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Professeur fiable
Ce professeur a un délai et un taux de réponse très élevé, démontrant un service de qualité et sa fidélité envers ses élèves.
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Depuis mars 2025
Professeur depuis mars 2025
Geographic Information System (GIS): Applications with open-source software
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Àpd 62 € /h
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The course is designed to provide an in-depth understanding of
Geographic Information Systems (GIS) and its applications.

It consists from 5 to 10 modules (or classes) that cover various aspects of GIS,
including introduction to GIS, geographic data representation and
uncertainty, georeferencing and spatial coordinate systems,
GIS software and data modeling, GIS data collection and processing,
spatial analysis and querying techniques, cartography and geovisualization,
advanced spatial data processing and automation with R and Python,
and future trends and innovations in GIS.

Each module is structured with sections for review and objectives,
lecture, interactive discussion, hands-on exercise, and Q&A.
The course aims to equip participants with the knowledge and skills
to effectively utilize GIS in problem-solving and decision-making across
different fields.
Informations supplémentaires
Location:
• Online classes (available worldwide).

Contact:
• Please contact me first to assess your level and tailor the course to your needs.
Lieu
location type icon
En ligne depuis Allemagne
Présentation
• Civil Engineer with ample experience in environmental modeling, hydrological, and climate analysis
• PhD in Environmental Sciences and MSc in Geospatial Technologies. Expert in
geospatial data modeling
• Skilled in data science, remote sensing, GIS, machine learning, and statistical
analysis with R and Python
Education
PhD, Wageningen University (The Netherlands)
M.Sc. Westfälische Wilhelms Universität (Germany)
M.Eng. Universidad Nacional de Colombia (Colombia)
Civil Engineer, Universidad Nacional de Colombia (Colombia)
Expérience / Qualifications
- 13 years of experience working with GIS software and data analysis
- 10 years of national and international experience in academy and consultancy.
- Proficient in using R and Python for spatial data processing and automation
- Strong knowledge of geospatial data collection techniques, including remote sensing
- Expertise in managing GIS projects and implementing GIS solutions in various fields
- Competency in cartographic design principles and geovisualization techniques
- Mastery in spatial analysis and querying techniques for problem-solving
- Qualification in different georeferencing methods and spatial coordinate systems
- Expertise in data modeling and database management in GIS
- Up-to-date with current trends and innovations in GIS, including big data and AI applications
Age
Adultes (18-64 ans)
Seniors (65+ ans)
Niveau du Cours
Débutant
Intermédiaire
Avancé
Durée
60 minutes
Enseigné en
espagnol
anglais
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
Courses I Offer:
• R programming from basic to advanced levels.
• R package development for automation and analysis.
• Data visualization with R.

Location:
• Online classes (available worldwide).

Contact:
• Please contact me first to assess your level and tailor the course to your needs.
Lire la suite
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*الهدف: فهم الذكاء الاصطناعي بلا خوف، استخدامه لتبسيط الحياة، وكشف الفخاخ الرقمية**

### **1: إزالة الغموض عن الذكاء الاصطناعي (ما هو بالضبط؟)**

* **الذكاء الاصطناعي ليس "روبوت الأفلام":** الفرق الجوهري بين الخيال العلمي والواقع العملي.
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---

### **2: استخدام الذكاء الاصطناعي لتسهيل حياتك**

* **التحاور مع الذكاء الاصطناعي (ChatGPT, Claude, Gemini):**
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* تخطيط مسارات السفر أو ابتكار وصفات طعام من المكونات المتوفرة في الثلاجة.


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* ترميم وتلوين صور العائلة القديمة.

3: فن التحدث مع الآلة (مهارة الـ Prompt)**

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* **تقمص الأدوار:** تعلم أن تطلب من الذكاء الاصطناعي "تحدث كخبير سياحي" أو "أجبني كمهندس زراعي مختص".

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الهلوسة الرقمية":** فهم أن الذكاء الاصطناعي قد يقدم معلومات خاطئة بثقة تامة (لا تعتمد عليه أبداً في استشارة طبية أو قانونية دون تحقق).
حماية الخصوصية
عدم مشاركة بيانات حساسة (أرقام الهوية، كلمات المرور، تفاصيل البنك).
إدراك أن كل ما تكتبه قد يُستخدم في تدريب الأنظمة مستقبلاً.

كشف التزييف العميق (Deepfakes):**
كيفية تمييز الصور أو الفيديوهات المفبركة (التدقيق في تفاصيل اليدين، الانعكاسات الغريبة، أو الصوت المعدني).
* القاعدة الذهبية: التحقق عبر مقاطعة المصادر المختلفة.

5: الأخلاقيات والأثر (رؤية مستقبلية)**

حقوق الملكية:** لمن تعود ملكية الصورة التي أنشأها الذكاء الاصطناعي؟
الأثر البيئي:** استهلاك المياه والطاقة في مراكز البيانات الضخمة.
المستقبل:** هل سيحل الذكاء الاصطناعي محلنا أم سيكون مساعداً لنا؟

نصيحة إضافية:** بما أنك تستهدف منطقة الخليج، يفضل استخدام مصطلحات مثل "التحول الرقمي" (Digital Transformation) و"الابتكار" (Innovation) في مقدمة عرضك، فهي كلمات رنانة جداً لدى صناع القرار هناك.
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Hi!

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- 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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Python is a simple, powerful, and versatile programming language, ideal for beginners looking to learn or change careers in computer science. This course will help you understand the basics of programming (variables, loops, conditions, functions) through practical, hands-on exercises.
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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.

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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.

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Learn data analysis.
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*الهدف: فهم الذكاء الاصطناعي بلا خوف، استخدامه لتبسيط الحياة، وكشف الفخاخ الرقمية**

### **1: إزالة الغموض عن الذكاء الاصطناعي (ما هو بالضبط؟)**

* **الذكاء الاصطناعي ليس "روبوت الأفلام":** الفرق الجوهري بين الخيال العلمي والواقع العملي.
* **كيف يعمل (ببساطة):** تخيل "مكتبة عملاقة"؛ لقد قرأ الذكاء الاصطناعي مليارات الكتب ويستخدمها لتوقع تكملة جملة ما أو ابتكار صورة جديدة.
* **أين نستخدمه حالياً؟** المصحح اللغوي، مقترحات نتفليكس ويوتيوب، نظام الملاحة (GPS)، والمساعدات الصوتية مثل (سيري وأليكسا).

---

### **2: استخدام الذكاء الاصطناعي لتسهيل حياتك**

* **التحاور مع الذكاء الاصطناعي (ChatGPT, Claude, Gemini):**
* كتابة رسائل البريد الإلكتروني الرسمية أو الخطابات المعقدة.
* تلخيص المقالات الطويلة أو الوثائق الضخمة.
* تخطيط مسارات السفر أو ابتكار وصفات طعام من المكونات المتوفرة في الثلاجة.


* **الإبداع والذاكرة:**
* إنشاء صور مبتكرة لبطاقات المعايدة (عبر Midjourney أو DALL-E).
* ترميم وتلوين صور العائلة القديمة.

3: فن التحدث مع الآلة (مهارة الـ Prompt)**

* **أسلوب السياق:** لماذا عبارة "أعطني وصفة كعكة" أقل فعالية من "أنا أعاني من حساسية الجلوتين وسأستقبل 4 أشخاص، أعطني وصفة كعكة شوكولاتة بسيطة".
* **تقمص الأدوار:** تعلم أن تطلب من الذكاء الاصطناعي "تحدث كخبير سياحي" أو "أجبني كمهندس زراعي مختص".

4: الاحتياطات والتفكير النقدي (دليل النجاة)**

الهلوسة الرقمية":** فهم أن الذكاء الاصطناعي قد يقدم معلومات خاطئة بثقة تامة (لا تعتمد عليه أبداً في استشارة طبية أو قانونية دون تحقق).
حماية الخصوصية
عدم مشاركة بيانات حساسة (أرقام الهوية، كلمات المرور، تفاصيل البنك).
إدراك أن كل ما تكتبه قد يُستخدم في تدريب الأنظمة مستقبلاً.

كشف التزييف العميق (Deepfakes):**
كيفية تمييز الصور أو الفيديوهات المفبركة (التدقيق في تفاصيل اليدين، الانعكاسات الغريبة، أو الصوت المعدني).
* القاعدة الذهبية: التحقق عبر مقاطعة المصادر المختلفة.

5: الأخلاقيات والأثر (رؤية مستقبلية)**

حقوق الملكية:** لمن تعود ملكية الصورة التي أنشأها الذكاء الاصطناعي؟
الأثر البيئي:** استهلاك المياه والطاقة في مراكز البيانات الضخمة.
المستقبل:** هل سيحل الذكاء الاصطناعي محلنا أم سيكون مساعداً لنا؟

نصيحة إضافية:** بما أنك تستهدف منطقة الخليج، يفضل استخدام مصطلحات مثل "التحول الرقمي" (Digital Transformation) و"الابتكار" (Innovation) في مقدمة عرضك، فهي كلمات رنانة جداً لدى صناع القرار هناك.
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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
Garantie Le-Bon-Prof
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