Dive into Data Science -- Newbie!

Almost every one of us was introduced to this field of automation, with jargons like Artificial Intelligence(AI), Machine Learning (ML), Deep Learning (DL), Data Science/Analytics, etc., which seemed like magic at first sight. The backbone of the course'Data Science' and those magical terms rests on these below topics: Note: The coursework I did in Machine Learning & Deep Learning was based on python, but there are alternatives like R, MATLAB, etc. but python is the most popular choice. Additionally, problem-solving or standard coding for questions is something students are familiar with throughout academia, but scripting the code in a refined, readable manner is very important when you are writing code for projects especially the ones in production. It's because when you are collaborating on a project, your team members need to be comfortable with your code at first sight. This helps them to improve your code and highly increases the efficiency of your project work.