Introduction
I get asked a lot about how people can break into Data Science and what should be the first thing they learn. And my answer always is:
Start with learning basic python!
Once you mastered basic python concepts you can build on that and move on to learn how to do some simple data analysis with python.
This article will outline what you should learn in your 'basic python' journey and what are the resources to learn and practice.
Some of you will ask why python and not another programming language. The reason for this is to make your life easier. Python is a very popular language with rich Data Science libraries. Additionally, its syntax is simple and intuitive for beginners and there are endless resources to learn in it online.
So let's get started!
What python concepts you need to master?
Let me outline here what you should cover in your basic python journey.
1. What variables are and what are the basic variable types in python. You want to learn about floats, integers, strings, and booleans.
2. What are functions and how to write them in python?
3. What are collections in python? Learn about lists, sets, dictionaries, and tuples. Master them!
4. String is a special data type in python. Learn some basic string functions.
5. Learn 'for loop' syntax and be able to use it with lists and dictionaries.
6. Learn about conditional logic (if and else statements) and how to use it in python.
7. Learn about python objects. What are python objects, how to define them, create them, and how to use their functions and attributes?
8. Learn about imports in python and how to import some basic modules (e.g math, random, etc.)
9. Learn good styling practices and variable naming. Distinguish when to use snake case and camel case variable names. Know best practices as outlined in PEP 8.
10. Be able to run the python code you write in either PyCharm, jupyter notebook, or Google colab. Some of this option will require you to set up your local environment.
I think those are ten concepts that you need to master while learning basic python. Luckily there are plenty of resources to do so.
Resources to learn python
In order to master the concepts above you will probably need to do several basic python courses that cover the topics of interest. I recommend that you do 2-3 different ones.
This is because you want to get this basic really well! Additionally, each course will have different examples, will explain concepts in a different manner so you will reinforce your learning with each course you do.
Look for courses that are named "Introduction to python" as those are most likely to cover these basics concepts. You can use your favorite learning platforms such as Udemy, Plusright, EdeX, DataCamp, or any other. They all have good basic python courses.
If you still do not know which one to go with there is a list of a few:
1. Introduction to Python on DataCamp (affiliate link).
2. Learn Python - Full Course for beginners by freeCodeCamp. This is a free resource and comes in the form of youTube video.
3. Python course on Kaggle. This is another free resource that will briefly introduce the theory and allow you to practice.
Those three courses should get you started. If you want to learn more or looking for an alternative source you could also get Learning Python book (affiliate link). This book covers basic concepts and much more!
Summary
In this article, we have outlined steps to learn basic python and how to get some solid fundamentals in this programming language.
Spend around a week or two trying to learn these basics. Once you master them you will be ready to learn python from a more Data Science perspective.
Happy learning!