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Additional learning materials to supplement Dataquest Courses

I wanted to crowdsource on what fellow students or experts find to be good supplementary learning resources on top of your Dataquest journey. It could be in the form of ebooks, textbooks, youtube videos, etc.

Do share your recommendations and how it helped you enrich your data science journey!

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  1. Blogs:
  2. Books:
  3. Youtube:
    • There are so many…, youtube just recommend videos for me.
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1. Blogs:

2. Documentation and Common Questions:

3. Supplementary Courses on AI/ML

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In addition to what others have suggested. Best way to learn data science is to practice and what’s better way than to compete in a hackathon.

I understand kaggle seems daunting for many students (including me :stuck_out_tongue: ) , below are some great beginner friendly hackathon websites.

  1. https://www.machinehack.com/

  2. https://datahack.analyticsvidhya.com/contest/all/

  3. Hackerearth

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I’m currently using these two books:

  1. Think Python 2e
  2. Think Stats 2

Both are designed for beginners, but the exercises are still challenging :joy:

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Yeah. I too refer this websites for any assistance. :+1:t5:

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Thanks man. This is very thoughtful of you.

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Here are some other related conversations from our Community that you may find helpful:

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Blogs from https://realpython.com/ is also very good.

Hi all,

Just wanted to share and collate some resources that we can use to complement and/or extend DQ’s curriculum as we aim to become better data scientists in 2021 and beyond!

  1. Following Madison Hunter & Daniel Bourke’s curriculum (there are overlaps)
  2. Columbia University: Applied Machine Learning Website and Youtube Lectures
  3. NYU Deep Learning Website and Youtube

Please share anymore of your awesome free discoveries! Happy New Year and Keep Learning! :tada:

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