Data Science Path to follow

So far you have understood what all fields are involved in Data Science, now let us look at the path which we can follow to learn Data Science.
There are fields which are independent to each other and hence they can be learnt parallely, however there are some fields which are dependent on others.

Take a look at the image below, you can plan to learn Data Science in three steps.

Step 1:

This is the first step where you will learn about

• Statistics: Statistical techniques which help you to analyze and interpret your problem statements
• Handling Data: this will teach you on how to work with data sets
• Python / R: you need to learn some programming language either Python or R so that you can work with data sets and make decisions through Data Science techniques.
  

All these 3 fields can be started independently. But before moving to step 2, it is recommended to finish step 1 with intermediate knowledge of all 3 mentioned fields.

Step 2:

Once you have finished step 1, you are now equipped with Statistical power and now you know how to use programming language to work with data. Now this is the time to train your model to predict business problems.

• Machine Learning: You need to learn Supervised as well as Unsupervised machine learning techniques
• Natural Language Processing (NLP): Here you will understand how to interact with textual data and how to predict/interpret through textual information
• SQL: this is where you will upgrade your skills with Database
  
  

Step 3:

This is a bit of a complicated section where it is very much required that you have proper knowledge of step 1 and step 2

• Neural Networks and Artificial Intelligence (AI): this is where things start becoming black box and you solve real time complex problems which can’t be solved easily/effectively through traditional Machine Learning models.