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How Not To Turn Your Data Science Learning Into A Panic Attack

How Not To Turn Your Data Science Learning Into A Panic Attack

Harshajit Sarmah

The use of data is on a continuous rise, disrupting several industries. Of late, every company has understood how important data is. It is not just companies that are witnessing the rise, aspiring individuals and data scientists across the world have also started to feel that the domain today is not just about extracting insights, it is much more than that. However, this rise in the significance of data science is also making many data scientist restless.

Data Science is a vast field and to be a data scientist, it takes a tremendous amount of knowledge. And today the requirements for a data scientist is increasing — aspirants and data scientists are becoming anxious and restless and are trying out every possible way to expand their knowledge. And, in order to help data science aspirants and data scientist to deal with this kind of situation, in this article, we are going to discuss some of the most effective ways.

Do Not Overwhelm Yourself Trying To Learn Everything At Once

A data scientist would definitely agree that even though data science is a fast-paced and a vast domain, it is exciting as well at the same time. Be it the paycheck or the reputation or the tasks, the job profile never fails to overwhelm the candidate. One of the overwhelming instances is when someone realizes that there are many different concepts and things you have to work with. You even might feel that in order to be competent or to be the best you, you need to learn and master all of them. And you end up spending a lot of time learning everything at once. However, that shouldn’t be a case.


The field of data science is all about a stable mind that can solve some of the complex problems with ease, and if s/he tries to do multiple things at once, it going to get hard. Therefore, make sure you have a list of concepts that you want to learn, and take one concept at a time. Learning things in a uniform way is always considered to be a good practice.

Have A Set Of Goals

Being a data scientist, you must be disciplined when it comes to getting the job done. And in order to be disciplined and getting every work done on time without becoming restless, you have to have a roadmap. So, how would you do that? Start by dividing your work for the day — have daily goals. And one by one start accomplishing every goal. Goals setting is one of those traits that every data scientist should possess. This is nothing less than art, and once you master this, the chances of failing and becoming restless reduce significantly.

Have A Strong Hand On Mathematics

It won’t be wrong if you call mathematics the backbone of data science. Without mathematical knowledge, your data science journey will most probably be meaningless.

There is an instance when a data scientist faces challenges in identifying patterns and assist in creating algorithms and it might make a data professional little worried and restless. And the ultimate solution to this is mathematics because its concepts are very important in the field of data science — the understanding of various notions of statistics and probability theory are key for the implementation of many algorithms in data science. 

So if you think, your knowledge in mathematics is lagging a bit behind, make sure you brush it up and have an upper hand in the subject.

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Have Significant Knowledge Of Programming

You might have strong mathematical skills, have a degree, or even have a strong problem-solving skill, but those are not enough to be a data scientist that stands out. Besides all these skills, there is a requirement for programming expertise. And every Data Scientist must be able to make the right decision about the type of programming language required for the job.

Data Science domain is a combination of several fields including Computer Science — there are instances when specific programming languages are needed to get a job done. And when you are a data scientist you can’t expect a software developer to the programming for you. Therefore, it’s advised to have an upper hand on all the significant data-centric programming languages to carry out algorithms suited for the specifics of Data Science.

Don’t Hesitate To Seek Help From Co-Workers When Needed

It is no surprise that people tend to hesitate to seek help from others when they work in a significantly high position. They tend to build a notion that if they have landed the job like a data scientist, then their knowledge and concepts are correct all the time. However, that’s not completely true.

Even a well-read and knowledgeable person makes a mistake and might not know a few things. So, do not hesitate to reach out to your fellow data scientists for help.

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