#Data Science Tools

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#Data Science Tools Reel by @askdatadawn (verified account) - This is the EXACT order I would learn Data Science in 2026.

Hi 😊 my name is Dawn. I've been a Data Scientist at Meta, Patreon and other startups. An
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@askdatadawn
This is the EXACT order I would learn Data Science in 2026. Hi 😊 my name is Dawn. I’ve been a Data Scientist at Meta, Patreon and other startups. And have coached 20+ clients into landing their dream Data jobs in the past year. 1️⃣ Learn SQL SQL is a must-have skill for every data professional because it’s the primary way you get data OUT of a database. It’s also a very easy coding language to learn, so I would start there. Use Interview Master to learn and practice SQL (link in bio): → Learn SQL: www.interviewmaster.ai/content/sql → Practice SQL: www.interviewmaster.ai/home 2️⃣ Start building Product Sense & Business Sense Product sense & business sense basically means you know how to use Data to solve real problems. I would start building this “soft” skill early because (1) it takes time to really learn this, and (2) as you’re learning Stats and Python, you already have context on how these might be used in the real world. I found the book: Cracking the PM Career to be super helpful before I landed my first Data Science job. 3️⃣ Learn Statistics How much Stats do you need for Data Science? Just the foundations, but you need to know it really really well. → Descriptive statistics → Common distributions → Probability and Bayes’ Theorem → Basic Machine Learning models → Experimentation concepts → A/B experiment design Check out Stanford’s Introduction to Statistics, which is free on Coursera. 4️⃣ Learn Python Python is the #1 skill for Data Scientists in 2025, but I put it 4th on this list because I find that it builds on skills 1-3. I learned Python on my own using DataCamp’s Python Data Fundamentals (link in bio). 5️⃣ Use AI-assisted coding tools Many data scientists are already using tools, like Claude Code & Cursor, to 2x their productivity. And also many companies are evaluating you on your use of AI during interviews. #datascience #datascientist
#Data Science Tools Reel by @the.datascience.gal (verified account) - 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 sy
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@the.datascience.gal
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]
#Data Science Tools Reel by @chrisoh.zip - The best projects serve a real use case

Comment "data" for all the links and project descriptions

#tech #data #datascience #ml #explore
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@chrisoh.zip
The best projects serve a real use case Comment “data” for all the links and project descriptions #tech #data #datascience #ml #explore
#Data Science Tools Reel by @digitalsamaritan (verified account) - 3 AI tools you need if you hate doing data analysis work!

Of course, this is AI so please exercise critical thinking with AI generated reports or ana
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@digitalsamaritan
3 AI tools you need if you hate doing data analysis work! Of course, this is AI so please exercise critical thinking with AI generated reports or analysis #dataanalysis #aitools
#Data Science Tools Reel by @sundaskhalidd (verified account) - Comment 'Projects' to get 5 Data Scientist Project ideas and a plan 👩🏻‍💻

♻️ repost to share with friends. Here is how to become a data scientist i
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@sundaskhalidd
Comment ‘Projects’ to get 5 Data Scientist Project ideas and a plan 👩🏻‍💻 ♻️ repost to share with friends. Here is how to become a data scientist in 2026 and beyond 📈 the original video was 4 min Andi had to cut it down to 3 because instagram. Should I do a part 3v what are other skills that you would add to the list and let me know what I should cover in the next video 👩🏻‍💻 #datascientist #datascience #python #machinelearning #sql #ai
#Data Science Tools Reel by @phdwithanjali - Stop suffering in silence. These tools will level up your analysis game!
Which one's your fav?
Comment down👇🏻
 #dataanalysis #phdlife #statsmadeeasy
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@phdwithanjali
Stop suffering in silence. These tools will level up your analysis game! Which one’s your fav? Comment down👇🏻 #dataanalysis #phdlife #statsmadeeasy #dataanalysis #rstats #prism #researchtools #scientificreels #academiaa #phd #phdwithanjali #juliusai @try_julius.ai
#Data Science Tools Reel by @swerikcodes (verified account) - The best data structures and algorithms resources you need if you're studying computer science #coding #learntocode #dsa #datastructuresandalgorithms
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@swerikcodes
The best data structures and algorithms resources you need if you’re studying computer science #coding #learntocode #dsa #datastructuresandalgorithms #cs #computerscience #codingforbeginners
#Data Science Tools Reel by @jessramosdata (verified account) - Comment "project" for my full video that breaks each of these projects down in detail with examples from my own work.

If you're using the Titanic, Ir
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@jessramosdata
Comment “project” for my full video that breaks each of these projects down in detail with examples from my own work. If you’re using the Titanic, Iris, or COVID-19 dataset for data analytics projects, STOP NOW! These are so boring and over used and scream “newbie”. You can find way more interesting datasets for FREE on public data sites and you can even make your own using ChatGPT or Claude! Here are the 3 types of projects you need: ↳Exploratory Data Analysis (EDA): Exploring a dataset to uncover insights through descriptive statistics (averages, ranges, distributions) and data visualization, including analyzing relationships between variables ↳Full Stack Data Analytics Project: An end-to-end project that covers the entire data pipeline: wrangling data from a database, cleaning and transforming it. It demonstrates proficiency across multiple tools, not just one. ↳Funnel Analysis: Tracking users or items move from point A to point B, and how many make it through each step in between. This demonstrates a deeper level of business thinking by analyzing the process from beginning to end and providing actionable recommendations to improve it Save this video for later + send to a data friend!
#Data Science Tools Reel by @data_pumpkin - In my first years as a data scientist, I wasted hours on broken SQL, slow pandas scripts, messy Flask deployments, and "works on my machine" chaos.

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@data_pumpkin
In my first years as a data scientist, I wasted hours on broken SQL, slow pandas scripts, messy Flask deployments, and “works on my machine” chaos. These 4 tools fixed that: • dbt → modular, documented SQL transformations • Polars → faster, cleaner alternative to pandas • FastAPI → quick, reliable model deployment • Docker → consistent environments, no more deployment nightmares If you’re just starting out, learning these early will save you months of frustration.
#Data Science Tools Reel by @maggieindata (verified account) - Comment PROJECT to access my step-by-step Python tutorial that anyone can follow to build your very first geospatial dashboard web app! 🌍📊

A good n
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@maggieindata
Comment PROJECT to access my step-by-step Python tutorial that anyone can follow to build your very first geospatial dashboard web app! 🌍📊 A good number of portfolio projects is 3–5, and the types of projects you choose should reflect the kind of data role you’re going after. A data analyst portfolio should look very different from a machine learning engineer one. Even within data science, a product/decision data scientist portfolio should focus on A/B testing and metrics storytelling—while an algorithm data scientist portfolio might highlight modeling and experimentation. ✨ Especially if you’re building your very first project, prioritize: 🌱 Real-world messiness (not polished Kaggle sets) 🌱 Business context and decision-making 🌱 Clear documentation (what you did and why) 🌱Visuals to help your work stand out No one’s asking for perfection—they want to see how you think. #datascienceportfolio #dataanalyst #learnpython #codingjourney #techcareers
#Data Science Tools Reel by @volkan.js (verified account) - Comment "DATA" for the links.

You Will Never Struggle With Data Science Again

📌 Learn the most important foundations with these beginner-friendly r
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@volkan.js
Comment "DATA" for the links. You Will Never Struggle With Data Science Again 📌 Learn the most important foundations with these beginner-friendly resources: 1️⃣ Learn Python for Data Science – FreeCodeCamp’s full beginner course 2️⃣ Essence of Linear Algebra – 3Blue1Brown’s visual, intuitive playlist 3️⃣ Statistics – A Full Lecture (2025) – step-by-step breakdown of core stats concepts Stop feeling overwhelmed by Python, statistics, or linear algebra. These tutorials simplify the fundamentals of Data Science with clear explanations, visuals, and real-world examples. Whether you’re preparing for a career in Data Science, getting into machine learning, or just curious about data analysis, this is the fastest way to finally understand how it all fits together. Save this post, share it, and turn confusion into clarity with Python, Stats, and Linear Algebra for Data Science 📊
#Data Science Tools Reel by @volkan.js (verified account) - Comment "Link" to get the links!

You Will Never Struggle With Data Structures & Algorithms Again

🔗 Explore these free visualization tools:

1️⃣ vis
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@volkan.js
Comment "Link" to get the links! You Will Never Struggle With Data Structures & Algorithms Again 🔗 Explore these free visualization tools: 1️⃣ visualgo.net 2️⃣ cs.usfca.edu 3️⃣ csvistool.com Stop memorizing code blindly. See every algorithm in action — arrays, linked lists, stacks, queues, trees, graphs, sorting, searching, and more. These interactive platforms show step-by-step exactly how data flows and how operations work. Whether you’re preparing for coding interviews, studying computer science, or just starting with DSA, this is the fastest way to master the fundamentals. Save this, share it, and turn complex algorithms into simple visuals you’ll never forget.

✨ #Data Science Tools Discovery Guide

Instagram hosts 12K posts under #Data Science Tools, creating one of the platform's most vibrant visual ecosystems. This massive collection represents trending moments, creative expressions, and global conversations happening right now.

The massive #Data Science Tools collection on Instagram features today's most engaging videos. Content from @volkan.js, @the.datascience.gal and @chrisoh.zip and other creative producers has reached 12K posts globally. Filter and watch the freshest #Data Science Tools reels instantly.

What's trending in #Data Science Tools? The most watched Reels videos and viral content are featured above. Explore the gallery to discover creative storytelling, popular moments, and content that's capturing millions of views worldwide.

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🌟 Featured Creators: @volkan.js, @the.datascience.gal, @chrisoh.zip and others leading the community

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✅ Moderate Competition

💡 Top performing posts average 900.7K views (2.4x above average). Moderate competition - consistent posting builds momentum.

Post consistently 3-5 times/week at times when your audience is most active

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💡 Top performing content gets over 10K views - focus on engaging first 3 seconds

✨ Many verified creators are active (75%) - study their content style for inspiration

✍️ Detailed captions with story work well - average caption length is 773 characters

📹 High-quality vertical videos (9:16) perform best for #Data Science Tools - use good lighting and clear audio

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