#Sql Basics For Data Science

DSA Practice cheatsheet #engineering #instadaily #instagood .

All SQl Join Methods || Save For Later 📲 Boost your web dev skills 🧑‍💻 Follow @de.code.dev for more @de.code.dev . . Learn Coding Frontend development, web development, HTML, CSS, JavaScript, React, Python #webdev #frontenddev #learntocode #javascript #reactjs #codinglife #fblifestyle

Here’s a roadmap to help you go from a software engineer to a data scientist 👩‍💻 👇 If you’re tired of writing vanilla apps and want to build ML systems instead, this one’s for you. Step 1 – Learn Python and SQL (not Java, C++, or JavaScript). → Focus on pandas, numpy, scikit-learn, matplotlib → For SQL: use LeetCode or StrataScratch to practice real-world queries → Don’t just write code—learn to think in data Step 2 – Build your foundation in statistics + math. → Start with Practical Statistics for Data Scientists → Learn: probability, hypothesis testing, confidence intervals, distributions → Brush up on linear algebra (vectors, dot products) and calculus (gradients, chain rule) Step 3 – Learn ML the right way. → Do Andrew Ng’s ML course (Deeplearning.ai) → Master the full pipeline: cleaning → feature engineering → modeling → evaluation → Read Elements of Statistical Learning or Sutton & Barto if you want to go deeper Step 4 – Build 2–3 real, messy projects. → Don’t follow toy tutorials → Use APIs or scrape data, build full pipelines, and deploy using Streamlit or Gradio → Upload everything to GitHub with a clear README Step 5 – Become a storyteller with data. → Read Storytelling with Data by Cole Knaflic → Learn to explain your findings to non-technical teams → Practice communicating precision/recall/F1 in simple language Step 6 – Stay current. Never stop learning. → Follow PapersWithCode (it's now sun-setted, use huggingface.co/papers/trending, ArXiv Sanity, and follow ML practitioners on LinkedIn → Join communities, follow researchers, and keep shipping new experiments ------- Save this for later. Tag a friend who’s trying to make the switch. [software engineer to data scientist, ML career roadmap, python for data science, SQL for ML, statistics for ML, data science career guide, ML project ideas, data storytelling, becoming a data scientist, ML learning path 2025]

Part 1 Coding Series ✨ 3 SQL tools you should know 📊 Follow @sundaskhalidd for data science, tech, and AI educational content✨ #sql #learntocode #datascience #dataanalyst #python #datascientist #dataengineer #chagpt #bard #ai #learndatascience #dataanalytics #dataanalysis #codinglife #programminglife

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nobody talks about SQL but it is one of the most requested skills in every data, backend, and analytics job posting right now. if you can write a clean query you are already ahead of half the applicants. save this and actually start this week because this one skill alone has landed people six figure jobs. #sql #datascience #machinelearning #ai #cs

Practice SQL for free 📈 SQL in one of the must-know languages for all data roles including data scientist, data analyst and data engineer! How did you learn SQL? 🔗 Link to the website: stratascratch.com/?via=sundas 🎥 YouTube SQL series: YouTube.com/sundaskhalid Follow @sundaskhalidd for data science, tech, and AI educational content✨ #sql #learntocode #datascience #dataanalyst #python #datascientist #dataengineer #chagpt #bard #ai #learndatascience

Learn SQL with these videos By @emrcodes #coding #programmer #sql

Comment “SQL” to get links! 🚀 Want to master SQL without getting bored to tears? This mini roadmap takes you from “what is a database?” to solving complex crimes with code. 🎨 DrawSQL Stop trying to visualize complex databases in your head. This tool lets you build beautiful Entity Relationship Diagrams (ERDs) just by dragging and dropping. It is the best way to understand how tables relate to each other—Foreign Keys and Joins finally make sense when you can actually see them. ⚡ SQLBolt Perfect if you want to learn by doing, not reading. This site gives you bite-sized, interactive lessons right in your browser. No installation needed. You’ll race through the basics of SELECT, filtering, and aggregations with instant feedback on your code. 🕵️ SQL Murder Mystery The ultimate way to practice. There has been a murder in SQL City, and you have to solve it by querying the police database. You will use advanced logic, joins, and wildcards to find the killer. It turns “studying” into a detective game you actually want to play. 💡 With these resources you will: Visualize database architecture like a System Designer Master the syntax through hands-on repetition Build real-world problem-solving skills (and have fun doing it) If you are aiming for Data Analytics or Backend Engineering roles, these 3 tools are your cheat sheet. 📌 Save this post so you don’t lose the roadmap. 💬 Comment “SQL” and I’ll send you the direct links. 👉 Follow for more content on Coding, Data, and Tech Careers.

save this + follow for part 3 to see the step-by-step of how to fix each of these in SQL 😉 Comment “data” for my free 5-day data career kickstart course to learn the basics of data careers, SQL, and portfolio building 🥰 Your data can look clean on the surface and still be a disaster underneath.💀 In part 1, I used @claudeai Code to build a dirty dataset AND a full answer key from scratch. Let’s explore that dataset and see what needs to be cleaned. Here’s what we found from the first look: ↳ duplicate order IDs hiding that would cause you to overcount in every aggregation ↳ inconsistent category values such as “Books” uppercase, lowercase, and spelled wrong, all being treated as separate categories ↳ columns that looked clean but were actually full of empty strings instead of nulls, meaning a basic null check would miss them entirely The last one is the sneaky one: Somewhere upstream in the ETL pipeline, nulls got coded as empty strings. You HAVE to know to look for it. Exploring dirty data before you touch it is the step most people skip. You can’t clean what you haven’t looked at 💀

Starting TODAY… we’re officially kicking off my 30-Day SQL Bootcamp right here on Reels simple SQL from scratch Comment START for the resources Here’s our roadmap 👇 ✨ Week 1: We break down the basics — Data, DBMS, and getting your SQL software installed. ✨ Week 2: We master the backbone of every database: CRUD (Create, Read, Update, Delete). ✨ Week 3: We get smart with grouping, filtering, and aggregate functions that actually make sense. ✨ Week 4: We level up JOINS, UNIONS, SUBQUERIES — the things that make you feel like a real data analyst. Whether you’re a student, a marketer, a freelancer, or someone planning a full pivot into analytics… this free series is your first real step into the backend world of the internet. But listen… 👇 If you want the full data stack SQL to pull the data, Excel & Power BI to make it speak then you’re going to want this: My Excel & Power BI Masterclass goes LIVE on December 14th. A complete, hands-on cohort where you’ll learn to build clean, professional dashboards that impress managers and convert clients. If you’re serious about stepping into Business Intelligence… DM me “DATA” to reserve your spot for the Dec 14th batch. Spots are going quickly. Turn on notifications because Day 1 drops in the next Reel and you don’t want to miss the start. #SQL #DataAnalysis #LearnSQL #DatabaseManagement #DBMS #RelationalDatabase #DataScience #ExcelTips #PowerBI #BusinessIntelligence #CodingForBeginners #TechCareer #DataAnalyst #SQLServer #MySQL #OnlineCourse #CareerGrowth #TechSkills #ExcelCourse #StudyMotivation

Want my full toolkit? ➡️💬 Comment “LINK” and I will share all the other websites that I use when I am doing DSA! Kindly FOLLOW the account and then comment LINK as instagram does not allow sending DMs to non-followers. DSA doesn’t have to be boring text on a screen. 🙅‍♂️💻 If you are struggling to understand trees, graphs, or sorting algorithms, you need to see them in action. Visual learning > Rote memorization. Follow @techninjaah to level up your dev journey! ✅