What should I learn? – Concepts or coding

This is the question that many of you might be having. Many online learning platforms are promoting coding with R or Python and become machine learning expert.

So, what happens, if we take up these courses and learn coding but we don’t understand the background. So, in the real world scenario you will be only able to do, what your supervisor tells you to do.

For example, you may learn how to use a clustering technique in Python, but you will not know when to use clustering and which technique will work best in a given scenario.

To solve a real world problem, we need to know all the different techniques and which one can be applied. In our models, we look for better accuracy in predicting. To do this, we may end up using multiple techniques and concepts. All this needs to be logical based on statistical or mathematical concepts.

Initially, you may be doing only coding work but if you want to grow then concepts are very important and my suggestion is to start with building sound base with concepts.

2nd step should be learning Python for coding work. Once you master these then Deep Learning comes into picture.

If you are new to this field then I would try to explain you which courses you can take up and how to move forward, I am keeping it simple with few top rated courses only.

Also keeping cost in mind, I will recommend the most cost effective way to gain knowledge. I am not recommending you to start searching YouTube and get lost in plethora of videos, some are good but others are just average and you will not understand where to start and how do they link to each other.

Overall we can divide the complete learning into three broad areas as shown below in the graphic.