#Data Science Projects

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#Data Science Projects 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
#Data Science Projects 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 Projects 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 Projects Reel by @penelope_data - 9 data projects ideas instead of doomscrolling: (And there is a repo with the data :) ) 🤖 Machine Learning Projects * Diabetes Classification
Build
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@penelope_data
9 data projects ideas instead of doomscrolling: (And there is a repo with the data :) ) 🤖 Machine Learning Projects * Diabetes Classification
Build and compare classification models to show how data preprocessing, feature scaling, and hyperparameter tuning directly improve predictive performance. * Heart Attack Prediction
Implement an end-to-end classification pipeline—from raw data to model evaluation—to demonstrate a realistic machine learning workflow. * Medical Cost Prediction
Train a regression model to predict healthcare costs, emphasizing feature importance analysis and model optimization to explain what drives predictions. 🛠️ Data Engineering Projects * NBA Player Statistics ETL Pipeline
Design an ETL pipeline that extracts player statistics, cleans and transforms the data, and stores it in a relational database for reliable downstream analysis. * Real-Time & Batch Data Pipelines with Kafka
Build a scalable pipeline that processes streaming and batch data using Kafka, PostgreSQL, and Docker to demonstrate modern data flow architecture. * Glassdoor Job Data Pipeline
Scrape job postings, clean and structure the raw data, and prepare it for analysis and visualization to showcase real-world data ingestion challenges. 📊 Data Analytics Projects * Pokémon Dataset Analysis
Perform exploratory data analysis and feature engineering to uncover patterns in Pokémon characteristics such as types, stats, and legendary status. * Automated EDA Tool Comparison
Benchmark AutoViz, SweetViz, and Pandas Profiling across multiple datasets to evaluate performance, resource usage, and practical trade-offs. * Exploratory Job Market Analysis
Analyze cleaned job posting data to extract trends, key skills, and role distributions using visualizations and summary statistics. 👉🏻 Comment « data » to get the link to the repo and portfolio strategies! #data #students #job
#Data Science Projects Reel by @sundaskhalidd (verified account) - Part 1: These are 2 solid Data Science projects you should add to your portfolio 📈 ㅤ And I have it all written down for you 🥰 Comment "data science"
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@sundaskhalidd
Part 1: These are 2 solid Data Science projects you should add to your portfolio 📈 ㅤ And I have it all written down for you 🥰 Comment "data science" and I'll send you the link in your DMs ✨ ㅤ What other projects you would add to the list? Come back for part 2. ㅤ #datascientist #sql #machinelearning #python #dataengineer
#Data Science Projects Reel by @engineer_bhaiya_yt - Don't miss these👇🏻👇🏻 150+ Data Science projects you can try with Python 🖇️ Link👇🏻👇🏻 https://python.plainenglish.io/85-data-science-projects
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@engineer_bhaiya_yt
Don't miss these👇🏻👇🏻 150+ Data Science projects you can try with Python 🖇️ Link👇🏻👇🏻 https://python.plainenglish.io/85-data-science-projects-c03c8750599e Comment “Projects” for the link and send the reel in my dm to get early access Don't forget to share the reel with your fellow friends 😉 Project research credit goes to @amankharwal.official i have just found these projects on internet 😀 Hashtags 🔎 #DataScienceCommunity #DataScience #DataScienceProjects #DataScienceEducation #datasciences #Python #PythonProjects #PythonProjects
#Data Science Projects 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 Projects Reel by @pycode.hubb (verified account) - Comment "Projects" & I will DM You all the projects! Here are 5 Python projects that can actually help you get hired: 1️⃣ Medical Data Extraction 2️
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@pycode.hubb
Comment "Projects" & I will DM You all the projects! Here are 5 Python projects that can actually help you get hired: 1️⃣ Medical Data Extraction 2️⃣ Sports Celebrity Image Classification 3️⃣ T20 World Cup Cricket Analytics 4️⃣ Grocery Store Management System 5️⃣ Sales Insights for a Consumer Goods Brand Like this reel, comment “Projects”, and share it with your friends! Must follow to receive the source code in your DMs 👇🔥 #pythonprojects #datascienceprojects #pythonforbeginners #jobready #techreels #pycodehubb
#Data Science Projects 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 Projects 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 Projects Reel by @darshcoded - Here are 3 unique data science projects you can build in a weekend (2026 World Cup) easy. a World Cup match outcome predictor. predict win, loss, or
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@darshcoded
Here are 3 unique data science projects you can build in a weekend (2026 World Cup) easy. a World Cup match outcome predictor. predict win, loss, or draw using historical FIFA data. tech stack: Python, Pandas, Scikit-learn, and Streamlit to deploy it. medium. a player performance dashboard. pull player stats from Transfermarkt, visualize everything, and cluster players by playing style. tech stack: Python, Pandas, Plotly, and Seaborn for visualization with KMeans for clustering. hard. a real time World Cup sentiment tracker. pull live tweets during matches, run sentiment analysis as goals happen, and visualize how public opinion shifts in real time. tech stack: Python, Tweepy for the Twitter API, HuggingFace Transformers for sentiment analysis, and Plotly Dash for the live dashboard. comment “World cup” for resources to help you out along the way. #machinelearning #datascience #ai #python #cs
#Data Science Projects 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!

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