Sri Athithya Kruth’s Answer
Data Science is a very diverse and interesting field. There are many sub domains in data science including:
- Machine Learning
- Deep Learning
- Database Management Systems (SQL, noSQL based ones)
- Data cleaning, wrangling etc.
You can do this through numerous courses available online.
For Machine learning, you can try Andrew Ng's famous Machine Learning course on Coursera. This course is famous as it covers Machine Learning in decent depth, and teaches you the math behind the algorithms, which is very important.
There are many good courses for Data Science on sites like Datacamp, Udacity etc. I suggest going through the curriculum for some of these, and trying to learn some of the content by yourself. If it interests you, you can sign up for one of these and continue learning.
Signing up for Kaggle is also a good idea. Kaggle has free courses for all of the topics you would need to know to compete in the contests. Going through these courses would help you get a good start on Kaggle as these are designed for people interested in Kaggle competitions.
Sri Athithya Kruth recommends the following next steps:
- Try going through Andrew Ng's free Machine learning course on Coursera.
- Sign up for Kaggle, and start taking some of their free courses to start up on Kaggle contests.
- Once you think you have a good grasp of the basic concepts on Kaggle, try the Titanic Survival Problem. There are several Kernels (these are solutions to the problem posted by people on the site) you can refer to in case you would like to look at possible solutions.