The single most asked question from Data Science enthusiasts around the world is whether they should get a Data Science Certification or not.
That does not stop there, as it is followed by several other questions: Will it add weight to my resume? Will it help me get employed? This, as I am sure a lot of you reading will be aware, ultimately leads to more stress and confusion.
Generally, there are some advantages for attending, passing, and showing off your certifications in your resume. It reflects your passion in transitioning into the wonderful world of Data. However, due to the boom of Data Science, there has been a massive uptake of these courses which makes them common or general.
So, what is the solution to your confusion?
“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.”
Before taking up certification, one needs to think carefully about one and only one 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 major chunk of these enthusiasts is getting attracted to the field of Data Science because of the glamour and expected high salaries that they think will come with it but this is far from reality. Many people apply for the jobs, but they hardly have any skills that would comply with the job descriptions needed for a particular Data related job in the organization.
Little do people know that there are many data-related roles available which are as attractive as being a Data Scientist within the organization. For e.g.: Business Analyst, Data Engineer, and many more!
It is imperative to know your right skills for the data-related jobs and apply for only those roles which are nearest to your skills and educational background. 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.
If you want to know more about whether to choose Data Science or Business Analytics as a career, please consider reading my other article on this website here.
What are the different paths of becoming a Data Scientist?
There is no limitation of learning materials currently when it comes to becoming a Data Scientist or choosing any career for that matter. You can browse through thousands of videos, practice materials and even useful articles around the web to learn anything which is beneficial to your quest for this career transition.
- Reading Blogs: Blogs are widely and freely available on the web. The greatest benefit one can extract from these blogs is that that are content specific, and it gives you information on a pinpoint fashion. However, they are generally not recommended for the novice / basic Data Science enthusiast as they are hard to follow and make use of it.
- Video Tutorials: They are a personal favorite of mine as they are another way of describing and making you understand theoretical concepts of Data Science in a much better way. However, they are also not recommended for the basic or new enthusiasts for the reasons already described above.
- Free Courses & Certifications: They are another feasible way for learning basic theories of Data Science. 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.
- Certifications: 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.
Different flavors of Data Science Certification Programs
Data Science certification programs are available in variety of forms. Either they prefer physical classroom sessions, or some require internet connection. Let us check out some of them!
- Classroom Courses: Prior to the Covid19 pandemic, these physical classroom sessions were preferred by most of the enthusiasts as it has the same format of any school or university that we attended in the past. You must pass the grading through assignments, quizzes and annual exams. Nowadays, the pandemic era has made these classes to be held via numerous tools like Xoom and Skype.
- MOOC: Massive Open Online Courses are probably the most known certification course in Data Science including Andrew Ng’s Machine Learning. These MOOCs are self-paced and are easier to attend as you do not have to be bound to be available at any specific time, just like physical classroom sessions we discuss earlier. The only disadvantage is that they get expensive if you opt to receive the certificate.
- Online Courses: As the name suggests, the classes of these online classes are prerecorded at an earlier date. You can access and study through these videos at any time. On the other hand, most of the videos I have come across becomes outdated quickly as Data Science is an evolving field and it witnesses advancements almost every day.
- Hybrid Courses: Hybrid courses offer you part classroom course and part online course. You will 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.
How to select a feasible Certification Course?
- Time: The certification course duration varies from a month to over a year. If you are a working professional, then an online course or online course of 3 months can suffice for basic machine learning.
- Skills being taught: It is essential for any student to go through the curriculum and select the best course which aligns with the career plans for the individual.
- Mentors: Any Data Science course should have one to one session with the mentors as it is compulsory for the students to have someone who holds their hands and clear any obstacles in their way for becoming a better Data Science professional.
- Prerequisites: Please make sure that you fulfill any prerequisites that the course demands to be addressed. For example, it is advised for going through the basic level of any tool before jumping directly on the advanced level of that same tool.
- Cost: At the end of the day, one should research well before transferring course fee of the course for making sure that it will give the best value of your hard-earned money.
Conclusion:
To conclude, the decision for to undergo a certification course is difficult.
The certification has no value unless the skills complement it. Always look for a course that adds value to your skills and not just the certificate. It is important for you to choose a course which gives you a chance to make use of your skills on a practical basis by developing academic or personal projects.
One cannot gain expertise in any tool or technique, unless you get your hands dirty by playing with it and creating some rich data models, visualizations, or anything to show your contributions to the world we live in.
