Do you hold the desire of becoming a professional in the data science field? Then don’t you think first you need to learn all the skills associated with it?
The market is in search of real talent. And thus you have to be equipped with all the skills that are needed for a data scientist. And what exactly do you need for it? Training. Proper training in data scientist course can help you learn all the skills and know profoundly and accelerate your career.
Today, I will discuss 5 skills that are usually required for becoming a successful data scientist. But before venturing into that, let me tell you who actually a data scientist is.
Who is a data scientist?
Shlomo Argamon, the professor of computer science and director of the Linguistic Cognition Laboratory at the Illinois Institute of Technology, once stated – “Data Scientist = Statistician + programmer + coach + storyteller + artist”.
Monica Rogati, an independent technical data science executive, said, “A data scientist is half hacker and half analyst, and he uses data to build and derive insights”.
The main job of a data scientist is to collect data and create a dataset that can easily be analyzed. After the data set is being obtained, this can be analyzed for the current trends or forecast the future trends.
Based on this, data scientists develop data-driven products and communicate the findings to other data scientists and the reports, blogs and visualizations.
Now, let’s have a look what skills you need to learn to become a data scientist.
R, Python and SAS training classes are needed for learning the skills properly. These are the major programming languages, having individual advantages. Just select one and start learning. Or join data science course at any reputed training center that covers all.
For more than centuries, SQL databases have been a major data storage mechanism. A large amount of data, saved by businesses, is in these SQL databases. If you want to grow in data science field, then try to be familiar with some concepts, such as –
There is a need of being familiar with the fundamentals of statistics, like distributions, statistical tests, p-value, experimental design etc.
Statistics is really important in organizations where stakeholders will depend on your assistance to make the decisions and assess experiments.
A maximum amount of time of a data scientists is spent converting data into usable form. If it cannot be done properly, the entire data analyzation will be messy, unstructured and tough to work with. Therefore, data munging is an important skill.
Organizations that make the data-driven decisions depend on the abilities of a data scientist to visualize and emit a story by analyzing available data, since one requires to communicate data-driven insights to both the non-technical and the technical people in the company.
Therefore, you should be a great story teller, if you want to be a good data scientist. There are some good visualization packages in R and Python. Just join a course today.
Being a data scientist, you need to have profound understanding of the industry you are working in and the business issues your company tries to solve.
This way, you can hold the position of understanding a business challenge and give a significant solution for the business problems, with data-driven insights.
