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🔥 How to become a data scientist in 2025?


1️⃣ First of all, strengthen your foundation (math and statistics) .

✏️ If you don't know math, you'll run into trouble wherever you go. Every model you build, every analysis you do, there's a world of math behind it. You need to know these things well:

Linear Algebra: Link

Calculus: Link

Statistics and Probability: Link



2️⃣ Then learn programming !

✏️ Without further ado, get started learning Python and SQL.

Python: Link

SQL language: Link

Data Structures and Algorithms: Link



3️⃣ Learn to clean and analyze data!

✏️ Data is always messy, and a data scientist must know how to organize it and extract insights from it.

Data cleansing: Link

Data visualization: Link



4️⃣ Learn machine learning !

✏️ Once you've mastered the basic skills, it's time to enter the world of machine learning. Here's what you need to know:

◀️ Supervised learning: regression, classification

◀️ Unsupervised learning: clustering, dimensionality reduction

◀️ Deep learning: neural networks, CNN, RNN

Stanford University CS229 course: Link



5️⃣ Get to know big data and cloud computing !

✏️ Large companies are looking for people who can work with large volumes of data.

◀️ Big data tools (e.g. Hadoop, Spark, Dask)

◀️ Cloud services (AWS, GCP, Azure)



6️⃣ Do a real project and build a portfolio !

✏️ Everything you've learned so far is worthless without a real project!

◀️ Participate in Kaggle and work with real data.

◀️ Do a project from scratch (from data collection to model deployment)

◀️ Put your code on GitHub.

Open Source Data Science Projects: Link



7️⃣ It's time to learn MLOps and model deployment!

✏️ Many people just build models but don't know how to deploy them. But companies want someone who can put the model into action!

◀️ Machine learning operationalization (monitoring, updating models)

◀️ Model deployment tools: Flask, FastAPI, Docker

Stanford University MLOps Course: Link



8️⃣ Always stay up to date and network!

✏️ Follow research articles on arXiv and Google Scholar.

Papers with Code website: link

AI Research at Google website: link

#DataScience #HowToBecomeADataScientist #ML2025 #Python #SQL #MachineLearning #MathForDataScience #BigData #MLOps #DeepLearning #AIResearch #DataVisualization #PortfolioProjects #CloudComputing #DSCareerPath

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