The amount of money data science and data analytics institutes are pouring into advertisements is astonishing. The world has accepted data science to be the best and the safest field of study and the greatest discipline to start a career in. Aspirants are crowding the digital stairs of data science institutes. It becomes hard to keep track of the collaborations happening between professional training institutes and universities. There is a rush, a hype to start a career in data science, that often makes you land on the wrong foot. So, here are five things that you need to look into before enrolling for a course.

1.   Quality of faculty members

Please do not fall for people with past jobs at such and such universities. 67% of data scientists admit that mentors and teachers have played a crucial role in their formation. While it is next to impossible that you would find a perfect match for yourself in your instructor, it is important to look for minimal compatibility. An instructor that does not strike the right chord can turn the experience of learning a difficult discipline like data science into an absolute disaster.

2.   Hidden costs

It is important that you read through the fine print while enrolling for a course. I am not saying that institutes are waiting to rob you of your money, but then again some of them are. Understand the fee structure very well, account for every single expenditure. Education is a psychological process and it helps if there is trust between you and your institution.

3.   Reviews, and fake reviews

Make a habit of tracing a review back to the reviewer. I am not asking you to investigate every single review for an institute. There are always a handful of reviews that really matter, the ones that really pull in towards or push away from a particular course. Investigate those reviews. For instance if you look for AnalytixLabs reviews, you will be able to trace most of the reviews back to the LinkedIn profiles of the people who posted them. 

The internet is drowning in fake reviews and it is always better to double check lest you invest based on one.

4.   Mentorship and Counselling

If you are trying to build a career in data science, you cannot ignore these foundational aspects. Data science is a multidisciplinary field containing diverse opportunities for people from different backgrounds, hence it is important that you start in the right direction. It would really help your understanding of the discipline if you receive the mentorship of a senior data science professional.

5.   Placement support

An institute that does not stay accountable for the successful placement of the students graduating from there hardly incurs trust and loyalty. While it is important to have faith in your ability to find a job for yourself after graduating, it is always nice to have someone look out for you, is it not?

Set your expectation from an institute based on these five points and you will definitely end up at the right place.

By Adam Smith

Hi, I'm an SEO expert and Outreach blogger.

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