#Data Science Applications

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#Data Science Applications 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 Applications 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 Applications Reel by @vee_daily19 (verified account) - 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.
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@vee_daily19
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 Applications 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 Applications 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 Applications Reel by @chrispathway (verified account) - Here is a full roadmap on how to get started with Data Science. Comment "DATA" for the full roadmap pdf.

#datascience #machinelearning #coding #ai #u
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@chrispathway
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 Science Applications Reel by @sabrina_ramonov (verified account) - Learn data science fundamentals for free! STEM background recommened but not required for most courses. - free data science courses? - best way to lea
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@sabrina_ramonov
Learn data science fundamentals for free! STEM background recommened but not required for most courses. - free data science courses? - best way to learn data science online? - how do I learn data science? #ai #datascience #learning #sabrinaramonov
#Data Science Applications Reel by @bri_xu (verified account) - Data Science 4 All is a free training program that makes data science shockingly uncomplicated
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@bri_xu
Data Science 4 All is a free training program that makes data science shockingly uncomplicated
#Data Science Applications Reel by @woman.engineer (verified account) - 📍How to prepare for Data Scientist role in 2026 🚀

CORE SKILLS YOU MUST MASTER: Programming You must be fluent in:

● Python

● NumPy

● Pandas

● S
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@woman.engineer
📍How to prepare for Data Scientist role in 2026 🚀 CORE SKILLS YOU MUST MASTER: Programming You must be fluent in: ● Python ● NumPy ● Pandas ● Scikit-learn Writing clean, readable, bug free code Data transformations without IDE help Expect: ● Data cleaning ● Feature extraction ● Aggregations ● Writing logic heavy code SQL Almost every Data Science role tests SQL. You should be comfortable with: ● Joins - inner, left, self ● Window functions ● Grouping & aggregations ● Subqueries ● Handling NULLs Statistics & Probability: ● Probability distributions ● Hypothesis testing ● Confidence intervals ● A/B testing ● Correlation vs causation ● Sampling bias Machine Learning Fundamentals. You must know: ● Supervised vs Unsupervised learning ● Regression & Classification ● Bias Variance tradeoff ● Overfitting / Underfitting Evaluation metrics: ● Accuracy ● Precision / Recall ● F1-score ● ROC-AUC ● RMSE FEATURE ENGINEERING & DATA UNDERSTANDING: ● This is where strong candidates stand out. ● Handling missing data ● Encoding categorical variables ● Feature scaling ● Outlier treatment CORE SKILLS YOU MUST MASTER: Programming You must be fluent in: ● Python ● NumPy ● Pandas ● Scikit-learn Writing clean, readable, bug free code Data transformations without IDE help Expect: ● Data cleaning ● Feature extraction ● Aggregations ● Writing logic heavy code SQL Almost every Data Science role tests SQL. You should be comfortable with: ● Joins - inner, left, self ● Window functions ● Grouping & aggregations ● Subqueries ● Handling NULLs Statistics & Probability: ● Probability distributions ● Hypothesis testing ● Confidence intervals ● A/B testing ● Correlation vs causation ● Sampling bias Machine Learning Fundamentals. You must know: ● Supervised vs Unsupervised learning ● Regression & Classification ● Bias Variance tradeoff ● Overfitting / Underfitting Evaluation metrics: ● Accuracy ● Precision / Recall ● F1-score ● ROC-AUC ● RMSE +++ for more look at the comment #datascientist #aiengineer #softwareengineer #datascience #dataengineer
#Data Science Applications Reel by @devshree.17 - 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 d
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@devshree.17
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
#Data Science Applications Reel by @emrcodes (verified account) - 3 data science projects you can do in a weekend.

If you're learning data science, one of the best ways to improve is by working through real examples
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@emrcodes
3 data science projects you can do in a weekend. If you’re learning data science, one of the best ways to improve is by working through real examples. Here are three Kaggle notebooks you can explore: • Loan Prediction – predicting whether a loan gets approved based on applicant data. • Bank Churn – analyzing which customers are likely to leave a bank. • House Price Prediction – estimating house prices from property features. You can study the notebooks and also try solving the same problems yourself using the same datasets. It’s a great way to practice and see different ways people approach the same problem. Comment “DATA” and I’ll send you the notebooks. #coding #datascience #university
#Data Science Applications Reel by @datasciencebrain (verified account) - 60 Unique Data Science Project Ideas Also see 👇
Top Places to Grab Public Datasets
Kaggle Datasets
Google Dataset Search
Hugging Face Datasets Hub
UC
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@datasciencebrain
60 Unique Data Science Project Ideas Also see 👇 Top Places to Grab Public Datasets Kaggle Datasets Google Dataset Search Hugging Face Datasets Hub UCI Machine-Learning Repository AWS Open Data Registry Microsoft Research Open Data BigQuery Public Datasets (Google Cloud) Data.gov (USA) data.gov.in (India) World Bank Open Data IMF Data Portal Eurostat Open Data FiveThirtyEight GitHub Awesome-Public-Datasets (GitHub) OpenML Zenodo Figshare PapersWithCode → Datasets Quandl Registry of Open Data on Azure Special Benefits for Our Instagram Subscribers 🔻 ➡️ Free Resume Reviews & ATS-Compatible Resume Template ➡️ Quick Responses and Support ➡️ Exclusive Q&A Sessions ➡️ Data Science Job Postings ➡️ Access to MIT + Stanford Notes ➡️ Full Data Science Masterclass PDFs ⭐️ All this for just Rs.45/month! . . . . . . . #datascience #machinelearning #python #ai #dataanalytics #artificialintelligence #deeplearning #bigdata #agenticai #aiagents #statistics #dataanalysis #datavisualization #analytics #datascientist #neuralnetworks #100daysofcode #genai #llms #datasciencebootcamp #dataengineer

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