is a breath of fresh air. This private tutoring program is aimed directly at high school students, undergraduate and graduate law students, and more generally at anyone intrigued by the beauty of legal language (you'll discover it soon enough).
Moreover, being currently preparing for the entrance exam to the National School of Magistrates, a solid mastery of legal fundamentals as well as the methods required in legal studies remains.

🎓 It is now necessary to elaborate somewhat on my experience:
- 4 years already dedicated to private lessons (which is significant) via the organization Complétude as well as independently (law, French, science, history and languages).
Regarding the law, and to clarify my point, the teaching that was provided covered and still covers a broad spectrum within the legal field, namely:
- Legal methodology (essential for success: legal essay, practical case study, case commentary and summary note)
- Civil Law (fundamental concepts, contract law, family law, tort law, property law, civil procedure, etc.)
- Criminal Law (fundamental concepts, special criminal law, criminal procedure, criminal law of property and business)
- Administrative Law (fundamental concepts, review of the vast body of existing case law on the subject)
- Labour Law (history of trade unionism, study of the employment contract)
- Public Law (Constitutional Law, Law of Local Authorities, Law of Social Welfare and Action, Constitutional Litigation)
- European Union Law (primary and secondary law, European Union litigation)
- The Law of English-speaking and Spanish-speaking countries
- ... and other subjects directly related to the program of the entrance examination to the National School of the Judiciary.

👋 What about my teaching approach, you might ask?
Beyond this desire for authenticity, it seems particularly crucial to dismantle the prejudices that poison the perception of legal studies. Law can then, and in my humble opinion must, be considered within the delicate balance between discipline and flexibility, between rigor and adaptability.

💬 Wouldn't you be interested?
Please feel free to contact me by message and I remain available to discuss the frequency of classes and their modalities (in-person in Tours, videoconference and possibility of travel if necessary).

In the meantime, Madam/Sir, it would be a real pleasure for me to support you as best I can on your path to success because, as its name suggests: you have the Right 😉
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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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A- TOPICS YOU CAN EXPLORE AND MASTER:
1- PYTHON FOUNDATIONS
• Variables, data types, operators, conditional structures, loops, functions, modules, files, exceptions, and object-oriented programming
• Lists, tuples, dictionaries, sets, comprehensions, debugging, and writing clear, reusable, well-structured code
• Jupyter Notebook, Anaconda, Visual Studio Code, virtual environments, and package management

2 — PROGRAMMING, ALGORITHMS, AND COMPUTER SCIENCE FOUNDATIONS
• Algorithmic thinking, problem decomposition, pseudocode, flowcharts, procedural programming, object-oriented programming, recursion, and modular program design
• Fundamental data structures including arrays, lists, stacks, queues, dictionaries/hash tables, sets, trees, graphs, and their appropriate use
• Searching, sorting, traversal, algorithm efficiency, computational complexity, Big-O notation, debugging, testing, code organization, and problem-solving strategies
• Practical programming exercises ranging from beginner problems to university-level algorithmic and computational challenges

3- DATA PREPARATION AND EXPLORATION
• NumPy and pandas for importing, cleaning, transforming, filtering, grouping, reshaping, and merging data
• Missing values, duplicates, outliers, inconsistent formats, data leakage, and data-quality validation
• Exploratory data analysis using descriptive statistics, Matplotlib, Seaborn, and graphical interpretation

4- MATHEMATICAL FOUNDATIONS
• Linear algebra, vectors, matrices, derivatives, optimization, probability, and statistics
• Loss functions, gradients, distance measures, regularization, likelihood, and model complexity
• Mathematical concepts are explained according to the learner’s level and the requirements of the selected algorithms

5- SUPERVISED MACHINE LEARNING
• Linear and polynomial regression, logistic regression, and regularized models
• k-nearest neighbours, decision trees, random forests, gradient boosting, support vector machines, and Naive Bayes classifiers
• Classification, regression, model assumptions, decision boundaries, feature importance, and interpretation of results

6- UNSUPERVISED LEARNING
• Clustering using k-means, hierarchical clustering, and density-based methods
• Principal component analysis, dimensionality reduction, anomaly detection, and pattern or structure discovery
• Method selection, evaluation of data structure, and interpretation of results without predefined labels

7- MODEL EVALUATION AND IMPROVEMENT
• Training, validation, and test sets; cross-validation; hyperparameter optimization
• Accuracy, precision, recall, specificity, F1 score, ROC–AUC, confusion matrices, MAE, MSE, RMSE, and R2
• Underfitting, overfitting, bias–variance trade-off, class imbalance, feature engineering, feature selection, scaling, and regularization

8- DEEP LEARNING
• Neural-network foundations, activation functions, forward propagation, backpropagation, and gradient descent
• Multilayer perceptrons, convolutional neural networks, recurrent neural networks, and Transformer foundations
• TensorFlow, Keras, or PyTorch depending on the learner’s project and working environment

9- ARTIFICIAL INTELLIGENCE APPLICATIONS
• Natural language processing, text classification, embeddings, sentiment analysis, and foundations of language models
• Computer vision, image classification, fundamental principles of object detection, and image preprocessing
• Recommendation systems, forecasting, anomaly detection, intelligent automation, and decision-support applications

10- GENERATIVE AI AND LARGE LANGUAGE MODELS
• Transformer architecture, tokens, embeddings, attention mechanisms, prompt engineering, Retrieval-Augmented Generation (RAG), and model evaluation
• Use of artificial-intelligence APIs, vector databases, document-retrieval systems, and structured AI-enabled workflows when relevant
• Reliability, hallucinations, bias, privacy, responsible use, and appropriate human validation

11- TOOLS AND LIBRARIES
• Python, NumPy, pandas, Matplotlib, Seaborn, scikit-learn, SciPy, Statsmodels, TensorFlow, Keras, and PyTorch
• Jupyter Notebook, Anaconda, Visual Studio Code, Git, GitHub, SQL, Excel, and Power BI when useful to the project
• Additional libraries may be introduced depending on the selected specialization and dataset

12- PROJECTS, RESEARCH, AND INTERVIEW PREPARATION
• Complete projects covering data preparation, model development, evaluation, interpretation, and presentation of results
• University assignments, dissertations, theses, research projects, portfolio projects, technical interviews, and professional applications
• Code review, debugging, documentation, reproducibility, model comparison, and communication of results

-------------------------------------------------------------------------------------------------------------------------------------------------------------------------------
B- PERSONALIZED TUTORING: LEARNING HOW TO REASON
Machine learning and artificial intelligence become much more accessible when mathematics, algorithms, Python code, data, and real-world applications are clearly connected.

My lessons help you move beyond simply copying code or using models as “black boxes.” You will learn how to define the problem correctly, prepare the data, select an appropriate algorithm, understand how it works, train and evaluate the model, diagnose errors, improve performance, and interpret results rigorously and responsibly.

Each lesson is personalized according to your current level, mathematical background, programming experience, dataset, university work, research project, interview preparation, or professional objective. We begin by identifying your existing knowledge, software environment, expected outcomes, and main conceptual or technical difficulties. We then establish a structured learning plan.

The first lesson combines a discussion of your background, objectives, and tutoring needs; an initial assessment of your current knowledge; personalized planning and organization of future sessions; and a short trial lesson to determine the most effective learning approach.

A typical session may include conceptual explanation, development of mathematical intuition, live coding, guided implementation, model evaluation, technical problem solving, and a concise summary of the next steps.

You may work with your own dataset, university assignment, research project, or professional problem, provided that confidential information is handled appropriately. I can also provide structured examples and datasets suited to your level.

My goal is not simply to help you run an algorithm. It is to help you understand why it is appropriate, how it learns from data, how to evaluate it correctly, why it may fail, and how to build a reliable, interpretable, and scientifically rigorous solution.
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French
The law can seem difficult: technical vocabulary, lengthy texts, demanding legal reasoning. My goal is to make it clear and accessible, in the language that suits you best: Arabic, French, or English.

This course is aimed at law students (Bachelor's, Master's), candidates for competitive exams and professionals who want to strengthen their foundations.

You will learn to :

Understanding the fundamental concepts (civil law, criminal law, business law, constitutional law, etc.)
Mastering the methodology: essay, case commentary, practical case
Use legal terminology in all three languages
Prepare effectively for your exams and competitions

Each session is tailored to your level, your program and your goals.

🇬🇧 English
Law can feel hard: technical vocabulary, long texts and demanding legal reasoning. My goal is to make it clear and accessible, in the language that suits you best: Arabic, French or English.

This course is for law students (bachelor's, master's), exam candidates and professionals who want stronger foundations.

You will learn to:

Understand core concepts (civil, criminal, business and constitutional law...)
Master legal method: essays, case comments and case studies
Use legal terminology in all three languages
Prepare effectively for your exams

Each lesson is tailored to your level, your syllabus and your goals.

🇲🇦 Arabic
قد يبدو القانون صعباً: مصطلحات تقنية، نصوص طويلة، وتفكير قانوني دقيق. هدفي هو جعله واضحاً وسهلاً، باللغة التي تناسبك: الفرنسية أو الإنجليزية.

هذا الدرس موجه لطلبة القانون (الإجازة والماستر)، والمترشحين للمباريات، والمهنيين الراغبين في تقوية معارفهم.

ستتعلم:

فهم المدني، الجنائي، قانون الأعمال، الدستوري...)
Use: الحالات العملية
استعمال المصطلحات القانونية باللغات الثلاث
التحضير الجيد للامتحانات والمباريات

كل حصة مكيفة حسب مستواك وبرنامجك وأهدافك.
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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
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Microsoft Excel is a powerful Microsoft corporation application that helps one do various mathematical, statistical and logic operations on data sets. It's a powerful tool for data analysis.

In this lesson you will be introduced to Microsoft Excel, it's importance and the basic features of the Microsoft Excel user interface.
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I am a student in the Franco-British Business Law Master's program (M1 level). I specialized in business law early on and have studied various aspects of French commercial law. My strengths lie in preparing practical cases and writing legal commentaries.
Feel free to contact me!
Madeleine
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