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SathiMondal
New Member

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How to learn data science

1 ACCEPTED SOLUTION
sannavajjala
Resolver II
Resolver II

Welcome to the community! If you're new to Data Science, I'd recommend starting with the fundamentals in this order:

  1. Learn Python programming and basic SQL.
  2. Build a foundation in statistics and probability.
  3. Practice data analysis using Pandas and NumPy.
  4. Learn data visualization with Power BI, Matplotlib, or Seaborn.
  5. Explore machine learning concepts using scikit-learn.
  6. Work on small real-world projects and publish them on GitHub to build a portfolio.

The key is to spend more time practicing than just watching tutorials. Start with simple datasets, analyze them, create visualizations, and gradually move into predictive models. Consistency is more important than speed, working on projects regularly will help you learn much faster than focusing only on theory.

 

Best of luck on your Data Science journey! 🚀

View solution in original post

3 REPLIES 3
v-kathullac
Community Support
Community Support

Thanks @sannavajjala  for Addressing the issue.

 

Hi @SathiMondal  ,
we would like to follow up to see if the solution provided by the super user resolved your issue. Please let us know if you need any further assistance.

 

Thanks,

Chaithanya.

v-kathullac
Community Support
Community Support

Thanks @sannavajjala  for Addressing the issue.

 

Hi @SathiMondal  ,
we would like to follow up to see if the solution provided by the super user resolved your issue. Please let us know if you need any further assistance.

 

Thanks,

Chaithanya.

sannavajjala
Resolver II
Resolver II

Welcome to the community! If you're new to Data Science, I'd recommend starting with the fundamentals in this order:

  1. Learn Python programming and basic SQL.
  2. Build a foundation in statistics and probability.
  3. Practice data analysis using Pandas and NumPy.
  4. Learn data visualization with Power BI, Matplotlib, or Seaborn.
  5. Explore machine learning concepts using scikit-learn.
  6. Work on small real-world projects and publish them on GitHub to build a portfolio.

The key is to spend more time practicing than just watching tutorials. Start with simple datasets, analyze them, create visualizations, and gradually move into predictive models. Consistency is more important than speed, working on projects regularly will help you learn much faster than focusing only on theory.

 

Best of luck on your Data Science journey! 🚀

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