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Since October 2026
Instructor since October 2026
Git Fundamentals: Version Control Essentials (Github / Gitlab)
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From 15 C$ /h
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Learn how to track code changes and manage projects using Git, with practical exercises from the first lesson.
Basic curriculum
- Git and version control concepts
- Repositories and git init
- git add, git commit and git status
- Viewing history with git log
- Branches and merging
- GitHub basics: push, pull and clone
- Resolving simple merge conflicts
Location
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Online from Morocco
About Me
I am a Software Engineer working at a leading technology company in Morocco, with an engineering degree in Software Engineering and a passion for programming and knowledge sharing.

I teach programming in a practical, structured, and beginner-friendly way, helping students understand not only how to write code, but also the concepts and reasoning behind it.

My lessons focus on hands-on exercises, clear explanations, and real-world examples, adapted to each student's level, goals, and learning pace.

I can help you get started with:
- **Java:** Programming fundamentals, object-oriented programming, and problem-solving.
- **Git:** Version control, managing code changes, and collaborating on projects.
- **Python:** Programming fundamentals and practical exercises for beginners.
- **React:** The basics of building interactive web applications.

Whether you are a complete beginner, a university student, or someone looking to strengthen your programming skills, I will help you build a solid foundation step by step.

My goal is to make programming easier to understand, help you gain confidence, and enable you to apply what you learn independently.
Education
Engineering degree in Software Engineering from one of the big institute in Morocco, with a strong foundation in programming, software design, algorithms, and application development.
Experience / Qualifications
Software Engineer at a leading technology company in Morocco. Experienced in software development, programming best practices, and building reliable applications. Passionate about sharing knowledge through practical, beginner-friendly lessons.
Age
Children (7-12 years old)
Teenagers (13-17 years old)
Adults (18-64 years old)
Seniors (65+ years old)
Student level
Beginner
Intermediate
Duration
60 minutes
The class is taught in
English
French
Arabic
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
Learn Java step by step through simple explanations, coding exercises, and a small final project.
Basic curriculum
- Introduction to Java, JDK and IDE setup
- Variables, data types and operators
- Conditions and loops
- Methods and arrays
- Classes, objects and constructors
- Encapsulation and basic inheritance
- Exceptions and simple debugging
- Mini-project: a console-based application
Read more
Discover programming with Python through beginner-friendly explanations and small real-world exercises.
Basic curriculum
- Installing Python and setting up an editor
- Variables, data types and operators
- Conditions and loops
- Lists, dictionaries and strings
- Functions and reusable code
- Reading and writing simple files
- Basic error handling
- Mini-project: a quiz, calculator or expense tracker
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Session 1: Revolutionizing your Scientific Writing with LaTeX & AI
Duration: 2 Hours | Level: Beginner | Tools: Overleaf + AI**

First Hour: Foundations and Cloud Environment (60 min)

1. Introduction to LaTeX Philosophy (15 min)

- The "WYSIWYM" concept:** Explain the difference between Word (*What You See Is What You Get*) and LaTeX (*What You See Is What You Mean*). Why content takes precedence over form.
- Key advantages:** Unrivaled typographic quality, automatic reference management, stability on long documents (theses), and free of charge.
- The structure of a file:** Distinction between the **preamble** (the brain: settings and packages) and the **body of the document** (the heart: text).

2. Immersion in Overleaf (25 min)

- Configuration:** Creation of an account and first project "Blank Project".
- Exploring the interface:** The file panel (left), the code editor (middle) and the PDF preview (right).
- Real-time collaboration:** How to share a project and leave comments (like on Google Docs).
- History and versions:** How to revert to a previous version in case of a compilation error.

3. Practical Workshop: My First Document (20 min)

* Writing basic commands: `\documentclass`, `\usepackage[french]{babel}`, `\title`, `\author`.
* Compilation of the document and observation of the result.
* Structuring: Use of `\section` and `\subsection`.

Second Hour: Mathematics and the Magic of AI (60 min)

4. The Power of Mathematics (20 min)

- Mathematical modes:** Difference between the text (`$...$`) and the centered block (`\[...\]`).
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- Introduction to AMS packages: Why amsmath and amssymb are essential for professional rendering.

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- Presentation of OCR tools:** Use of **Mathpix Snip** (the leader) or models like Gemini/ChatGPT to transform a photo into code.
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1. Take a picture of a complex handwritten formula (e.g., an integral with matrices).
2. Use AI to generate the corresponding LaTeX code.
3. Correction and insertion: Learn to check the AI-generated code before copying and pasting it into Overleaf.

6. Conclusion and Q&A (10 min)

* Summary of achievements.
* Resources for further exploration
* Definition of the exercise for the next session.
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A comprehensive course in Linear Programming and Linear Optimization, based on the renowned reference:

Bertsimas, D., & Tsitsiklis, J. N. (1997). Introduction to Linear Optimization. Athena Scientific.

The course covers the first five chapters in their entirety, forming the foundation upon which everything that follows in mathematical improvement is built. The concepts are explained in clear Arabic with step-by-step solved examples, illustrations, and practice exercises.

The five lectures:

Lecture 1 — Introduction to Linear Optimization:

What is optimization? And why do we need it?

Variables, decisions, functions, and constraints

The general formula for linear programming

Standard Form

Reducing any issue to the standard formula

Piecewise Linear Convex Functions

Graphing and solution

Fundamentals of Linear Algebra

Analysis of algorithms and number of operations

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Practical examples: food issues, production, scheduling, networks, pattern classification

Converting problems to standard format

Remove free variables

Slack and Surplus variables

convex and concave functions

Absolute values in objective functions

Graphical solution in 2D and 3D

The five possible solutions

Lecture 3 — Geometry of Linear Programming (LP):

Polyhedron and Polytope

Hyperplanes & Halfspaces

Extreme Points

Vertices

Basic Feasible Solutions

Active Constraints

Degeneration

The presence of extreme points

Visual examples in 2D and 3D

Lecture 4 — The Simplex Method:

Optimality Conditions

Reduced Costs

Development of the Simplex algorithm

Simplex Tableau

Pivoting

The Revised Simplex Method

Cycling and how to avoid it

Bland's Rule

Finding a basic, possible, initial solution

Two-Phase Simplex Method

Big-M Method

Mathematical aptitude and average behavior

Klee-Minty cube

Lecture 5 — Duality Theory:

The original (Primal) and dual problem

The relationship between variables and constraints

Weak Duality Theory

Strong Duality Theory

Conditions for Complementary Slackness

Dual variables as marginal costs

Shadow Prices

Dual Simplex Method

Geometric interpretation of duality

Applications in Economics and Finance

Advantages:

🎯 Explanation based on an accredited academic reference

📐 Illustrations for each geometric concept

🧮 Solved examples with numbers

💻 Examples in Python using gurobipy

📊 Comparison tables between different formulas

🔗 Linking theory to practical applications

📝 Exercises at the end of each lecture
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Contact el Mehdi
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1st lesson is backed
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Similar classes
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Vincent
With over seven years of experience in teaching Computer Science & Information Technology (ICT), I have developed a strong expertise in delivering high-quality education across multiple internationally recognized curricula, including Cambridge IGCSE, GCSE, A-Levels, O-Levels, and Checkpoint. My passion lies in equipping students with coding, cybersecurity, and digital literacy skills, ensuring they are well-prepared for the evolving demands of the digital world.

Expertise & Teaching Areas:
✅ Programming & Software Development: Python, Java, C++
✅ Cybersecurity: Ethical hacking, data protection, network security
✅ Digital Literacy: ICT applications, online safety, cloud computing
✅ Data Science & AI: Data analysis, machine learning fundamentals
✅ Web Development: HTML, CSS, JavaScript

Curriculum & Pedagogical Experience:
🔹 Cambridge IGCSE & GCSE ICT & Computer Science – Teaching core and extended syllabi, focusing on programming logic, databases, and networking.
🔹 Cambridge A-Levels & O-Levels Computer Science – Preparing students for advanced computing concepts, problem-solving, and algorithm development.
🔹 Cambridge Checkpoint ICT – Building foundational skills in digital technology and computer applications.

Professional Impact:
📌 Mentored students to achieve top grades in Cambridge ICT & Computer Science exams.
📌 Developed interactive lesson plans integrating real-world applications of technology.
📌 Conducted coding boot camps and cybersecurity workshops to enhance practical learning.
📌 Guided students in project-based learning, including app development and website design.

With a strong commitment to student-centered learning and technological innovation, I am dedicated to shaping future tech leaders and empowering learners with skills relevant to careers in technology, data science, and software development.
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Laroussi
Session 1: Revolutionizing your Scientific Writing with LaTeX & AI
Duration: 2 Hours | Level: Beginner | Tools: Overleaf + AI**

First Hour: Foundations and Cloud Environment (60 min)

1. Introduction to LaTeX Philosophy (15 min)

- The "WYSIWYM" concept:** Explain the difference between Word (*What You See Is What You Get*) and LaTeX (*What You See Is What You Mean*). Why content takes precedence over form.
- Key advantages:** Unrivaled typographic quality, automatic reference management, stability on long documents (theses), and free of charge.
- The structure of a file:** Distinction between the **preamble** (the brain: settings and packages) and the **body of the document** (the heart: text).

2. Immersion in Overleaf (25 min)

- Configuration:** Creation of an account and first project "Blank Project".
- Exploring the interface:** The file panel (left), the code editor (middle) and the PDF preview (right).
- Real-time collaboration:** How to share a project and leave comments (like on Google Docs).
- History and versions:** How to revert to a previous version in case of a compilation error.

3. Practical Workshop: My First Document (20 min)

* Writing basic commands: `\documentclass`, `\usepackage[french]{babel}`, `\title`, `\author`.
* Compilation of the document and observation of the result.
* Structuring: Use of `\section` and `\subsection`.

Second Hour: Mathematics and the Magic of AI (60 min)

4. The Power of Mathematics (20 min)

- Mathematical modes:** Difference between the text (`$...$`) and the centered block (`\[...\]`).
- Essential syntax:** Fractions `\frac{}{}`, exponents `^`, indices `_`, and roots `\sqrt{}`.
- Introduction to AMS packages: Why amsmath and amssymb are essential for professional rendering.

5. From hand to screen: AI at the service of LaTeX (30 min)

- Presentation of OCR tools:** Use of **Mathpix Snip** (the leader) or models like Gemini/ChatGPT to transform a photo into code.
- Concrete demonstration:
1. Take a picture of a complex handwritten formula (e.g., an integral with matrices).
2. Use AI to generate the corresponding LaTeX code.
3. Correction and insertion: Learn to check the AI-generated code before copying and pasting it into Overleaf.

6. Conclusion and Q&A (10 min)

* Summary of achievements.
* Resources for further exploration
* Definition of the exercise for the next session.
verified badge
عبدالرحمن
A comprehensive course in Linear Programming and Linear Optimization, based on the renowned reference:

Bertsimas, D., & Tsitsiklis, J. N. (1997). Introduction to Linear Optimization. Athena Scientific.

The course covers the first five chapters in their entirety, forming the foundation upon which everything that follows in mathematical improvement is built. The concepts are explained in clear Arabic with step-by-step solved examples, illustrations, and practice exercises.

The five lectures:

Lecture 1 — Introduction to Linear Optimization:

What is optimization? And why do we need it?

Variables, decisions, functions, and constraints

The general formula for linear programming

Standard Form

Reducing any issue to the standard formula

Piecewise Linear Convex Functions

Graphing and solution

Fundamentals of Linear Algebra

Analysis of algorithms and number of operations

Lecture 2 — Linear Programming Basics (LP Basics):

Practical examples: food issues, production, scheduling, networks, pattern classification

Converting problems to standard format

Remove free variables

Slack and Surplus variables

convex and concave functions

Absolute values in objective functions

Graphical solution in 2D and 3D

The five possible solutions

Lecture 3 — Geometry of Linear Programming (LP):

Polyhedron and Polytope

Hyperplanes & Halfspaces

Extreme Points

Vertices

Basic Feasible Solutions

Active Constraints

Degeneration

The presence of extreme points

Visual examples in 2D and 3D

Lecture 4 — The Simplex Method:

Optimality Conditions

Reduced Costs

Development of the Simplex algorithm

Simplex Tableau

Pivoting

The Revised Simplex Method

Cycling and how to avoid it

Bland's Rule

Finding a basic, possible, initial solution

Two-Phase Simplex Method

Big-M Method

Mathematical aptitude and average behavior

Klee-Minty cube

Lecture 5 — Duality Theory:

The original (Primal) and dual problem

The relationship between variables and constraints

Weak Duality Theory

Strong Duality Theory

Conditions for Complementary Slackness

Dual variables as marginal costs

Shadow Prices

Dual Simplex Method

Geometric interpretation of duality

Applications in Economics and Finance

Advantages:

🎯 Explanation based on an accredited academic reference

📐 Illustrations for each geometric concept

🧮 Solved examples with numbers

💻 Examples in Python using gurobipy

📊 Comparison tables between different formulas

🔗 Linking theory to practical applications

📝 Exercises at the end of each lecture
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