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v2.5 StablePikory 2026
Discovery Intelligence

#Data Science Roadmap

Total Volume
18KLive
Discovery Velocity
Viral
Initial Sampling
12 Items
Hashtag StatsBased on recent activity
Total Posts
18K
Avg. Views
689,429
Best Performing Reel View
5,323,286 Views
Analyzed Creators
11
Performance Context
Initial Batch12 reels analyzed

Trending Feed

12 posts loaded

Data Scientist Roadmap 
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#reels #viral #trendingree
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Data Scientist Roadmap . . . . . #reels #viral #trendingreels #newcollection #viralvideos #reelsvideo #reelsinstagram #shorts #trending #viralreels

DATA SCIENCE ROADMAP FROM GOOGLE DATA SCIENTISTS
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DATA SCIENCE ROADMAP FROM GOOGLE DATA SCIENTISTS . . . #datascience #google #nodaysoff #AI #sql #python #roadmap #cheatsheet

Here’s a roadmap to help you go from a software engineer to
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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]

Comment ‘Projects’ to get 5 Data Scientist Project ideas and
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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 Roadmap from a Googler❤️

Recently I spoke to s
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Data Science Roadmap from a Googler❤️ Recently I spoke to several friends here in the Bay Area, one of them is a data scientist at google, some are data scientists at walmart, and a few others working in California! Based on their 4-10 years of experience in the field, I have designed a beginner friendly roadmap: ✅Covering 4 Month Timeline ✅Topics to cover and their resources ✅Frequently asked questions #datascience #google #softwareengineer #indiansinusa #jobsearch

This is the EXACT order I would learn Data Science in 2026.
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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

Your Complete Data Science Roadmap in 11 Videos 🚀

🔖Save t
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Your Complete Data Science Roadmap in 11 Videos 🚀 🔖Save this post → Your future self will thank you Stop jumping between courses. These 11 playlists cover EVERYTHING you need to become job-ready in Data Science & AI: 📊 Foundation Layer: → Python for Data Science - Nicholas Renotte (5hrs) → DSA in Python - CampusX (Mega Video) → Statistics for Data Science - Krish Naik (6hrs) 💼 Data Analytics Stack: → Ultimate Data Analyst Bootcamp - Alex The Analyst (24hrs) SQL | Excel | Tableau | Power BI | Python | Azure 🤖 Machine Learning & Deep Learning: → 100 Days of ML - CampusX → 100 Days of DL - CampusX → Neural Networks: Zero to Hero - Andrej Karpathy ⚡ Modern AI Stack: → FastAPI - Tech With Tim → Generative AI with LangChain - CampusX → Agentic AI with LangGraph - CampusX Bonus: → Databricks Data Engineer Certification - FreeCodeCamp Each playlist = One skill mastered. Follow this sequence, build projects alongside, and you'll have a portfolio that stands out. All videos are FREE. No excuses. Just consistent effort. Which skill are you starting with? Drop it in comments 👇 📲 Follow @datasciencebrain #datasciencebrain for Daily Notes 📝, Tips ⚙️ and Interview QA🏆 . . . . . . [datascienceroadmap, airoles, mlengineerpath, datasciencejobs, analyticscareer, datatechskills, mlopsengineer, dataengineerskills, aiindustrytrends, techlearningguide] #datascience #machinelearning #python #ai #dataanalytics #artificialintelligence #deeplearning #bigdata #agenticai #aiagents #statistics #dataanalysis #datavisualization #analytics #datascientist #neuralnetworks #100daysofcode #genai #llms #datasciencebootcamp

Data Analytics Road map (6-9 months)

https://drive.google.c
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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

Here is a full roadmap on how to get started with Data Scien
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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

If you want to crack Data Science jobs in the next 30 days,
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If you want to crack Data Science jobs in the next 30 days, here’s the three step process which you will follow which literally no one talks about. . . . #datascience #data #interview

Data Science Roadmap with Gen AI!! Save it & Share it

Follo
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Data Science Roadmap with Gen AI!! Save it & Share it Follow @meet_kanth #datascience #course #roadmap #generativeai #2026

🔥 How to Become a Data Scientist in 2026
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🔥 How to Become a Data Scientist in 2026 . . { data scientist roadmap, data science 2026, ai ml careers, python sql, machine learning projects } . #datascience #datascientist #aicareers #machinelearning #intellipaat

Top Creators

Most active in #data-science-roadmap

Semantic Clustering

Reels Graph Intelligence.

Advanced mapping of high-affinity Instagram Reels semantic patterns identified within the #data-science-roadmap ecosystem.

Strategic Implementation

Our semantic engine has identified these specific pattern clusters as high-affinity matches for #data-science-roadmap. Integrated usage of #data-science-roadmap with strategic Reels tags like #data science and #science is statistically linked to a significant increase in initial Reels discovery velocity.

In-Depth Hashtag Analysis: #data-science-roadmap

Expert Review • June 5, 2026 • Based on 12 Reels

Executive Overview

#data-science-roadmap is an actively used Instagram hashtag. Across the 12 trending reels analyzed on this page, the content has accumulated a combined total of 8,273,147 views— demonstrating strong content velocity within this content vertical. The top creator ecosystem features 8 notable accounts, led by @onseventhsky with 5,323,286 total views. The hashtag's semantic network includes 15 related keywords such as #data science, #science, #sciences, indicating its position within a broader content cluster.

Avg. Views / Reel
689,429
8,273,147 total
Viral Ceiling
5,323,286
Best Performing Reel
Unique Creators
8
12 reels analyzed

Viewership & Reach Analysis

The 12 reels in this dataset have generated a combined 8,273,147 views, translating to an average of 689,429 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.

Top Performing Reel

The highest-performing reel in this dataset received 5,323,286 views. This viral outlier performance is 772% 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 #data-science-roadmap 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 5,323,286. The top three creators — @onseventhsky, @the.datascience.gal, and @vee_daily19 — together account for 91.0% of the total views in this dataset. The semantic network of #data-science-roadmap extends across 15 related hashtags, including #data science, #science, #sciences, #roadmap. Creators often use these tags together to reach overlapping audiences.

Discoverability & Reach Potential

The discoverability metrics for #data-science-roadmap indicate an active content ecosystem. The average of 689,429 views per reel demonstrates consistent audience reach. For creators using #data-science-roadmap, high-quality production and strong hooks in the first 1-2 seconds tend to perform best given the competition.

Analyst Verdict

#data-science-roadmap demonstrates the hallmarks of a well-performing Instagram hashtag. With an average of 689,429 views per reel, the viewership metrics position this hashtag as a premium discovery vehicle. Creators like @onseventhsky and @the.datascience.gal are leading the charge, setting viewership benchmarks for the community.

Frequently Asked Questions

Everything about #data-science-roadmap on Instagram

Frequently Asked Questions

How popular is the #data science roadmap hashtag?

Currently, #data science roadmap has over 18K public posts on Instagram. It is a highly active community focus area for creators and brands.

Can I download reels from #data science roadmap anonymously?

Yes, Pikory allows you to view and download public reels tagged with #data science roadmap without an account and without notifying the content creators.

What are the most related tags to #data science roadmap?

Based on our semantic analysis, tags like #sciences, #datae, #sciencing are frequently used alongside #data science roadmap.
#data science roadmap Instagram Discovery & Analytics 2026 | Pikory