Trending Feed
12 posts loaded

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

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

What is Data Science? 🤖📊 It’s literally where human intelligence meets computer science — a field where we actually predict the future using data. 🔮 Companies study graphs, maps, past trends, and millions of data points to understand what might happen next… because yes, history repeats itself. Election agencies even pay millions for prediction models before the results are out. 🗳️📈 And tech companies? They track your behaviour to recommend products, personalize your apps, and show ads you’re most likely to click. 🎯📱 If you want to enter the world of Data Science, here are the 3 skills you NEED: 1️⃣ Mathematics — statistics & probability 2️⃣ Programming — Python or R for analysis & visualization 3️⃣ Machine Learning Algorithms — including regressions 🤝🤖 Comment “Data Science + your favourite company” and I’ll send you a full beginner-friendly roadmap! Follow @podus.app for more tech breakdowns, coding insights, and career guides. 🚀✨ #datascience #machinelearning #pythonprogramming #techcontent #aicommunity #programminglife #learnpython #datavisualization #techfacts #techreels #codingreels #aiml #artificialintelligence #bigdata #datatrends #datascientist #analytics #mlalgorithms #statistics #probability #codinglife #techcreator #techguide #computerscience #techlearning #futuretech #programmingtutorial #dataanalysis #reelsinstagram #podus

The best projects serve a real use case Comment “data” for all the links and project descriptions #tech #data #datascience #ml #explore

Data Interpretation Mind Map + Important Formulas 📊 | UGC NET Paper 1 Quick Revision

Here is a full roadmap on how to get started with Data Science. Comment “DATA” for the full roadmap pdf. #datascience #machinelearning #coding #ai #university

Data Analytics Road map (6-9 months) https://drive.google.com/drive/folders/17KOCp6F1JGqOCwIdryzcDykNCSu93Ltc?usp=sharing Built from my personal interview experiences(Interviews given - 5+) Duration - 1-2 Months - Basics Learn basic - intermediate SQL(joins) from youtube/udemy Basic Python from youtube/udemy/Leetcode Basic Excel Duration 2-3 Months - Intermediate Practice intermediate to advanced SQL on Data Lemur/Leetcode/WiseOwl Practice easy-intermediate python questions on Leetcode/Hackerrank Start BI - Power BI tutorial from youtube/udemy Duration 3-4 Months - Advanced Learn Pandas/pyspark, practice EDA on csv files from Kaggle datasets on jupyter notebook/colab Practice advanced SQL questions(window functions) Build BI projects from kaggle datasets/Datacamp Github profile to showcase your projects + LinkedIn Theoretical knowledge on ETL pipelines/ Data warehousing concepts(Chat GPT) Resources SQL - Theory - W3Schools(free)/Udemy(paid), Practice - Leetcode/Data Lemur Python - Theory - Youtube/Udemy, Practice - Leetcode(easy to medium) Data Warehousing+ETL - Tutorials Point/Udemy, Datacamp/Chat GPT Power BI/Tableau - Datacamp, wiseowl Pandas/Pyspark - Datacamp, Leetcode, Kaggle Basic Excel . . . . . . #big4 #fyp #data #analytics #ootd #grwm

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 📊

Day 1 - Inferential and Descriptive Statistics Hope this helpful, let me know if you want more such videos. Follow for more #datascience #machinelearning #womeninstem #learnintogether #progresseveryday #tech #consistency #statistics

Repost to share with friends ♻️ Here’s how to become a data analyst in 2026 and beyond? 📈 The original video was 5 minutes long and I had to cut it down to 3 minutes because instagram. One part that got cut off was the job market. Should I post a part 2? what are other skills that would you add to the list?? #dataanalysis #dataanalyst #sql #python

Learn DATA ANALYTICS FOR FREE 🔥 • • • If you are interested in learning Data Analytics for Free then, this reel is very important for you as I have made a COMPLETE ROADMAP of what you need to do for the next 6 months along with where you can get the free resources! Do share it amongst your friends and follow @kavach.khanna01 for such value! #dataanalytics #dataanalyticsforfree #learndata #learndatascience #kavachkhanna

Learn these to become a data analyst! . . #canada #canadajobs #canadastudents #canadalife #data #dataanalytics #datascience
Top Creators
Most active in #what-is-data
Reels Graph Intelligence.
Advanced mapping of high-affinity Instagram Reels semantic patterns identified within the #what-is-data ecosystem.
Strategic Implementation
Our semantic engine has identified these specific pattern clusters as high-affinity matches for #what-is-data. Integrated usage of #what-is-data with strategic Reels tags like #what is biometric data and #what is data annotation is statistically linked to a significant increase in initial Reels discovery velocity.
In-Depth Hashtag Analysis: #what-is-data
Expert Review • June 5, 2026 • Based on 12 Reels
Executive Overview
#what-is-data is an actively used Instagram hashtag. Across the 12 trending reels analyzed on this page, the content has accumulated a combined total of 8,870,080 views— demonstrating strong content velocity within this content vertical. The top creator ecosystem features 8 notable accounts, led by @onseventhsky with 5,323,528 total views. The hashtag's semantic network includes 100 related keywords such as #what is biometric data, #what is data annotation, #datas, indicating its position within a broader content cluster.
Viewership & Reach Analysis
The 12 reels in this dataset have generated a combined 8,870,080 views, translating to an average of 739,173 views per reel. This exceptionally high average viewership indicates that content in this hashtag frequently hits the Explore page or Reels tab, driving massive exposure beyond the creator's immediate follower base.
The highest-performing reel in this dataset received 5,323,528 views. This viral outlier performance is 720% of the average reel performance in this set. This significant gap between the top performer and the average highlights the "viral lottery" nature of this hashtag — breakout hits can achieve massive scale.
Content Overview & Top Creators
The #what-is-data ecosystem is dominated by short-form video content (Reels), aligning with Instagram's algorithmic preference for video-first distribution. There are 8 distinct accounts contributing to the trending feed. The top creator, @onseventhsky, has contributed 1 reel with a total viewership of 5,323,528. The top three creators — @onseventhsky, @sahilgogna_, and @sundaskhalidd — together account for 90.2% of the total views in this dataset. The semantic network of #what-is-data extends across 100 related hashtags, including #what is biometric data, #what is data annotation, #datas, #what is. Creators often use these tags together to reach overlapping audiences.
Discoverability & Reach Potential
The discoverability metrics for #what-is-data indicate an active content ecosystem. The average of 739,173 views per reel demonstrates consistent audience reach. For creators using #what-is-data, high-quality production and strong hooks in the first 1-2 seconds tend to perform best given the competition.
Analyst Verdict
#what-is-data demonstrates the hallmarks of a well-performing Instagram hashtag. With an average of 739,173 views per reel, the viewership metrics position this hashtag as a premium discovery vehicle. Creators like @onseventhsky and @sahilgogna_ are leading the charge, setting viewership benchmarks for the community.
Frequently Asked Questions
Everything about #what-is-data on Instagram
Global Reels Trends
Explore high-velocity Instagram Reels hashtags currently shaping global discovery.










