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LaTeX: Refining Academic Articles and Theses with technical writing rules
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From 14.96 € /h
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This course is designed to guide you through the process of refining professional academic documents using LaTeX. You can progress through the following modules:
1️⃣ LaTeX Environment and Setup
Install the necessary software and editors.
2️⃣ Formatting and Document Structure
3️⃣ Tables, Figures, and Graphics
4️⃣ Writing Equations and Formulas
Numbering and referencing equations
5️⃣ Using BibTeX for Bibliographies
Location
location type icon
Online from Algeria
About Me
Passionate about computer science and applied mathematics, I hold a Master's degree in Artificial Intelligence. My teaching approach is based on complex concepts, whether it's solving mathematical problems, mastering Python programming, modeling statistical analyses using the R language, or guiding students in scientific writing through academic approaches using LaTeX. I enjoy sharing my knowledge in a practical and concrete way. I adapt my methodology to the student's needs, whether they are a curious beginner or a student looking to refine their technical skills.
Education
Master of Science (M.Sc.): Artificial Intelligence, Systems and Knowledge - University of Ghardaïa (Graduated in 2019).
BSc Degree: Informatics Systems - University of Ghardaïa (Graduated in 2017).
Certifications: Professional certificates in Data Science (IBM) and Data Analytics (Google).
Experience / Qualifications
Data Analyst & Mentor: Experience in technical mentoring for start-ups on data acquisition and strategic planning.
Python Expertise: Advanced use of Python for data analysis, machine learning, and AI.
BI tools trainer: Facilitating workshops on Power BI and MS Excel for professional teams.
Statistical Analysis: Mastery of mathematical and statistical methods applied to real-world projects.
Age
Children (7-12 years old)
Teenagers (13-17 years old)
Adults (18-64 years old)
Seniors (65+ years old)
Student level
Beginner
Intermediate
Advanced
Duration
60 minutes
The class is taught in
French
English
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
Are you a STEM student or researcher? Do you need to conduct rigorous analyses for your studies or publications? Join our intensive training program designed to support you.

Training program:

The Fundamentals of R: Installation, syntax and basic structures.

Data manipulation: Proficiency in essential packages (Tidyverse, dplyr).

Data Visualization: Creation of professional and impactful graphs.

Statistical Analyses: ANOVA, Linear Regressions, Statistical.

Multidimensional Methods: PCA (Principal Component Analysis) and Clustering.
session composition:
✅ Practical approach based on real cases.
✅ Personalized support for your research projects.
Read more
I offer training in Algorithms and Python programming for students and beginners.
Level 1: variables, logical syntax, balls, blocks and functions.
Level 2: packages, file processing, graphical presentations (dashboard).
Read more
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Students are expected to be present for each scheduled class, not late, and to avoid a rude or disrespectful beahviour.

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In parallel to my teaching, I have implemented numerous data science projects – from exploratory analysis and data modeling to decision support in a business context. This combination of theory and practice makes my teaching particularly close to reality while remaining accessible.

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One-to-one lessons with a focus on data comprehension, statistics & analytical thinking
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Practical explanations – step by step and adapted to your everyday life
Teaching modern methods for data analysis, modeling & interpretation
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• Python programming (fundamentals, logic building, problem-solving, data handling)
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• CSS (styling, layout systems, responsive design)
• Website Development (front-end foundations and structure)
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Students learn how to think computationally, break down problems logically, and build structured solutions. Lessons are practical and project-based, meaning students don’t just watch — they build.

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My approach emphasizes clarity, structure, and application. I help students understand not only what to type, but why it works — which is the difference between copying code and truly understanding it.

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• School students exploring computer science
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verified badge
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Object-Oriented Programming is often perceived as complex or abstract.

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

🎯 Training Objectives

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

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

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

🛠️ Teaching method: Understand before writing

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

🚀 Learner's result

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

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

You will leave with:
a solid understanding of OOP
a cleaner and more professional code
an ideal foundation for learning React, Node.js or any other modern framework
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This advanced course builds on programming fundamentals using Python (programming language) and is designed for students who want to deepen their programming knowledge.

The course continues from functions and introduces advanced programming concepts including object-oriented programming principles such as polymorphism, inheritance, abstraction, and encapsulation.

Students will also learn data handling techniques, working with Python libraries, and developing structured programs using complex loops and data collections.

The course covers practical implementation of nested loops, nested lists, tuples, and dictionaries, as well as an introduction to data structures and algorithmic thinking.

Additional topics include graphical user interface development using libraries such as Tkinter, along with introductory concepts in data science and machine learning using Python.

Teaching combines theoretical explanation with real coding exercises to help students develop strong practical programming skills.

• Review of programming fundamentals and functions
• Object-Oriented Programming (OOP) concepts
• Polymorphism, inheritance, abstraction, and encapsulation
• Data structures basics
• Nested loops and complex data handling
• Lists, tuples, and dictionaries
• Introduction to algorithms
• Working with Python libraries
• GUI development using Tkinter
• Introduction to data science and machine learning concepts
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