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Depuis septembre 2022
Professeur depuis septembre 2022
Python For Everybody (A-Z) - From a Software Engineer
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Àpd 219.66 CNY /h
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There are lots of people knowing how to write code around us. If you want to be one of them, we can both learn and have fun together.

Knowing to program gains you skills like analytical thinking, problem-solving etc. Also, if you are curious about AI, don't worry I am a postgraduate student at the University of Sussex and after learning the Python language, I can teach you some AI techniques.
Lieu
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En ligne depuis Royaume-Uni
Age
Enfants (7-12 ans)
Adolescents (13-17 ans)
Adultes (18-64 ans)
Seniors (65+ ans)
Niveau du Cours
Débutant
Intermédiaire
Avancé
Durée
60 minutes
Enseigné en
anglais
turc
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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Python is one of the best, if not the best, language to start learning programming. It is also one of the most widely used languages today, especially in cutting-edge areas such as machine learning.

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Les algorithmes vous semblent difficiles ? Vous pensez qu'ils sont réservés aux spécialistes en informatique ? Détrompez-vous ! Ce cours vous prouve que concevoir et analyser des algorithmes peut être simple et accessible à tous.

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Aux étudiants en informatique désireux de renforcer leurs bases en conception et analyse d'algorithmes.
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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.

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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

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- 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

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- 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)

7. Projets réels (au choix)

- Analyse des ventes / Churn client / Scoring de crédit / Santé publique

- Ou projet personnalisé à vos propres données

💻 Outils utilisés :

- Python (Pandas, Matplotlib, Scikit-learn, Seaborn)

- ou R (selon la préférence)

- Excel, Power BI/Tableau (pour la visualisation avancée)
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* **Context Style:** Why is the phrase "Give me a cake recipe" less effective than "I have a gluten allergy and I'm having 4 people, give me a simple chocolate cake recipe".
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Digital hallucinations:** Understand that artificial intelligence may confidently present false information (never rely on it for medical or legal advice without verification).
Privacy protection
Do not share sensitive data (ID numbers, passwords, bank details).
Be aware that everything you write may be used to train systems in the future.

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How to identify fake photos or videos (examine hand details, strange reflections, or metallic sound).
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Copyright: Who owns the image created by artificial intelligence?
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Clear explanations and step-by-step guidance
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Whether you're preparing for postgraduate studies, working on a thesis, or transitioning into data science, this class will give you a strong, practical foundation.
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Contacter Serkan
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Le premier cours est couvert par notre Garantie Le-Bon-Prof
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Hello, I am a doctoral student in electrical engineering and associate professor in engineering sciences, experienced in the field of electrical engineering, I offer support courses in the subjects of engineering sciences (Electronics, automatics, electrical engineering, automation, programming).

Digital electronics
Analog electronic
electromagnetism (propagation of high frequency waves)
Automatic (continuous, sampled)
electrical engineering (transformers, electrical machines, switching power supply)
C / c ++ programming, Assembler, ARM, STM32
renewable energy (wind, PV)
engineering Sciences
RDM
Python,VHDL
PIC Microprocessor and Microcontroller
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These courses allow the student to get up to speed and regain confidence in all scientific subjects, just as they prepare him effectively for the Baccalaureate, the Preparatory Classes or various examinations of the engineering classes.

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Resumption and deepening of fundamental concepts through exercises with course reminders.

Put the student in a situation of questioning and research.

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Learn to build theoretical reasoning from observable facts or hypotheses.

Specific preparation for higher education requirements (in-depth content, increase in work capacity, enrichment of scientific background)

This educational approach is effective since it has often led me to interesting results with my students.

Associate professor provides support courses in electrical engineering
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Python is one of the best, if not the best, language to start learning programming. It is also one of the most widely used languages today, especially in cutting-edge areas such as machine learning.

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I created this course especially for students having difficulty progressing in their computer programming courses/projects. I support students of all university levels. My help covers many others:
- Analysis and planning of projects
- Technological choice in languages and tools/framework
- Algorithmic and programming support
- Assistance with debugging and code correction
- Data modeling (MCD/MLD diagram, UML diagrams)

Why choose my courses?
My method is different and more adapted than that of traditional teachers because it is:
* Personalized: Adapted to your level and your specific needs.
* Interactive: Promotes interaction and visualization of concepts.
* Practical: Oriented towards practice with concrete exercises and projects.
* Proven: I have already managed to help more than 200 students in the space of 2 years.
verified badge
doctoral student in engineering sciences provides support courses in analog and digital electronics at any DEUG level and engineering schools. having scientific and technical knowledge, three years of experience in the field of teaching, pedagogy and a sense of listening and analysis, I am able to help pupils and students and train them in the chapters of which they are having difficulty. for more info please contact me
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Are you a university student, engineer, or professional who needs to actually use data — not just learn theory about it?
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Discover the art of programming with Python courses tailor-made to meet your specific needs. Whether you are a beginner, intermediate or professional, my lessons are suitable for all levels.

Why Choose My Courses?

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.

Ongoing Support: Get unlimited email support for any questions you have between sessions.

As a Python expert, I have a passion for teaching and sharing my knowledge. My goal is to guide you effectively in your learning journey.

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Les algorithmes vous semblent difficiles ? Vous pensez qu'ils sont réservés aux spécialistes en informatique ? Détrompez-vous ! Ce cours vous prouve que concevoir et analyser des algorithmes peut être simple et accessible à tous.

Que vous soyez étudiant en informatique, novice en programmation, ou simplement curieux de comprendre le fonctionnement des logiciels, ce cours vous accompagnera pas à pas pour saisir les bases des algorithmes sans vous perdre dans le jargon technique.

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Comprendre les algorithmes : Qu'est-ce qu'un algorithme ? Pourquoi sont-ils cruciaux en informatique ?
Conception d'algorithmes : Apprenez à décomposer des problèmes complexes en étapes simples et logiques.
Structures de contrôle : Maîtrisez les instructions conditionnelles (if, else) et les boucles (for, while) pour créer des algorithmes dynamiques.
Pseudocode et diagrammes de flux : Représentez vos idées clairement avant même de les coder.
Analyse de complexité : Découvrez les concepts de complexité temporelle et spatiale (Big O) de manière intuitive.
Algorithmes courants : Explorez des algorithmes de tri (Tri par insertion, Tri à bulles) et de recherche (Recherche linéaire, Recherche dichotomique).
Résolution de problèmes : Mettez en pratique vos connaissances à travers des exercices inspirés de situations réelles.

Pourquoi choisir ce cours ?
Explications simples et claires : Chaque concept est présenté de manière intuitive, accompagné d'exemples concrets et d'analogies tirées de la vie quotidienne.
Approche progressive : Vous progressez du plus simple au plus complexe, étape par étape, sans jamais vous sentir perdu.
Exercices pratiques : Appliquez vos connaissances à travers des exercices ludiques et des projets concrets.
Flexibilité et confort : Apprenez depuis chez vous, sans avoir besoin de caméra, grâce à un partage d’écran interactif pour une expérience fluide.
Un atout professionnel : La maîtrise des algorithmes est une compétence très recherchée dans les domaines du développement logiciel, de la data science et de l'intelligence artificielle.
À qui s'adresse ce cours ?
Aux débutants complets qui souhaitent comprendre les algorithmes sans se perdre dans des explications trop techniques.
Aux étudiants en informatique désireux de renforcer leurs bases en conception et analyse d'algorithmes.
Aux développeurs novices qui veulent écrire un code plus optimisé et efficace.
À toute personne curieuse d'explorer les fondements de la logique informatique.
Prérequis :
Aucun ! Ce cours est ouvert à tous, même si vous n'avez jamais programmé auparavant.
Il vous suffit d’avoir :

Un ordinateur pour suivre les exercices (aucune installation complexe n’est requise).
La motivation d'apprendre et de pratiquer avec des exemples concrets.

Rejoignez ce cours dès maintenant et découvrez à quel point les algorithmes peuvent être à la fois simples et amusants ! Ne laissez pas passer cette chance de comprendre enfin la logique qui se cache derrière les logiciels et applications que vous utilisez chaque jour. Prêt à relever le défi ? Inscrivez-vous aujourd'hui et commencez votre aventure avec les algorithmes !
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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)

7. Projets réels (au choix)

- Analyse des ventes / Churn client / Scoring de crédit / Santé publique

- Ou projet personnalisé à vos propres données

💻 Outils utilisés :

- Python (Pandas, Matplotlib, Scikit-learn, Seaborn)

- ou R (selon la préférence)

- Excel, Power BI/Tableau (pour la visualisation avancée)
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This mathematics course is aimed at students in lower or upper secondary education who wish to strengthen their basic skills, fill in gaps or effectively prepare for an exam.

We will work together on understanding key concepts (arithmetic, geometry, algebra, functions, etc.) through clear explanations, progressive exercises and a method adapted to the pace of each student.

The goal is to restore confidence, develop logic and reasoning skills, and make mathematics more accessible and concrete.

This course is also suitable for students in scientific, technical or linguistic fields who need regular or occasional support.
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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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*Goal: To understand artificial intelligence without fear, use it to simplify life, and uncover digital traps.*

### **1: Demystifying Artificial Intelligence (What Exactly Is It?)**

* **Artificial intelligence is not a "movie robot":** The fundamental difference between science fiction and practical reality.
* **How it works (simply):** Imagine a "giant library"; AI has read billions of books and uses them to predict the completion of a sentence or create a new image.
* **Where do we use it now?** The spell checker, Netflix and YouTube suggestions, GPS navigation, and voice assistants such as Siri and Alexa.

---

### **2: Using artificial intelligence to make your life easier**

* **Interacting with artificial intelligence (ChatGPT, Cloud, Gemini):**
* Writing formal emails or complex letters.
* Summarizing long articles or huge documents.
* Plan travel itineraries or create food recipes from ingredients available in the refrigerator.


* **Creativity and Memory:**
* Create creative images for greeting cards (via Midjourney or DALL-E).
Restoring and coloring old family photos.

3: The art of speaking to the machine (the Prompt skill)**

* **Context Style:** Why is the phrase "Give me a cake recipe" less effective than "I have a gluten allergy and I'm having 4 people, give me a simple chocolate cake recipe".
* **Role-taking:** Learn to ask the artificial intelligence to "speak like a tourism expert" or "answer me like a specialized agricultural engineer."

4: Precautions and Critical Thinking (A Survival Guide)**

Digital hallucinations:** Understand that artificial intelligence may confidently present false information (never rely on it for medical or legal advice without verification).
Privacy protection
Do not share sensitive data (ID numbers, passwords, bank details).
Be aware that everything you write may be used to train systems in the future.

Detecting deepfakes:**
How to identify fake photos or videos (examine hand details, strange reflections, or metallic sound).
* The golden rule: Verify by cross-referencing different sources.

5: Ethics and Impact (A Future Perspective)**

Copyright: Who owns the image created by artificial intelligence?
Environmental impact: Water and energy consumption in large data centers.
The future: Will artificial intelligence replace us or will it be an assistant to us?

Additional tip:** Since you are targeting the Gulf region, it is preferable to use terms such as "Digital Transformation" and "Innovation" at the beginning of your presentation, as they are very catchy words for decision-makers there.
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I offer personalized tutoring in mathematics, programming, and languages, tailored to your level and goals. Whether you are a student, beginner, or someone looking to improve your skills, I provide structured and practical lessons to help you succeed.

With a background in AI and Software Engineering, I combine strong theoretical knowledge with real-world applications. I can help you understand complex concepts in a simple and intuitive way.

Subjects I teach:

Mathematics: from school-level to university basics (algebra, calculus, problem-solving)
Programming: Python, C, C++, and Java (from fundamentals to practical projects)
Languages: English, French, German and Arabic (speaking, writing, and comprehension)

My teaching approach focuses on:

Clear explanations and step-by-step guidance
Practical exercises and real examples
Adapting to your pace and learning style

I am patient, flexible, and committed to helping you build confidence and achieve your goals—whether it's passing exams, improving skills, or starting something new.
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Learn how to use R to analyze data, conduct research, and produce professional reports—even if you’re starting from scratch.

This course is designed for students, researchers, and professionals who want to build practical data skills for academic work, career growth, or international opportunities.

In this class, you will learn how to:
- Clean and analyze real-world datasets using R and Python
- Perform statistical analysis for research projects
- Create high-quality visualizations
- Automate reports using tools like Quarto
- Structure research workflows that stand out for scholarships and publications

The teaching approach is hands-on and project-based. You won’t just learn theory—you’ll work on real datasets and build a portfolio you can use immediately.

Whether you're preparing for postgraduate studies, working on a thesis, or transitioning into data science, this class will give you a strong, practical foundation.
Garantie Le-Bon-Prof
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