Do you need a Certification to become a Data Scientist? 5 Things you Should Consider

Overview

• Data science certifications are ubiquitous – should you get one? If yes, which certification should you choose?
• Here, we list down the different aspects of a data science certification you should consider before making your career choice

Introduction

Should I get a certification in data science? It’s the most mind-boggling question every aspiring data scientist inevitably faces.

And this is followed by more questions – Will it add more weightage to my resume or will it help get me employed? This, as I’m sure a lot of you reading will be aware, ultimately leads to more stress and confusion.

There are definitely some advantages that come along with a data science certification. It reflects your interest and passion in the field of data science but there’s a caveat – due to the boom of data science, there has been a massive uptake of these courses which makes them common or general.

So, what can you do in this situation?

To stand apart from the crowd, you will need to take up a course that provides you with industry exposure and high-quality projects. A certification is taken as a standard to measure great talent.

BlackBelt + is one such course that will provide with you each and everything you will need to become a highly valuable professional in the data science industry. It isn’t just about certification, it is about the quality and guidance that comes with it.

In this article, we will dissect the question into multiple components and help you get the answer to this all-consuming question!

Do I want to become a Data Scientist?

Certainly, Data Science has become a glamorous role over the years, and especially when HBR termed the role of the data scientist as the sexiest job of the 21st century. Today, the market size of data science stands at $38 billion and is expected to reach $140 billion by 2025! It is undeniably a high growth role.

The majority of enthusiasts aim to become a data scientist because of the glamour and high salary band but this is hardly the reality anymore. Many people apply for the same job role but don’t have the right skill set for the job resulting in a crunch of high expectations.

In the initial years of my career, I wanted to solve data-driven problems and so I aimed to become a data scientist. Little did I know that there are many other data-based roles available in the industry like a Business analyst, data engineer, and many more!

For example, if you come from the software engineering industry then data engineering may be the right role for you or if you want a job that has a high number of openings then you may want to go with Business analytics as a career choice.

The big question we must ask ourselves – Why do I want to become a data scientist? If you want to know about other data-based roles, you can check out this article:

• Business Analytics vs. Data Science – Which Path Should you Choose?
  

What are the different paths to become a data scientist?

There is no limitation when it comes to learning especially in the digital age where you have an ample amount of options open! You can browse through millions of freely available resources or even pay a hefty amount for a shining course. It all depends on how you want to do it. Let us discuss some different resources and their pros and cons.

• Reading Blogs – Blogs are widely and freely available resources on the internet. The greatest benefit of blogs is that there is a lot of variety in it and they are of course easy to grasp. You don’t need to go chapter-wise to reach a specific topic. The disadvantage is when you are a beginner, it becomes hard to connect the dots with the overall topic leading to gaps in knowledge. Analytics Vidhya has provides a range of articles on various topics. Make sure you go through the blog section. 🙂
• Learning through video tutorials – Can’t learn through reading? Videos tutorials are a great option for you. It is always better to see someone implement the concept, code, or project in front of you and then repeat after them. Video tutorials have the same disadvantage as mentioned in the above point.
• Free Courses – Yes, Free Courses are available for data science! These are usually short introductory courses which you can explore as a beginner. Many of them also provide certification as well. The advantage of such courses is that you get the comprehensive learning path for the intended concept. The disadvantage is that these are not specialized programs and only consist of generic knowledge. You can get access to a variety of free courses at Analytics Vidhya. (P.S Some of them even have free certification)
• Certification courses – Duh! Certification courses offer a great way to learn data science. You get a complete curriculum and reach the goal in a structured approach. These are usually taught by industry experts with high-quality content. There is no specific disadvantage of the program the only one being – you need to choose the certification course wisely. You can get access to Analytics Vidhya’s all the courses in the BlackBelt + program

Starting a data science career without proper guidance and planning can be confusing. We have compiled a clear-cut free roadmap guide to building a career in Data Science that is curated by expert curators at Analytics Vidhya – 

• • Download this free Comprehensive Data Science Roadmap to start your career

A Gist about Certification Programs in Data Science

Data Science certifications come in a variety of forms. Some require an internet connection and some require physical presence. Let us check out the different formats.

• MOOCs – or Massive Open Online Courses are probably the most known certification course in Data Science including Andrew Ng’s Machine Learning. These MOOCs may be self-paced and can be started anytime. Anyone can access these courses without any formal admission process. The only problem with these courses is that they can get very expensive if you want the certificate. The courses are usually conducted by universities such as Harvard, Stanford, and others.
• Classroom courses – These courses are in the same format as a school or university. You’ll join a batch of aspirants and taught via the pre-designed curriculum. You’ll be given assignments as homework and you can always raise your hand when in doubt. But you may find yourself in a difficult spot if you miss a few classes because these won’t be repeated just for you. Due to Covid-19, these courses are going online as live classes.

• Online courses – As the name suggests, these courses are online. These are pre-recorded videos set according to the curriculum. You can access the videos at any point in time in whichever order you want. But you won’t be able to clear your doubts in real-time here.
• Hybrid courses – Want the best of both worlds? Hybrid courses offer you part classroom course and part online course. You’ll get all the self-paced content at the start of the course. There will also be a limited number of classroom classes in which you can get your doubt cleared.

Honestly, Does it Matter?

Well, Yes and No!

In simple words, certifications definitely matter but not because of the certificate itself but because of the skills you have gained as part of the certification.

Over the decade, many data science certification courses have popped up leading to the generalization of these courses. Now anyone can just take up a certification and claim to be a data scientist but it doesn’t work like that when you apply for a job.

Recruiters receive tons of applications and they don’t have the time to skim through the certifications and then check its authenticity. Instead, they focus on the skillsets and projects completed.

In the end, it all boils down to the interview process. The interviewer will test everything that you have mentioned in your skillset. Therefore, if you choose to go ahead with a data science certification, make sure that you keep up with your classes and gain the right skills. Your certificate won’t get you the job, skills will.

How do I select a certification?

• Time – The certification course duration varies from a month to over a year. The question at the end is how much time can you devote. If you are a working professional, then an online course or online course of 3 months can suffice for basic machine learning. If you want to specialize then you may want to commit a longer duration of time.
• Skills taught – Python, R, or SQL, Excel? When selecting the course, the first decision is probably to select the language and other skills you want to have and then match it to the course curriculum.
• Mentors – A Data Science course without a mentor is riding the bicycle in the dark. You really don’t know where you are heading so make sure you get a one-on-one session with a mentor.
• Prerequisites – Make sure that you go through the prerequisites mentioned in the course. For any prerequisites, you can go through Analytics Vidhya’s free courses.
• Cost – At the end of the day, we need to match our expectations with our budget. Analytics Vidhya offers plenty of courses at the lowest prices. You can check them out.

If you are a beginner in Data Science, we have just the right course for you – the Blackbelt+ program. It comes with 14+ courses, 25+ projects, and a 1:1 mentor. The course doesn’t boast about its certification but the ability to transform you into an industry-ready data science professional. Your mentor will build a customized learning path specific to your career goals. you can learn Data science holistically with Blackbelt+.

End Notes

To conclude, taking the decision to undergo a certification course is difficult. You risk your time and money and hope to build a new career. It is a strong bet if you choose the right course and build your skillset.

The certification in itself has no value unless the skills complement it. Always look for a course that adds value to your skills and not just the certificate.

Hope this article clears your doubts. Let me know in the comments about your thoughts on certification courses.