Data Management With Python, SQLite, and SQLAlchemy

In this tutorial, you’ll learn how to use:

1⃣ Flat files for data storage
🔢 SQL to improve access to persistent data
🔢 SQLite for data storage
🔢 SQLAlchemy to work with data as Python objects

Enroll Free: https://realpython.com/python-sqlite-sqlalchemy/

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https://t.me/DataScience4

🖥 190 Python projects

Link: https://amankharwal.medium.com/130-python-projects-with-source-code-61f498591bb

#DataAnalytics #Python #SQL #RProgramming #DataScience #MachineLearning #DeepLearning #Statistics #DataVisualization #PowerBI #Tableau #LinearRegression #Probability #DataWrangling #Excel #AI #ArtificialIntelligence #BigData #DataAnalysis #NeuralNetworks #SupervisedLearning #LearnDataScience #LLM #RAG #Mathematics #PythonProgramming

https://t.me/CodeProgrammer 🖥

Find your location on Map using Python

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https://t.me/CodeProgrammer 🖥

"Introduction to Python Programming"

This 415-pages #FREE book is perfect if you are starting your #Python journey.

Download book: https://t.co/aMLeAQre6r

#DataAnalytics #DataScience #MachineLearning #DeepLearning #Statistics #Probability #AI #ArtificialIntelligence #BigData #DataAnalysis #NeuralNetworks #Mathematics #PythonProgramming

https://t.me/CodeProgrammer ✅

A Complete Course to Learn Robotics and Perception

Notebook-based book "Introduction to Robotics and Perception" by Frank Dellaert and Seth Hutchinson

github.com/gtbook/robotics

roboticsbook.org/intro.html

#Robotics #Perception #AI #DeepLearning #ComputerVision #RoboticsCourse #MachineLearning #Education #RoboticsResearch #GitHub

⚡️ BEST DATA SCIENCE CHANNELS ON TELEGRAM 🌟

Python Cheat Sheet

#AI #SentimentAnalysis #DataVisualization #pandas #Numpy #InteractiveDesign #NLP #MachineLearning #Python #GitHubProjects #TowardsDataScience

⚡️ Our Telegram channels: https://t.me/addlist/0f6vfFbEMdAwODBk

📱 Our WhatsApp channel: https://whatsapp.com/channel/0029VaC7Weq29753hpcggW2A

🔖 Preparing for Data Science Interviews
📝 With LeetCode FAQs

👨🏻‍💻 If you're aiming for top tech companies like Google or Amazon, it's natural to feel overwhelmed and unsure where to begin. I’ve been there too—facing tons of questions without a clear roadmap of what to study or when.

✏️ That’s why I decided to create a step-by-step plan for myself. In this guide, I’ve compiled the most frequently asked LeetCode questions, complete with solutions, techniques, and patterns to help you master the kinds of problems that big companies love to ask.

✅ Whether you're just starting out or sharpening your interview skills, this resource is designed to give you clarity, focus, and confidence.

📂 Stay tuned — I’ll be sharing the full file soon!

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✉️ Our Telegram channels: https://t.me/addlist/0f6vfFbEMdAwODBk

📱 Our WhatsApp channel: https://whatsapp.com/channel/0029VaC7Weq29753hpcggW2A

Part 3: Enterprise Web Scraping – Building Scalable, Compliant, and Future-Proof Data Extraction Systems

Duration: ~60 minutes

Link A: https://hackmd.io/@husseinsheikho/WS-3A

Link B (Rest): https://hackmd.io/@husseinsheikho/WS-3B

#EnterpriseScraping #DataEngineering #ScrapyCluster #MachineLearning #RealTimeData #Compliance #WebScraping #BigData #CloudScraping #DataMonetization

✉️ Our Telegram channels: https://t.me/addlist/0f6vfFbEMdAwODBk

📱 Our WhatsApp channel: https://whatsapp.com/channel/0029VaC7Weq29753hpcggW2A

In Python, building AI-powered Telegram bots unlocks massive potential for image generation, processing, and automation—master this to create viral tools and ace full-stack interviews! 🤖

# Basic Bot Setup - The foundation (PTB v20+ Async)
from telegram.ext import Application, CommandHandler, MessageHandler, filters

async def start(update, context):
    await update.message.reply_text(
        "✨ AI Image Bot Active!\n"
        "/generate - Create images from text\n"
        "/enhance - Improve photo quality\n"
        "/help - Full command list"
    )

app = Application.builder().token("YOUR_BOT_TOKEN").build()
app.add_handler(CommandHandler("start", start))
app.run_polling()

# Image Generation - DALL-E Integration (OpenAI)
import openai
from telegram.ext import ContextTypes

openai.api_key = os.getenv("OPENAI_API_KEY")

async def generate(update: Update, context: ContextTypes.DEFAULT_TYPE):
    if not context.args:
        await update.message.reply_text("❌ Usage: /generate cute robot astronaut")
        return
    
    prompt = " ".join(context.args)
    try:
        response = openai.Image.create(
            prompt=prompt,
            n=1,
            size="1024x1024"
        )
        await update.message.reply_photo(
            photo=response['data'][0]['url'],
            caption=f"🎨 Generated: *{prompt}*",
            parse_mode="Markdown"
        )
    except Exception as e:
        await update.message.reply_text(f"🔥 Error: {str(e)}")

app.add_handler(CommandHandler("generate", generate))

Learn more: https://hackmd.io/@husseinsheikho/building-AI-powered-Telegram-bots

#Python #TelegramBot #AI #ImageGeneration #StableDiffusion #OpenAI #MachineLearning #CodingInterview #FullStack #Chatbots #DeepLearning #ComputerVision #Programming #TechJobs #DeveloperTips #CareerGrowth #CloudComputing #Docker #APIs #Python3 #Productivity #TechTips

https://t.me/DataScienceM 🦾