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Depuis décembre 2023
Professeur depuis décembre 2023
Computer Science and Programming class for beginners
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Àpd 69.17 € /h
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Computer Science is the study of algorithms, data structures, and the principles underlying the design of software and hardware systems. Programming, a key aspect of computer science, involves writing code to instruct computers. Students explore topics like algorithms, data analysis, artificial intelligence, and software development methodologies in this dynamic field.
Lieu
location type icon
En ligne depuis Royaume-Uni
Age
Enfants (4-6 ans)
Enfants (7-12 ans)
Adolescents (13-17 ans)
Niveau du Cours
Débutant
Intermédiaire
Durée
60 minutes
Enseigné en
anglais
malayalam
Disponibilité semaine type
(GMT -04:00)
New York
at teacher icon
Cours par webcam
Mon
Tue
Wed
Thu
Fri
Sat
Sun
00-04
04-08
08-12
12-16
16-20
20-24
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As a Geophysics PhD student, I rely heavily on programming tools like Matlab, Python, and R for data analysis, mathematical modeling, plot results and much more.

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The construction of simple sentences (present, past, future).
Useful vocabulary: family, food, time, travel, emotions...
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Structured course materials (PDF + exercises).
Audio recordings to improve pronunciation.
Mini real-life scenarios for practice.
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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)
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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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Durée : 2 Heures | Niveau : Débutant | Outils : Overleaf + IA**

Première Heure : Fondations et Environnement Cloud (60 min)

1. Introduction à la Philosophie LaTeX (15 min)

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- Collaboration en temps réel :** Comment partager un projet et laisser des commentaires (comme sur Google Docs).
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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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Nous aborderons notamment :
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• encapsulation, héritage et polymorphisme
• structures de contrôle et logique de programmation
• bonnes pratiques de codage et résolution de problèmes
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For computer science courses, I can teach children how to code with Python and C, and I can also teach high school students in the economics track how to study computer science.
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Contacter Jinu
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Le premier cours est couvert par notre Garantie Le-Bon-Prof
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Personalized Teaching Approach: Each course is tailored to your skill level and individual goals.

Practical Experience: Learn by doing with real-world projects that build your understanding and skills.

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As a Geophysics PhD student, I rely heavily on programming tools like Matlab, Python, and R for data analysis, mathematical modeling, plot results and much more.

After a lot of requests from students I created this course which is specifically meant to give you support completing your final programming projects.

Here's what you can expect:

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Vous avez des données mais ne savez pas comment les exploiter ? Vous souhaitez prendre des décisions basées sur des faits concrets ? Ou vous êtes étudiant·e et voulez maîtriser les outils de l'analyse moderne ?
Ce cours est fait pour vous.

👨‍🏫 À propos du formateur :
Je suis Data Scientist et Ingénieur en Mathématiques Appliquées, diplômé de l’Université Cheikh Anta Diop (UCAD). Mon expertise repose sur une solide base en Mathématiques, Statistiques, Machine Learning et Visualisation de données. J’allie rigueur scientifique et outils modernes pour transformer des données brutes en décisions stratégiques.

🧠 Objectifs du cours :
Comprendre et manipuler les données (exploration, nettoyage, visualisation)

- Identifier les variables importantes et repérer les anomalies

- Appliquer les méthodes statistiques et Machine Learning pour extraire de la valeur

- Construire des tableaux de bord clairs et parlants pour la prise de décision

- Adapter les analyses aux besoins réels d’une entreprise ou d’un projet académique

🧰 Contenu détaillé :
1. Introduction à l’analyse de données

- Qu’est-ce que l’analyse de données ?

- Typologie des données (quantitatives, qualitatives)

- Méthodologie globale

2. Préparation des données

- Nettoyage (valeurs manquantes, doublons, outliers)

- Encodage des variables catégorielles

- Normalisation et transformation

3. Visualisation et exploration

- Graphiques de distribution, de corrélation, de tendance

- Tableaux croisés, heatmaps, boxplots

- Détection de patterns et d’anomalies

4. Statistique descriptive et inférentielle

- Moyenne, Médiane, Ecart-type, Corrélation

- Tests statistiques : Khi2, t de Student, ANOVA

5. Modélisation prédictive (ML supervisé)

- Régression linéaire/logistique

- Arbre de décision, Random forest, KNN, SVM

- Évaluation : accuracy, recall, precision, F1-score, AUC

6. Segmentation et classification non supervisée

- Clustering (K-means, DBSCAN, hiérarchique)

- Réduction de dimension (ACP/PCA)

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- ou R (selon la préférence)

- Excel, Power BI/Tableau (pour la visualisation avancée)
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* Using the Terminal (basic commands, Git, working environment)
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* Anyone curious to learn how to create a website

💡 Method: Interactive video lessons (Zoom/Meet), screen sharing, practical exercises, and flashcards. You progress at your own pace, with real support and simple explanations.

⏰ Flexible hours – 1 hour, 1.5 hour or 2 hour sessions
💶 Available packages
🌍 100% Online Courses – Wherever You Are!



See you soon.
Sandrine.
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Data science, statistics & mathematics – clearly explained, personally supported.
My name is Kian, an experienced tutor from Bern. I support students, career starters, and professionals on their journey into the data-driven world—whether in their studies, projects, or everyday work.

With my structured, understandable, and motivating approach, I'll help you not only solve problems but also understand data, recognize connections, and make informed decisions. My lessons are personalized, efficient, and at eye level.

Who I am – and why I teach:
I teach in Bern and successfully completed the MAS program in Statistical Data Science at the University of Bern, focusing on statistics, mathematics, and data science. For several years, I have been passionately teaching, both in academic contexts and for professionals who want to think and work more data-driven.

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.

I love making complex topics tangible, creating aha moments, and empowering people to handle data confidently. For me, tutoring isn't just about imparting knowledge—it's about developing their minds on equal terms.

-What you can expect from me:
One-to-one lessons with a focus on data comprehension, statistics & analytical thinking
Support with projects, assignments, exams or getting started in the data world
Practical explanations – step by step and adapted to your everyday life
Teaching modern methods for data analysis, modeling & interpretation
Long-term strategies for problem-solving & structured thinking
Flexible lessons in Bern or online – personal, competent & reliable

Why I can help you understand data science:
Because I work at the interface between science and practice. I know how quickly you can get lost in formulas and tools—and I'll help you see the common thread:
How data tells stories, how you analyze it, and how you make smart decisions.

With me, you won't just learn methods—you'll learn how to think with data. Whether in your studies or in your career, I'll guide you in truly understanding data and applying it confidently.
Learn data analysis.
Analyze and model complex data sets – understandable, practical and with structure.
If you're ready to get to grips with data, I'm ready to guide you.
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This course is aimed at non-Arabic speakers wishing to learn Arabic in a simple, progressive and practical way, while discovering Moroccan pronunciation (darija).
It is accessible to all beginner levels, and requires no prior knowledge.
Through an interactive method, you will learn:
The basics of the Arabic alphabet and correct pronunciation.
Essential expressions for everyday communication.
The construction of simple sentences (present, past, future).
Useful vocabulary: family, food, time, travel, emotions...
An introduction to Moroccan Darija, to understand and speak easily with Moroccans.
The course is suitable for:
Adults, students and travellers.
People wishing to discover Moroccan culture.
Learners seeking patient, clear and motivating support.
I provide :
Structured course materials (PDF + exercises).
Audio recordings to improve pronunciation.
Mini real-life scenarios for practice.
Personalized support to progress with confidence.
📚 Simple, clear and effective method
👨‍🏫 Support tailored to your pace
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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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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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Ce cours d’informatique est destiné aux élèves et étudiants souhaitant acquérir des bases solides en programmation orientée objet (POO). Il convient aux débutants ainsi qu’aux personnes ayant déjà des notions de programmation et souhaitant mieux structurer leur code.

Nous aborderons notamment :
• concepts fondamentaux de la POO (classes, objets, attributs, méthodes)
• encapsulation, héritage et polymorphisme
• structures de contrôle et logique de programmation
• bonnes pratiques de codage et résolution de problèmes
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For computer science courses, I can teach children how to code with Python and C, and I can also teach high school students in the economics track how to study computer science.
For French, I can study children in primary, middle, and high school.
And above all, my class will be dynamic and have an atmosphere that will motivate the students.
Garantie Le-Bon-Prof
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