It was exactly 2 years ago when I decided to self-study data analytics and now I accepted a 6-digit offer.

This page summarizes the projects mentioned and recommended in the original post on /r/phcareers

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  • WorkOS - The modern identity platform for B2B SaaS
  • InfluxDB - Power Real-Time Data Analytics at Scale
  • SaaSHub - Software Alternatives and Reviews
  • PythonDataScienceHandbook

    Python Data Science Handbook: full text in Jupyter Notebooks

  • Python Data Science Handbook: This was my first data science book. This covers all basic data science libraries (e.g, Pandas, Numpy, Matplotlib, Sklearn). I was able to finish the book but I didn’t appreciate the machine learning part. Probably because machine learning was not part of my priorities at this time yet. Actually, you can skip this book. The next reference is even better.

  • ggplot2-book

    ggplot2: elegant graphics for data analysis

  • Ggplot2: Probably the best book to understand the structure of data visualization while also learning R. You’ll have a different perspective on data visualization after reading this book.

  • WorkOS

    The modern identity platform for B2B SaaS. The APIs are flexible and easy-to-use, supporting authentication, user identity, and complex enterprise features like SSO and SCIM provisioning.

    WorkOS logo
  • handson-ml2

    A series of Jupyter notebooks that walk you through the fundamentals of Machine Learning and Deep Learning in Python using Scikit-Learn, Keras and TensorFlow 2.

  • Hands-on machine learning (Python): Python reference for machine learning. Use their Github repo as a supplement because some codes in the book are outdated. Finish at least part 1: Fundamentals of machine learning.

NOTE: The number of mentions on this list indicates mentions on common posts plus user suggested alternatives. Hence, a higher number means a more popular project.

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