Five steps to learn "Data Science"

                              

One of the most common questions asked is, how to be a decent Data Scientist. An answer surely can be found on the web. Well, I have tried to jot down a few points, and it may be helpful for you to understand what are the steps really needed to be a data scientist. I have summarized them into 5 points.

1. Motivation: One should have the motivation to learn Data Science, Data Mining, Machine Learning, and Descriptive Statistics. One must have a thinking habit and a clear mind to visualize the data. For that, self-motivation is highly recommended.

2. Language: Start learning R programming and be expert in data analysis with R. Someone may be interested in Python; so my suggestion is, if you know python already, then fine, keep continuing with that, but if you are a fresh aspirant in Data Science, I would recommend you to learn R programming as it is the best with regards to the application of Data Science. Plenty of packages are available online free and the R community is vast; hence you can get a quick answer to any of your doubts.

3. Knowing Data Mining is a must. I would recommend you to read the book, namely Data Mining: Concepts and Techniques, 2nd Ed, written by Jiawei Han and Micheline Kamber. You even further can read Data Mining by Tan, Steinbach, and Kumar.

4. Take some free online courses (related to data analysis, machine learning ) from Data Camp, Udemy, and Course era. Participate in Kaggle’s data science competitions. They have free training data sets. Play with it and learn to build a new, efficient learning algorithm for predictions.

5. Lastly, you need to interact a lot with the data scientists.

~AISavvy,2019