Getting Started with Data Science

Data science has become one of the most emerging career fields in the world and the demand for a data scientist is increasing day by day. Simply, data science means using data to answer a question. One of the reasons for the rise of the field of data science is the vast amount of data available, thanks to digitalization.

The interesting fact is that data science is a soup of many fields. It includes many disciplines. Initially, it started with Mathematics and Statistics, but now it has moved on to the field of Machine Learning too.

If you are interested in data science and hope to follow your future in this focus area, it is very important to get a basic knowledge of the basic concepts such as Statistics, Mathematics and Linear Algebra. Before you start to learn about data science, I highly recommend you to get an understanding about the aforementioned concepts.

Then try to acquire at least the fundamental knowledge in programming languages. There are many languages which data scientists use such as Python, R, Spark, SAS etc. You don’t need to know every programming language but practice at least one language
Afterwards, you can move forward to learn about Machine learning and Deep Learning concepts. That knowledge comes in handy when you solve real-world problems using data science. There are many online courses that you can learn about Machine Learning and Deep Learning.

Studying theory is not enough. You must apply those theories in real-world problems. If you want to practice and test your data science ability, you can try out the Kaggle platform which is dedicated to data science. It also consists of a series of micro-courses to learn about data science.

Following links will helpful for you to learn about data science step by step.

Just a suggestion: The most important thing to remember is, no matter how well you know the theory behind data science, it’s your analytical mindset that brings you closer and closer to the solution.
There are many competitions organized by our university and many other universities in data science. I highly encourage those who are interested to participate. Good luck!