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#Data Science 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 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 Reel by @young4stem - Where are all our data scientists at! 👀👇🏻

#young4stem #datascience #job #reel #stem #computerscience
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@young4stem
Where are all our data scientists at! 👀👇🏻 #young4stem #datascience #job #reel #stem #computerscience
#Data Science 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 Reel by @priyal.py - 1. Netflix Show Clustering
Group similar shows using K-Means based on genre, rating, and duration.
Tech Stack: Python, Pandas, Scikit-learn, Seaborn
2.5M
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@priyal.py
1. Netflix Show Clustering Group similar shows using K-Means based on genre, rating, and duration. Tech Stack: Python, Pandas, Scikit-learn, Seaborn 2. Spotify Audio Feature Analyzer Analyze songs by tempo, energy and danceability using Spotify API. Tech Stack: Python, Spotipy, Matplotlib, Plotly 3. YouTube Trending Video Analyzer Discover what makes a video go viral. Tech Stack: Python, Pandas, BeautifulSoup, Seaborn 4. Resume Scanner using NLP Parse and rank resumes based on job description matching. Tech Stack: Python, SpaCy, NLTK, Streamlit 5. Crypto Price Predictor Predict BTC/ETH prices using historical data. Tech Stack: Python, LSTM (Keras), Pandas, Matplotlib 6. Instagram Hashtag Recommender Suggest hashtags based on image captions or niche. Tech Stack: Python, NLP, TF-IDF, Cosine Similarity 7. Reddit Sentiment Tracker Analyze community sentiment on hot topics using Reddit API. Tech Stack: Python, PRAW, VADER, Plotly 8. AI Job Postings Dashboard Scrape and visualize job trends by tech stack and location. Tech Stack: Python, Selenium/BeautifulSoup, Streamlit 9. Airbnb Price Estimator Predict listing prices based on location and amenities. Tech Stack: Python, Scikit-learn, Pandas, XGBoost 10. Food Calorie Image Classifier Estimate calories from food images using CNNs. Tech Stack: Python, TensorFlow/Keras, OpenCV Each project can be completed in 1-2 weekends. #datascience #machinelearning #womeninstem #learningtogether #progresseveryday #tech #consistency #projects
#Data Science Reel by @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.
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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 Reel by @meet_kanth (verified account) - Why Data Science Jobs are Difficult to Crack in 2025?? 

#datascience #machinelearning #deeplearning #artificialintelligence #generativeai #ai #data #
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@meet_kanth
Why Data Science Jobs are Difficult to Crack in 2025?? #datascience #machinelearning #deeplearning #artificialintelligence #generativeai #ai #data #mlops #llms #chatgpt #sql #datawarehouse #mentoring #agenticai #careers #jobs #dataanalytics #googleanalytics #analytics #promptengineering #pythonprogramming #dataengineer #azure #aws #devops #computerscience #masters #professionals
#Data Science 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 Reel by @datasciencebrain (verified account) - Your Complete Data Science Roadmap in 11 Videos 🚀

🔖Save this post → Your future self will thank you 

Stop jumping between courses. These 11 playli
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@datasciencebrain
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 Science Reel by @intellipaat (verified account) - Data Scientist Salary in 2026 💸📈
.
demand is rising.
companies are investing big.
and data scientists?
they're becoming the backbone of every ai-dri
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@intellipaat
Data Scientist Salary in 2026 💸📈 . demand is rising. companies are investing big. and data scientists? they’re becoming the backbone of every ai-driven decision. 2026 is the year where skills = salary. master data + ai → unlock opportunities across every industry. it’s one of the smartest career moves right now. . { data scientist salary, ai careers, data jobs 2026, career growth, tech jobs } . #datascience #datajobs #aicareers #salarytrends #futureofwork #techcareers #machinelearning #upskillnow #career2026 #intellipaat
#Data Science Reel by @onseventhsky (verified account) - Data Analytics Road map (6-9 months)

https://drive.google.com/drive/folders/17KOCp6F1JGqOCwIdryzcDykNCSu93Ltc?usp=sharing

Built from my personal int
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@onseventhsky
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
#Data Science Reel by @askdatadawn (verified account) - FREE Data Analytics learning resources.

Seriously, start here before paying for any courses.

These are FREE & a great introduction for any skill you
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@askdatadawn
FREE Data Analytics learning resources. Seriously, start here before paying for any courses. These are FREE & a great introduction for any skill you want to learn. - SQL: https://www.youtube.com/watch?v=7S_tz1z_5bA - Excel: https://www.youtube.com/watch?v=pCJ15nGFgVg - Tableau: https://www.youtube.com/watch?v=aHaOIvR00So - Python: https://www.youtube.com/watch?v=LHBE6Q9XlzI #dataanalytics #dataanalyst #datascience #womenintech #aiengineering #techcareers

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