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Depuis août 2023
Professeur depuis août 2023
Computer Science and Programming, Website design, Google suits
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Àpd 13 $ /h
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In this modern world, it is hard to tell our children what will be important in the future because the world is changing by a computer. In century ago, it was possible to tell you children what they can learn. but in nowadays, the world is developing at the breakneck speed, the beauty is that computer and programmers are the one changing this. this means that their knowledge will still be on market and the new economy of 2040 will demand it still. That is why I said that we must learn programming.
Informations supplémentaires
Bring your own laptop.
You are the one to afford internet related things.
Lieu
location type icon
En ligne depuis Rwanda
Age
Enfants (7-12 ans)
Adolescents (13-17 ans)
Adultes (18-64 ans)
Seniors (65+ ans)
Niveau du Cours
Débutant
Intermédiaire
Durée
60 minutes
Enseigné en
anglais
kinyarwanda
swahili
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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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
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Practical explanations – step by step and adapted to your everyday life
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Long-term strategies for problem-solving & structured thinking
Flexible lessons in Bern or online – personal, competent & reliable

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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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Contacter Key
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Le premier cours est couvert par notre Garantie Le-Bon-Prof
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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 ?
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- 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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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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*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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