Over the last year, several articles have been written to help candidates prepare for data science technical interviews. These resources cover a wide range of topics including machine learning, SQL, programming, statistics, and probability.

1️⃣ Machine Learning (ML) Interview
Types of ML Q&A in Data Science Interview
https://shorturl.at/syN37

ML Interview Q&A for Data Scientists
https://shorturl.at/HVWY0

Crack the ML Coding Q&A
https://shorturl.at/CDW08

Deep Learning Interview Q&A
https://shorturl.at/lHPZ6

Top LLMs Interview Q&A
https://shorturl.at/wGRSZ

Top CV Interview Q&A [Part 1]
https://rb.gy/51jcfi

Part 2
https://rb.gy/hqgkbg

Part 3
https://rb.gy/5z87be

2️⃣ SQL Interview Preparation
13 SQL Statements for 90% of Data Science Tasks
https://rb.gy/dkdcl1

SQL Window Functions: Simplifying Complex Queries
https://t.ly/EwSlH

Ace the SQL Questions in the Technical Interview
https://lnkd.in/gNQbYMX9

Unlocking the Power of SQL: How to Ace Top N Problem Questions
https://lnkd.in/gvxVwb9n

How To Ace the SQL Ratio Problems
https://lnkd.in/g6JQqPNA

Cracking the SQL Window Function Coding Questions
https://lnkd.in/gk5u6hnE

SQL & Database Interview Q&A
https://lnkd.in/g75DsEfw

6 Free Resources for SQL Interview Preparation
https://lnkd.in/ghhiG79Q

3️⃣ Programming Questions
Foundations of Data Structures [Part 1]
https://lnkd.in/gX_ZcmRq

Part 2
https://lnkd.in/gATY4rTT

Top Important Python Questions [Conceptual]
https://lnkd.in/gJKaNww5

Top Important Python Questions [Data Cleaning and Preprocessing]
https://lnkd.in/g-pZBs3A

Top Important Python Questions [Machine & Deep Learning]
https://lnkd.in/gZwcceWN

Python Interview Q&A
https://lnkd.in/gcaXc_JE

5 Python Tips for Acing DS Coding Interview
https://lnkd.in/gsj_Hddd

4️⃣ Statistics
Mastering 5 Statistics Concepts to Boost Success
https://lnkd.in/gxEuHiG5

Mastering Hypothesis Testing for Interviews
https://lnkd.in/gSBbbmF8

Introduction to A/B Testing
https://lnkd.in/g35Jihw6

Statistics Interview Q&A for Data Scientists
https://lnkd.in/geHCCt6Q

5️⃣ Probability
15 Probability Concepts to Review [Part 1]
https://lnkd.in/g2rK2tQk

Part 2
https://lnkd.in/gQhXnKwJ

Probability Interview Q&A [Conceptual Questions]
https://lnkd.in/g5jyKqsp

Probability Interview Q&A [Mathematical Questions]
https://lnkd.in/gcWvPhVj

🔜 All links are available in the GitHub repository:
https://lnkd.in/djcgcKRT

#DataScience #InterviewPrep #MachineLearning #SQL #Python #Statistics #Probability #CodingInterview #AIBootcamp #DeepLearning #LLMs #ComputerVision #GitHubResources #CareerInDataScience

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😉 A list of the best YouTube videos
✅ To learn data science


1️⃣ SQL language


⬅️ Learning

💰 4-hour SQL course from zero to one hundred

💰 Window functions tutorial

⬅️ Projects

📎 Starting your first SQL project

💰 Data cleansing project

💰 Restaurant order analysis

⬅️ Interview

💰 How to crack the SQL interview?

➖➖➖

2️⃣ Python


⬅️ Learning

💰 12-hour Python for Data Science course

⬅️ Projects

💰 Python project for beginners

💰 Analyzing Corona Data with Python

⬅️ Interview

💰 Python interview golden tricks

💰 Python Interview Questions

➖➖➖

3️⃣ Statistics and machine learning


⬅️ Learning

💰 7-hour course in applied statistics

💰 Machine Learning Training Playlist

⬅️ Projects

💰 Practical ML Project

⬅️ Interview

💰 ML Interview Questions and Answers

💰 How to pass a statistics interview?

➖➖➖

4️⃣ Product and business case studies


⬅️ Learning

💰 Building strong product understanding

💰 Product Metric Definition

⬅️ Interview

💰 Case Study Analysis Framework

💰 How to shine in a business interview?

#DataScience #SQL #Python #MachineLearning #Statistics #BusinessAnalytics #ProductCaseStudies #DataScienceProjects #InterviewPrep #LearnDataScience #YouTubeLearning #CodingInterview #MLInterview #SQLProjects #PythonForDataScience

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

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

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