Learning resources
Python

1. Books
   • Mark Lutz. Learning Python – Python developer’s bible. It can be read
     at all stages of learning Python
   • Python Tricks: The Book – an awesome tiny book about different Python features
   • Grokking Algorithms – a simple book about algorithms, but examples in Python
   • Two Scoops of Django 3.х: Best Practices for the Django Web Framework – relevant practices in Django.
   • Django Book – e-book with examples
2. Courses
   1. Course on the basics of Python programming from the University of Michigan on
      Coursera
   2. Another course from the University of Michigan, also on Coursera
   3. Python in depth on Udemy
   4. OOP with Python – continuation of the previous course with a deep dive into the
      topic of OOP in Python
   5. An Introduction to Interactive Programming in Python – a course from MIT
   6. An interesting channel on Python, with lots of different topics and
      complexity of materials (don’t forget to give it thumbs up)Great to read
      • Lots of interesting stuff
      • Django: The Web framework for perfectionists with deadlines – get
        acquainted with the largest Python framework

1. Books
   • C.J. Date. An Introduction to Database Systems – theory and practice on
     databases. Do not be scared by the number of pages in the book
   • MySQL. Notes for Professionals book, which covers almost all major operations
   • PostgreSQL. Notes for Professionals book on studying relational
     databases using Postgres examples
2. Online Tutorial
   • SQL Tutorial

• Pro Git – and nothing more is needed, just practice
• Linux basics from the Gentoo founder, 4 parts

It stands for one of the key tools for processing and analyzing big data.

1. Official documentation
   There is nothing better than official documentation where you can:
   • Get an idea of Spark’s main components;
   • Learn what distributed computing is, and what data structures Spark uses;
   • Understand the meaning of such definitions as Lazy Evaluation, Fault Tolerance, Catalyst Optimizer, UDF, Transformations, Actions, Wide & Narrow Operations, Partitions, Shuffle, Broadcast, and much more:
     • https://spark.apache.org/
     • https://spark.apache.org/docs/latest/quick-start.html
     • https://spark.apache.org/docs/latest/api/python/
2. Books
   • Big Data Fundamentals: Concepts, Drivers & Techniques – this book
     gives a great jump to understanding such an interesting topic as Big
     Data
   • Learning Spark, 2nd Edition – Apache Spark has become the de facto
     standard for processing and analyzing Big Data
   • High Performance Spark – this book tells you how to use Spark effectively
   • Hadoop: The Definitive Guide – this book will present the Hadoop
     ecosystem as the main technology for storing and processing Big Data
3. Courses and videos
   • Youtube channel of Databricks – the main contributor to Apache Spark
   • PySpark Tutorial for Beginners – PySpark course from Edureka
4. Great to read
   • Big Data Zone
   • Favorites on Medium
   • Data Engineering podcast