Introduction to Data Science and What to Learn

Data science is now a days most talked about buzzword. As said by Harvard Business Review “Data Scientist is the Sexiest Job of 21st Century”, its becoming popular and useful everyday. Even when no one is working in office Data Science add to companies efficiency by adding new customer or get more work done.

We have learned/ remember a lot of Math and statistics in our childhood and always hated it. Reason being “We are never gonna use it”. But you must be happy to know that Data Scientists use it on daily basis. Even some of the most advanced mathematical algorithms and advanced statistics.

As asked by many people, I have summarized list of topics we must study to be a Data Scientist.  These topics are fundamental of learning data science and are not tools.

1. Understand Data Science
2. Math (eg. Probability, Permutation, Combination etc.)
3. Statistics (e.g. Histogram, Skewness etc.)
4. Python / R  – programming language for implementation
5. Advanced Statistics (e.g. Regression, Cluster etc.)
6. Machine Learning/ Deep Learning
7. Position of Data Scientist

Data science is needed to check your data and predict the future based on it. It helps companies to build machine learning / deep learning models to automate pattern recognition and provide better direction for company.

For example giving out same discounts to all customers will be utterly useless in most of the cases but discount coupon based on a customer’s buying habit, purchase power (or any other variable) will be better for companies business.

So keep on the pace and join us (by FOLLOW button) to be in this journey to learn Data Science.