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Since June 2025
Instructor since June 2025
Translated by GoogleSee original
Full-stack Web Development + Devops/Cloud Computing
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From 16 € /h
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Web development can be overwhelming today with the emergence of so many frameworks and technologies. Fear not! In this course, I'll give you the basics instead of bombarding you with these new frameworks.
Believe me, towards the end you will see that when you learn this logic, any framework will be just an implementation of your own understanding and critical analysis of the new features, based on what you learned with me.
And let's not forget a very important part: DevOps/Cloud Computing, which is now the new hype with AI!
So I invite you to join me and discover what we can accomplish together. It's going to be so much fun! Mini-projects, training on new frameworks, a collaborative space, and most importantly: your personal growth and an enriching experience that will help you enter the world of IT with a vengeance.
Extra information
Computer + passion
Location
location type icon
Online from Morocco
About Me
Abdelghafour - Computer Engineer
Passionate about nature and music, I find web development a way to harmonize creativity and technology. My expertise focuses on integrating emerging technologies—Artificial Intelligence, DevOps, and Cloud Computing—at the heart of modern web development.
My teaching philosophy
I firmly believe that learning by doing is the key to success. My method is based on building concrete projects that give my students that incomparable pride: that of creating something with their own hands.
What motivates me

Share my passion for innovative technologies
Creating meaningful solutions together
Transmit the confidence that comes from technical mastery
Cultivating exchange and mutual learning

Each class is a collaborative adventure where we explore, experiment, and build together. Because beyond technical skills, it's this passion for discovery and pride in a job well done that I want to pass on to each student.
“Learn by creating, grow by sharing”
Education
🎓 Training & Academic Career

State Engineer in Computer Science (5th year) - ENSA Marrakech
DUT Networks & Telecommunications - EST Essaouira

🏆 Certifications & Distinctions

Oracle Cloud Infrastructure (OCI) - Certified
Oracle AI Professional - LangGraph & LLM Specialization
Finalist - AI for Sustainable Cities (IRCAE x GITEX Africa 2025)
Experience / Qualifications
💡 Innovative Projects Completed

AI-Assisted Coding Platform with RAG System (End of Year Project)
Sentiment analysis app + automatic book reading
ChatGPT Clone with Focus on Advanced User Experience
Complete DevOps pipeline for AWS deployment on NextWork

Passionate about nature and music, I find web development a way to harmonize creativity and technology. My expertise focuses on integrating emerging technologies—Artificial Intelligence, DevOps, and Cloud Computing—at the heart of modern web development.
My teaching philosophy
I firmly believe that learning by doing is the key to success. My method is based on building concrete projects that give my students that incomparable pride: that of creating something with their own hands.
🔧 Methods & Tools mastered

Project management: Trello, Notion, Agile methods
DevOps: CI/CD pipelines, automated deployment
Cloud: AWS, Oracle Cloud Infrastructure
AI: RAG Systems, LLM, LangGraph

What motivates me

Share my passion for innovative technologies
Creating meaningful solutions together
Transmit the confidence that comes from technical mastery
Cultivating exchange and mutual learning

Each class is a collaborative adventure where we explore, experiment, and build together. Because beyond technical skills, it's this passion for discovery and pride in a job well done that I want to pass on to each student.
“Learn by creating, grow by sharing”
Age
Preschool children (4-6 years old)
Children (7-12 years old)
Teenagers (13-17 years old)
Adults (18-64 years old)
Student level
Beginner
Intermediate
Advanced
Duration
90 minutes
The class is taught in
French
English
Arabic
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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# Class Title
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# Class Description
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Clear and effective teaching: The explanations are adapted to your level to facilitate understanding.
Regular and motivating monitoring: Each progress is closely monitored to encourage and guide you throughout your journey.
Positive and caring method: Learn without stress and gain confidence thanks to caring support.
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Mathematics can sometimes seem complicated, but with the right explanations, it becomes logical and accessible.
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Middle School Level: Arithmetic, fractions, basic geometry, statistics.
High school level: Algebra, functions, equations, analytical geometry, probabilities.
Preparation for exams: Brevet, Bac, entrance exams for grandes écoles.
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This module covers:

Middle and high school level: Mechanics, electricity, optics, thermodynamics.
University Level: Analytical mechanics, advanced electromagnetism, quantum physics, statistical thermodynamics.
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This module adapts to your level:

Introduction to Computers: Understand how a computer works, master office software.
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Advanced Programming: Complex algorithms, advanced 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 "🎯 Tailor-made Success – 📘 Private Lessons in Maths, 🔬 Physics & 💻 Computer Science!" 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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This course is designed for anyone interested in learning data science using Python. It provides a hands-on introduction to fundamental data analysis tools such as NumPy, pandas, matplotlib, and seaborn. You'll learn how to manipulate datasets, create visualizations, and lay the foundations for statistical analysis and machine learning.

The course combines theory and practical exercises for effective, practical progress. No prior programming experience is necessary: we'll start with the basics to build solid, usable skills quickly.
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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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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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This module is a crucial step for any web developer wishing to move from simple DOM manipulation to mastering modern frameworks. The objective is clear: to understand the "invisible foundations" of the language in order to write shorter, more readable code and, above all, be ready to code professionally in React.

🎯 Training Objectives

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

📖 Detailed program content

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

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

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

Data manipulation:

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

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

Code robustness:

1- Managing default parameter values.

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

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

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

🛠️ Teaching method: "Learning by doing"

This course is not just about theory. It includes:

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

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

🚀 Learner's result

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

Format: Clean visual presentation, coloured syntax for code, and focus on readability.
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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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📊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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# Class Title
**Information Technology & Web Development – From Fundamentals to Real-World Projects**

# Class Description
Explore the world of Information Technology and Web Development through practical, beginner-friendly lessons designed to build real technical skills.

This class introduces students to essential IT concepts, programming fundamentals, web technologies, and the process of creating modern websites and applications.

Topics include:
- **IT Fundamentals:** Computer systems, operating systems, networks, and troubleshooting.
- **Programming Fundamentals:** Problem-solving, logical thinking, algorithms, and coding principles.
- **Web Development:** HTML, CSS, JavaScript, and responsive website development.
- **Backend Development:** Introduction to servers, APIs, databases, and application logic.
- **Practical Projects:** Build websites and small applications while learning how real software is developed.
- **Technology & Career Skills:** Development tools, debugging, version control, and good programming practices.

Whether you're completely new to technology or looking to strengthen your existing skills, the goal is to make complex concepts easier to understand through clear explanations, hands-on exercises, and practical examples.

**My teaching approach:** Learn by understanding, practice by building, and improve by solving real problems.
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Java is one of the most widely used languages in the world, both in business and in higher education. But learning Java is not just about writing code that "works": it's about writing code that is readable, reliable, and easy to maintain.

As a master's student in computer science, specializing in software quality, I offer a practical course that teaches you the language while giving you the good habits of professional developers from the start.
Good-fit Instructor Guarantee
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