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معلم موثوق
يتميز هذا المعلم بمعدل استجابة سريع، مما يدل على خدمة عالية الجودة لطلابه.
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منذ أكتوبر 2022
أستاذ منذ أكتوبر 2022
Tech Support for Legacy Systems and Troubleshooting Experts
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من 205.63 AED
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Is your printer refusing to work with your computer again? Are you stuck with a weird error that no one on the forums seems to understand? Or maybe you have an ancient device that stores priceless data, but no modern system will talk to it? That’s where I come in - call me your digital detective.

I specialize in solving the kinds of tech problems most people walk away from—legacy hardware, software compatibility issues, obscure drivers, and cryptic error messages. Whether it’s a memory leak in a 20-year-old Palm PDA or making two completely unrelated systems communicate, I’ve been there and I've fixed that.

If your setup is unique, outdated, or just plain broken, I’ll treat it like a puzzle worth solving. Tech archeology meets modern ingenuity. I’m also happy to travel and work on-site if needed—sometimes the only way to truly understand a system is to sit down with it in person.
“Legacy systems fear him. Devs envy him. Managers don’t understand him.” - one of my clients, probably.
المكان
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عبر الانترنت من هولندا
من أنا؟
Having two little sisters provided me plentiful opportunities to experience first-hand what it's like to teach youngsters. With my guidance they became fluent in English as well as the language of music and theory. I never forced them to do as I say, nor did I penalize them for failing to prepare - just showing up is always sufficient. There is nothing in the world more fulfilling and meaningful than to see week by week the little steps a student takes on the path of learning. To see the milestones, the techniques they weren't able to perform just a few days prior, to see a delightful gleaming smile of success, the fact that they believed in themselves. This is what motivates me more than anything else in my piano and programming teaching voyage.

Studying and practicing can be stressful sometimes. It can be quite difficult in the early phases to train those rebellious fingers actively trying to sabotage a seemingly easy piece of music or program. It takes endurance to sit down on the same every day to practice, often without much improvement. But over time, it always becomes crystal clear, that every single second of practice counts, that practice itself improves self-control, not only within the confines of music and computers but also in everyday life.

He who never fails never tried to succeed either. The prerequisite of mastery is being a beginner.
المستوى التعليمي
Vrije Universiteit Amsterdam, The Netherlands
- Artificial Intelligence Bsc class 2024
Solti György Zeneiskola, Budapest, Hungary
- Solti György Középfokú Zeneismereti Diploma
Eötvös József Gimnázium, Budapest, Hungary
- played in the band "Peaches In The Sky":
الخبرة / المؤهلات
Python applications, Machine Learning, openCV, sklearn, numpy, pandas, tensorflow, and many many more libraries that I use in my personal projects
السن
الأطفال (7-12 سنة)
شباب (13-17 سنة)
الكبار (18-64 سنة)
الكبار (65 سنة فأكثر)
مستوى الطالب
مبتدئ
متوسط
متقدم
المدة
60 دقيقة
الدرس يدور باللغة
الإنجليزية
المجرية
الهولندية
الألمانية
المراجعات
الجاهزية في الأسبوع العادي
(GMT -05:00)
نيويورك
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على الانترنت عبر كاميرا ويب
Mon
Tue
Wed
Thu
Fri
Sat
Sun
00-04
04-08
08-12
12-16
16-20
20-24
“AI is the future.” You’ve heard it before, but what does it actually mean? Facial recognition, recommendation systems, self-driving cars—it all starts with data, algorithms, and code. The best part? You can learn it too.

Whether you're a curious beginner or someone already dabbling with machine learning, I offer hands-on guidance through the AI jungle. Using libraries like Pandas, Scikit-learn, TensorFlow, and OpenCV, I’ve built projects ranging from eye-tracking systems to classification models. I know how to explain complex concepts in simple terms—and help you build real, working prototypes.

From your first regression model to deploying your neural network, I’ll be your guide. Whether you want to understand the math behind it or just want results, we’ll move at your pace. available remotely across Europe.
إقرأ المزيد
Tired of doing the same tedious task over and over again? What if a small Python script could save you hours—every week? Whether it’s organizing files, renaming batches of documents, equalizing the volume of your MP3s, or auto-filling forms, automation is the silent superpower of the tech-savvy.

I build personalized scripts that do exactly what you need, no more, no less. These are not generic tools, but lightweight, purpose-built solutions designed to run on your system and make your workflow smoother.

If you’ve ever said, “There must be a better way to do this,” there probably is. Let me build it for you. Smart code for smart people.
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Amine
◾ Tools

RStudio • SQL • SPSS • SAS • Jamovi • JASP

◾ Statistical Methods & Tests

Student's t-test • ANOVA • MANOVA • ANCOVA • Regression (linear & logistic) • Correlation • Chi-square • Nonparametric tests • PCA • MCA • Exploratory factor analysis • Classification / Clustering • Mediation • Moderation • Interpretation

◾ Data analysis & decision support

- Data preparation, structuring and validation using SAS, R and SQL
- Descriptive, exploratory and multivariate statistical analyses on business data
- Production of performance indicators and actionable analyses to support decision-making

◾ Selection and implementation of methods

- Preparation and structuring of databases
- Hypothesis testing and univariate, bivariate and multivariate analyses (ANOVA / ANCOVA)
- Linear and logistic regressions
- Factor analyses (PCA / MCA)
- Mediation and moderation models
- Classification / clustering

1) Academic support

- Lectures, tutorials, projects and assignments in statistics
- Help in understanding and interpreting the results
- Preparation for exams and academic presentations

2) Statistical analysis

- Descriptive statistics (univariate and bivariate)
- Multivariate analyses
- Data exploration and outlier detection

3) Statistical tests

- Correlations (Pearson, Spearman, Cohen's Kappa)
- t-tests (one and two samples, independent or paired)
- Chi-square, binomial tests
- z-scores and associated indicators

4) Statistical modeling

- Linear regressions (simple and multiple)
- Logistic regression
- Interpretation of coefficients, diagnostics and validation of models

5) ANOVA & ANCOVA

- One- or multi-factor ANOVA
- Repeated measures ANOVA
- Fixed and random effects
- Post-hoc tests and effect sizes

6) Factor analyses

- ACP / PCA (scree plot, factor scores, matrices)
- Exploratory factor analysis
- Factorial rotations
- Validation and interpretation of structures and clusters

◾ Reporting & communication

- Clear, structured and concise reporting of results
- Visualizations tailored to decision-makers
- Support for strategic and operational decision-making
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Oussama
Your project is broken? Deadline approaching? Can't deploy? I help developers and students fix bugs, optimize code, and deploy applications to production.
I Specialize In:

Emergency Debugging: Find and fix errors fast (frontend crashes, backend timeouts, database issues)
Deployment Rescue: Get your app live when nothing works (AWS, Vercel, Netlify)
Performance Optimization: Speed up slow applications (database queries, API responses, bundle size)
CI/CD Setup: Automate your deployment pipeline (GitHub Actions, testing, monitoring)

Common Problems I Solve:

❌ "My app works locally but crashes in production"
❌ "Database queries are too slow"
❌ "Authentication isn't working"
❌ "Can't deploy to AWS / Vercel"
❌ "Getting weird errors I don't understand"
❌ "Payment integration (Stripe) not working"

Technologies I Work With:

Frontend: React, Next.js, TypeScript, Vue, Angular
Backend: Node.js, NestJS, Express, Python (Django, Flask)
Databases: PostgreSQL, MySQL, MongoDB, Redis
Cloud: AWS (EC2, RDS, S3), Vercel, Netlify, Render
DevOps: Docker, CI/CD, GitHub Actions, Nginx

Perfect For:

Students: Fix your project before the deadline
Junior Developers: Debug production issues you can't solve alone
Freelancers: Get unstuck on client projects fast
Startups: Fix and deploy your MVP without hiring a full-time engineer

How It Works:

Live Debugging Session: We fix it together via screen share
Code Review: I show you how to prevent the issue in the future
Documentation: You get a summary of what was fixed and why

Average Resolution Time:

Simple bugs: 1-2 hours
Deployment issues: 2-3 hours
Complex debugging: 3-5 hours

Urgent projects accepted (same-day availability for emergencies).
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Raouf
Objective: To understand AI without fear, to use it to simplify one's life and to know how to identify digital traps.

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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Laroussi
Séance 1 : Révolutionner sa Rédaction Scientifique avec LaTeX & l'IA
Durée : 2 Heures | Niveau : Débutant | Outils : Overleaf + IA**

Première Heure : Fondations et Environnement Cloud (60 min)

1. Introduction à la Philosophie LaTeX (15 min)

- Le concept "WYSIWYM" :** Expliquer la différence entre Word (*What You See Is What You Get*) et LaTeX (*What You See Is What You Mean*). Pourquoi le contenu prime sur la forme.
- Les avantages clés :** Qualité typographique inégalée, gestion automatique des références, stabilité sur les documents longs (thèses), et gratuité.
- La structure d'un fichier :** Distinction entre le **préambule** (le cerveau : réglages et packages) et le **corps du document** (le cœur : texte).

2. Immersion dans Overleaf (25 min)

- Configuration :** Création d'un compte et premier projet "Blank Project".
- Exploration de l'interface :** Le panneau de fichiers (gauche), l'éditeur de code (milieu) et la prévisualisation PDF (droite).
- Collaboration en temps réel :** Comment partager un projet et laisser des commentaires (comme sur Google Docs).
- L'historique et les versions :** Comment revenir en arrière en cas d'erreur de compilation.

3. Atelier Pratique : Mon Premier Document (20 min)

* Écriture des commandes de base : `\documentclass`, `\usepackage[french]{babel}`, `\title`, `\author`.
* Compilation du document et observation du résultat.
* Structuration : Utilisation de `\section` et `\subsection`.

Seconde Heure : Mathématiques et Magie de l'IA (60 min)

4. La puissance des Mathématiques (20 min)

- Modes mathématiques :** Différence entre le texte (`$...$`) et le bloc centré (`\[...\]`).
- Syntaxe essentielle :** Fractions `\frac{}{}`, exposants `^`, indices `_`, et racines `\sqrt{}`.
- Introduction aux packages AMS : Pourquoi amsmath et amssymb sont indispensables pour un rendu professionnel.

5. De la main à l'écran : L'IA au service du LaTeX (30 min)

- Présentation des outils d'OCR :** Utilisation de **Mathpix Snip** (le leader) ou de modèles comme Gemini/ChatGPT pour transformer une photo en code.
- Démonstration concrète :
1. Prendre une photo d'une formule manuscrite complexe (ex: une intégrale avec des matrices).
2. Utiliser l'IA pour générer le code LaTeX correspondant.
3. Correction et insertion : Apprendre à vérifier le code généré par l'IA avant de le copier-coller dans Overleaf.

6. Conclusion et Q&A (10 min)

* Synthèse des acquis.
* Ressources pour aller plus loin
* Définition de l'exercice pour la prichaine séance.
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اتصل بGergely
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الدرس الأول مضمون
بواسطة
ضمان المدرس المناسب
فصول مماثلة
arrow icon previousarrow icon next
verified badge
Amine
◾ Tools

RStudio • SQL • SPSS • SAS • Jamovi • JASP

◾ Statistical Methods & Tests

Student's t-test • ANOVA • MANOVA • ANCOVA • Regression (linear & logistic) • Correlation • Chi-square • Nonparametric tests • PCA • MCA • Exploratory factor analysis • Classification / Clustering • Mediation • Moderation • Interpretation

◾ Data analysis & decision support

- Data preparation, structuring and validation using SAS, R and SQL
- Descriptive, exploratory and multivariate statistical analyses on business data
- Production of performance indicators and actionable analyses to support decision-making

◾ Selection and implementation of methods

- Preparation and structuring of databases
- Hypothesis testing and univariate, bivariate and multivariate analyses (ANOVA / ANCOVA)
- Linear and logistic regressions
- Factor analyses (PCA / MCA)
- Mediation and moderation models
- Classification / clustering

1) Academic support

- Lectures, tutorials, projects and assignments in statistics
- Help in understanding and interpreting the results
- Preparation for exams and academic presentations

2) Statistical analysis

- Descriptive statistics (univariate and bivariate)
- Multivariate analyses
- Data exploration and outlier detection

3) Statistical tests

- Correlations (Pearson, Spearman, Cohen's Kappa)
- t-tests (one and two samples, independent or paired)
- Chi-square, binomial tests
- z-scores and associated indicators

4) Statistical modeling

- Linear regressions (simple and multiple)
- Logistic regression
- Interpretation of coefficients, diagnostics and validation of models

5) ANOVA & ANCOVA

- One- or multi-factor ANOVA
- Repeated measures ANOVA
- Fixed and random effects
- Post-hoc tests and effect sizes

6) Factor analyses

- ACP / PCA (scree plot, factor scores, matrices)
- Exploratory factor analysis
- Factorial rotations
- Validation and interpretation of structures and clusters

◾ Reporting & communication

- Clear, structured and concise reporting of results
- Visualizations tailored to decision-makers
- Support for strategic and operational decision-making
verified badge
Oussama
Your project is broken? Deadline approaching? Can't deploy? I help developers and students fix bugs, optimize code, and deploy applications to production.
I Specialize In:

Emergency Debugging: Find and fix errors fast (frontend crashes, backend timeouts, database issues)
Deployment Rescue: Get your app live when nothing works (AWS, Vercel, Netlify)
Performance Optimization: Speed up slow applications (database queries, API responses, bundle size)
CI/CD Setup: Automate your deployment pipeline (GitHub Actions, testing, monitoring)

Common Problems I Solve:

❌ "My app works locally but crashes in production"
❌ "Database queries are too slow"
❌ "Authentication isn't working"
❌ "Can't deploy to AWS / Vercel"
❌ "Getting weird errors I don't understand"
❌ "Payment integration (Stripe) not working"

Technologies I Work With:

Frontend: React, Next.js, TypeScript, Vue, Angular
Backend: Node.js, NestJS, Express, Python (Django, Flask)
Databases: PostgreSQL, MySQL, MongoDB, Redis
Cloud: AWS (EC2, RDS, S3), Vercel, Netlify, Render
DevOps: Docker, CI/CD, GitHub Actions, Nginx

Perfect For:

Students: Fix your project before the deadline
Junior Developers: Debug production issues you can't solve alone
Freelancers: Get unstuck on client projects fast
Startups: Fix and deploy your MVP without hiring a full-time engineer

How It Works:

Live Debugging Session: We fix it together via screen share
Code Review: I show you how to prevent the issue in the future
Documentation: You get a summary of what was fixed and why

Average Resolution Time:

Simple bugs: 1-2 hours
Deployment issues: 2-3 hours
Complex debugging: 3-5 hours

Urgent projects accepted (same-day availability for emergencies).
verified badge
Raouf
Objective: To understand AI without fear, to use it to simplify one's life and to know how to identify digital traps.

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?
verified badge
Laroussi
Séance 1 : Révolutionner sa Rédaction Scientifique avec LaTeX & l'IA
Durée : 2 Heures | Niveau : Débutant | Outils : Overleaf + IA**

Première Heure : Fondations et Environnement Cloud (60 min)

1. Introduction à la Philosophie LaTeX (15 min)

- Le concept "WYSIWYM" :** Expliquer la différence entre Word (*What You See Is What You Get*) et LaTeX (*What You See Is What You Mean*). Pourquoi le contenu prime sur la forme.
- Les avantages clés :** Qualité typographique inégalée, gestion automatique des références, stabilité sur les documents longs (thèses), et gratuité.
- La structure d'un fichier :** Distinction entre le **préambule** (le cerveau : réglages et packages) et le **corps du document** (le cœur : texte).

2. Immersion dans Overleaf (25 min)

- Configuration :** Création d'un compte et premier projet "Blank Project".
- Exploration de l'interface :** Le panneau de fichiers (gauche), l'éditeur de code (milieu) et la prévisualisation PDF (droite).
- Collaboration en temps réel :** Comment partager un projet et laisser des commentaires (comme sur Google Docs).
- L'historique et les versions :** Comment revenir en arrière en cas d'erreur de compilation.

3. Atelier Pratique : Mon Premier Document (20 min)

* Écriture des commandes de base : `\documentclass`, `\usepackage[french]{babel}`, `\title`, `\author`.
* Compilation du document et observation du résultat.
* Structuration : Utilisation de `\section` et `\subsection`.

Seconde Heure : Mathématiques et Magie de l'IA (60 min)

4. La puissance des Mathématiques (20 min)

- Modes mathématiques :** Différence entre le texte (`$...$`) et le bloc centré (`\[...\]`).
- Syntaxe essentielle :** Fractions `\frac{}{}`, exposants `^`, indices `_`, et racines `\sqrt{}`.
- Introduction aux packages AMS : Pourquoi amsmath et amssymb sont indispensables pour un rendu professionnel.

5. De la main à l'écran : L'IA au service du LaTeX (30 min)

- Présentation des outils d'OCR :** Utilisation de **Mathpix Snip** (le leader) ou de modèles comme Gemini/ChatGPT pour transformer une photo en code.
- Démonstration concrète :
1. Prendre une photo d'une formule manuscrite complexe (ex: une intégrale avec des matrices).
2. Utiliser l'IA pour générer le code LaTeX correspondant.
3. Correction et insertion : Apprendre à vérifier le code généré par l'IA avant de le copier-coller dans Overleaf.

6. Conclusion et Q&A (10 min)

* Synthèse des acquis.
* Ressources pour aller plus loin
* Définition de l'exercice pour la prichaine séance.
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