Charming the Python

Python is the language of choice for most AI programmers, but that’s just one of the places it can be used. It is a very versatile language that is easy to learn if you are determined and organized enough to pursue it.

The Base
This article assumes you have some base in logical thinking or thinking like a programmer. If you don’t have this base, no problem: you can learn it pretty quickly. A little known fact about most programmers is that they don’t know everything about a particular language. Instead programmers are great at solving problems by breaking them down into bite-sized bits and taking care of each of them in a logical sequence. A great way to practice this is to think about daily problems that you solve, they don’t need to be computer related. For example, think about making a cup of tea, or applying butter and jam to your bread. Break it down into very precise steps. Write it down and then try following these steps or ask someone to follow the steps exactly as mentioned to test it.

If you want to apply butter to a slice of bread, you would have to mention things like taking a slice of bread out of the packet, using a butter knife, applying an approximately 1 mm layer of butter on your bread etc. Being specific is what makes a good programmer. Read through this informative article by The Odin Project titled Problem Solving: Foundations Course, and watch this video series, Think Like a Coder (by TED-Ed) on Youtube.

Learning Python
With AI, it is widely believed that programmers will lose jobs to artificial intelligence. However, this may not be the case for a long time to come. Asking AI to write a program now takes a lot of effort if you don’t have the skill to recognize when the AI has written a wrong program, or a program that doesn’t do what you want it to. Instead, we can use AI to accelerate your learning and error handling. 

The way Python is written is simplistic when compared to other programming languages and you can learn this rather quickly with some online tutorials. I will list some at the end of this section. The thing you need to take care of is indents. Indents in Python are very important and a wrong indent can prevent your program from working. So, it is advisable to write your programs with an Integrated development environment (IDE). You have a few to choose from, Visual Studio Code is very popular and so is Pycharm. You can also try Cursor AI, which integrates ChatGPT with Visual Studio.

To get started from scratch ,watch this video: Python Tutorial for Beginners by TechWorld With Nana (YouTube). It will get you started and teach you how to write your first few programs in under six hours. In reality it should take about two days. You can explore Python a bit more with tutorials at www.learnpython.org. 

Try and error correct on your own, however, if you do get stuck and can’t see where you are going wrong. Feel free to paste your code in ChatGPT and ask it to find the error and explain why it occurred and how to fix it. This will help you improve your error detection while learning.

Github
Another thing you need to know is how to use Github. This is important because it is a place to showcase your skills and, at the same time, Github or Gitlabs are used by many companies as part of their workflow. Git stores your program and changes you have made over time. It is a great way to showcase your project. For starters, you will need to get a Github account. Watch this video Git and GitHub for Beginners (freeCodeCamp.org, YouTube) to learn the basics of Git and Github. You can explore Github further with this link: https://docs.github.com/en/get-started.

Practicing with Projects
A big part of getting your skills up to scratch is practicing. There are plenty of exercises to learn and practice your basic Python skills. This is also where you can specialize and learn to do things like data analysis or machine learning or even automation. There are mock projects for all these skills available as well. For basic projects check out pythongeeks.org, if you are interesting in machine learning and data science check out www.kaggle.com which hosts beginner competitions and practical courses that will get you started. 

Securing a job
Securing a job as a program requires a bit of work. If you have managed to follow the other steps, you should already have a robust Github profile. This will act as a portfolio to find an entry level position. The position might not pay as much but it will be a foot in the door and a place where you can truly hone your skills by working on real world problems in a real office environment. Securing a job can get easier if you stack some more skills with your ability to program, usually some level of SQL expertise or web development or even experience in Linux can help.

Testing your skills
Depending on what stream you are concentrating on you can find various challenges online to test your skills and compete against other beginners.

You can do this on the following websites:
www.kaggle.com
www.topcoder.com
projecteuler.net
www.hackerrank.com
www.codechef.com
exercism.org
www.codewars.com
leetcode.com
www.codingame.com

 

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