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My Data Engineering Portfolio

This repository is all about what I'm learning from the internet (courses, tutorials, and blog posts) about Data Engineering (in the future it will be about the MLOps field, which takes Machine Learning, DevOps, and Data Engineering, all combined).

But why Data Engineering? Because loving DevOps culture and Machine Learning field is not enough for me, a simple Software Engineer, and because I do like almost everything related to Data.

Important note

In this portfolio/side project/study repository I mainly will use Google Colab which covers everything that you probably will have to deal with to run into your local environment, like:

  • install Python (version =>3.6);
  • install PIP package manager;
  • install all the dependencies that are required to run properly in your local machine;
  • maybe install Anaconda (which it comes with several and useful tools for Data Science, Data Analysis, Machine Learning, etc);
  • deal with some annoying setups;
  • other things that I miss to put in here;

So, you have two choices: or you just have to import those .ipynb from Jupyter Notebooks into your local environment, or use Google Colab and import these files and run it in the "Cloud".

Resources

Books

Courses

Roadmap for Data Engineering