My Experience Starting With Python For Data Science.

Well, in a data science journey, the first thing is to learn python and if you are trying to learn python you have to start with usual variables, loops, data types, dictionaries, sets, tuples, and functions for starters then you can move on to deeper topics like classes, libraries, inheritance and many others.

To me, python has been quite easy to learn the basics since it has a simple syntax similar to English and with fewer lines of code. jupyter notebook easily interprets the code and gives you an output as soon as possible. I really enjoyed coding using jupyter notebook. I wish all other programming languages had one of those.

Well, obviously if you want to learn any programming language you have to practice and give it time. I for one block some time out of my day to sit down, open my jupyter notebook and do some of the challenges to help me learn more about the Python language.

If you are going to program then you are going to spend 70percent of the time on google especially if you are a beginner, this you cant avoid. The amazing thing is there are many resources on learning python programming such as youtube, stack overflow, google which you can help you whenever you are blocked.

You will discover somethings for yourself as well during your practice and this is exciting for example for me I realised that python relies a lot on indentation, using whitespace, to define scope; such as the scope of loops, functions and classes. Other programming languages often use curly-brackets for this purpose and also dropping the semi-colon hahaha that one disturbed me a lot.