Python Courses & Resources

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Master Python with step-by-step courses – from basics to advanced projects and practical applications. Admin: @HusseinSheikho

Red:Machine Learning with Python India7 124 Educación3 433...

📈 Análisis del canal de Telegram Python Courses & Resources

El canal Python Courses & Resources (@python53) en el segmento lingüístico de Inglés es un actor destacado. Actualmente la comunidad reúne a 50 363 suscriptores, ocupando la posición 3 433 en la categoría Educación y el puesto 7 124 en la región India.

📊 Métricas de audiencia y dinámica

Desde su creación el невідомо, el proyecto ha mostrado un crecimiento acelerado, reuniendo a 50 363 suscriptores.

Según los últimos datos del 28 agosto, 2026, el canal mantiene una actividad estable. En los últimos 30 días la variación de miembros fue de 336, y en las últimas 24 horas de -2, conservando un alto alcance.

Estado de verificación: No verificado
Tasa de interacción (ER): El promedio de interacción de la audiencia es 3.12%. Durante las primeras 24 horas tras publicar, el contenido suele obtener 1.28% de reacciones respecto al total de suscriptores.
Alcance de las publicaciones: Cada publicación recibe en promedio 1 571 visualizaciones. En el primer día suele acumular 647 visualizaciones.
Reacciones e interacción: La audiencia responde de forma activa: el promedio de reacciones por publicación es 2.
Intereses temáticos: El contenido se centra en temas clave como consultation, dentist, insidead, waybienad, appointment.

📝 Descripción y política de contenido

El autor describe el recurso como un espacio para expresar opiniones subjetivas:
“Master Python with step-by-step courses – from basics to advanced projects and practical applications. Admin: @HusseinSheikho”

Gracias a la alta frecuencia de actualizaciones (últimos datos recibidos el 29 agosto, 2026), el canal mantiene la vigencia y un amplio alcance. La analítica demuestra que la audiencia interactúa activamente con el contenido, lo que lo convierte en un punto de referencia dentro de la categoría Educación.

50 363

Suscriptores

-224 horas

-317 días

+33630 días

1 571

Visitas de la publicación

~ 64724 horas

~ 93348 horas

3.12%

Tasa de compromiso

~ 2

Mensajes por día

Ads index

beta

Archivo de publicaciones

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Repost from Machine Learning with Python

Most people learn Python in random order. No wonder they feel stuck. This roadmap fixes that. Here are the 5 layers every data professional must master, in order: 𝟭. 𝗖𝗼𝗿𝗲 𝗣𝘆𝘁𝗵𝗼𝗻 (𝗙𝗼𝘂𝗻𝗱𝗮𝘁𝗶𝗼𝗻) Variables, loops, functions, error handling, collections. Do not skip this. Everything else breaks without it. 𝟮. 𝗗𝗮𝘁𝗮 𝗛𝗮𝗻𝗱𝗹𝗶𝗻𝗴 & 𝗣𝗿𝗼𝗰𝗲𝘀𝘀𝗶𝗻𝗴 Pandas, NumPy, file handling, SQL integration, data cleaning. This is where your actual job begins. 𝟯. 𝗗𝗮𝘁𝗮 𝗔𝗻𝗮𝗹𝘆𝘁𝗶𝗰𝘀 𝗟𝗶𝗯𝗿𝗮𝗿𝗶𝗲𝘀 Matplotlib, Seaborn, EDA, statistical functions, hypothesis testing. Can you turn raw data into a decision? This layer teaches you how. 𝟰. 𝗔𝗱𝘃𝗮𝗻𝗰𝗲𝗱 𝗔𝗻𝗮𝗹𝘆𝘁𝗶𝗰𝘀 & 𝗠𝗟 Scikit-Learn, clustering, feature engineering, big data tools. This is what gets you promoted. 𝟱. 𝗜𝗻𝗳𝗿𝗮𝘀𝘁𝗿𝘂𝗰𝘁𝘂𝗿𝗲 & 𝗕𝗲𝘀𝘁 𝗣𝗿𝗮𝗰𝘁𝗶𝗰𝗲𝘀 Git, virtual environments, unit testing, workflow scheduling. This is what separates professionals from beginners. The mistake most people make, they jump straight to ML without nailing the foundation. You cannot build insights on broken code. Master the layers. In order. With real data. Save this roadmap and share it with someone who needs direction. Where are you on this right now? ♻️ Repost to help someone learning Python the right way https://t.me/CodeProgrammer ✅

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🔅 Hands-On Introduction: Python

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🔅 Hands-On Introduction: Python 📝 Explore the fundamental skills you need to know as a coder to take your knowledge of Python to the next level. 🌐 Author: Ronnie Sheer 🔰 Level: Intermediate ⏰ Duration: 1h 18m 📋 Topics: Python

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AI Agents for Beginners This is Microsoft's official, structured course designed to teach AI agents from the ground up. 🎓 It provides a comprehensive curriculum covering fundamentals to deployment through exclusive video tutorials with hands-on code examples. The course is entirely free and accessible without registration. It is ideal for beginners and intermediate developers seeking to understand how AI agents reason, utilize tools, and automate real-world tasks. 🤖 Prerequisites: Basic command line experience is beneficial, though no prior AI experience is required. 📚 12 structured lessons 🏃‍♂️ Self-paced with immediate access 👨‍🏫 Created by: Microsoft Developer Team 🔗 Course Link https://github.com/microsoft/ai-agents-for-beginners #AIAgents #Microsoft #AutonomousAI #AgenticAI ➖➖➖➖➖➖➖➖➖➖➖➖➖➖

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Repost from Machine Learning with Python

Follow the Machine Learning with Python channel on WhatsApp: https://whatsapp.com/channel/0029VaC7Weq29753hpcggW2A

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🚀 Sber has released two open-source MoE models: GigaChat-3.1 Ultra and Lightning Both code and weights are available under the MIT license on HuggingFace. 👉 Key details: • Trained from scratch (not a finetune) on proprietary data and infrastructure • Mixture-of-Experts (MoE) architecture Models: 🧠 GigaChat-3.1 Ultra • 702B MoE model for high-performance environments • Outperforms DeepSeek-V3-0324 and Qwen3-235B on math and reasoning benchmarks • Supports FP8 training and MTP ⚡️ GigaChat-3.1 Lightning • 10B model (1.8B active parameters) • Outperforms Qwen3-4B and Gemma-3-4B on Sber benchmarks • Efficient local inference • Up to 256k context Engineering highlights: • Custom metric to detect and reduce generation loops • DPO training moved to native FP8 • Improvements in post-training pipeline • Identified and fixed a critical issue affecting evaluation quality 🌍 Trained on 14 languages (optimized for English and Russian) Use cases: • chatbots • AI assistants • copilots • internal ML systems Sber provides a solid open foundation for developers to build production-ready AI systems with lower infrastructure costs.