On the back of massive digitisation, data science has emerged as a lucrative career option in a short time. Forward-looking companies worldwide are on the lookout for digital talents to make the best of their data to optimise business outcomes. However, being a developing field undergoing a tectonic shift, the demand-supply gap for IT talents is widening. To plug the gap, India’s leading institutions such as IITs and IIMs have introduced data science courses at the undergraduate and postgraduate levels. However, not everyone can pursue full-time courses due to budget and time constraints, lack of access, and many other limiting factors. This is where online certifications courses come into play.
Below, we look at the pros and cons of full time and part-time courses in data science to help you make an informed decision.
Sign up for your weekly dose of what's up in emerging technology.
Good domain knowledge: Most data science companies look for experienced candidates, and unless you don’t have good domain knowledge, your chances of landing a job in a top drawer company are slim, especially if you are a fresher.
“If a person already has a full-time statistics or similar degree and he/she just wants to learn a new topic, say NLP or computer vision, then a certification would be a good choice. On the other hand, if a person does not have a statistics or similar degree, then I would highly recommend pursuing full-time courses ( two years, three years or more). In a way, I view full-time courses akin to a foundation of a building. The online certificates are like floors built on top of the foundation, but they can’t be the foundation,” said Venkat Raman, co-founder of Aryma Labs.
Full-time courses will help you build your domain knowledge from the ground up. “I think full-time courses are better than part-time certifications. In a full-time course, one can get detailed knowledge of the topic. Moreover, the courses usually include student-faculty interactions, live projects, assignments, workshops, presentations etc which play a very important role in the students’ growth,” said Priyabrata Mishra, who is pursuing an integrated Masters in mathematics and computing from BIT.
Well-structured curriculum: Data science is a complex field, and a good grip on statistics, programming languages, as well as business acumen will take you a long way. Building skills in multiple areas need time and effort (read discipline). Full-time courses have a well-thought-out curriculum curated by subject matter experts keeping the students’ learning curve in mind.
Active learning: In-person full-time courses in data science allow students to interact with the faculty and clear doubts in real-time. Brainstorming with your peers to solve real-world problems and tinkering with data are the best ways to get the data science concepts down cold.
Employer preference: Generally, employers prefer students who have pursued full-time courses. However, Aryma Labs’ Raman said there are always exceptions to the rule. “Someone might not have a full-time statistics degree, but they might have learnt things on the job or have done reading on their own. In such cases, we do have to give them an opportunity. As a data scientist recruiter myself, I am open to such candidates,” he added.
Time-consuming: More often than not, working professionals looking to upskill may not always have the luxury to put their careers on hold to go for a full-time two year or three-year course. In such cases, online courses seem to be the best option.
Expensive: Full-time courses at premier institutes are costly, mainly because of the brand name, the top-tier faculty ( professors and industry partners) etc. Meanwhile, online courses are often much cheaper and not geographically limited.
Self-paced: Online courses offer the flexibility of learning at your own pace and are particularly helpful for working professionals. “For a person who is working, he/she may have time constraints to join a full-time course. In this case they can always opt for a certification course to learn new things and enhance their skills,” said Mishra.
Remote: Online courses can be accessed from anywhere in the world. Institutions that offer full-time courses in data science are often based out of tier-1 cities in India. With online courses, students from anywhere in India can upskill themselves or change their career trajectory at any time. All you need is a laptop and an internet connection.
Shorter duration: Typically, the duration of online courses in data science falls in the range of six months to a year. For example, suppose a business analyst with knowledge of basic statistical concepts and programming languages wants to upgrade to a predictive analytics role. In that case, a relevant part-time certification course can facilitate it.
Superficial: Data science is a vast field, and online certification courses just scratch the surface because of shorter durations.
Passive learning: Online courses are a mix of pre-recorded videos and a few live sessions to interact with faculty. The structure of such courses are not conducive to real-time doubt clearance, and a lack of peer interaction can be disincentivising.
Raman has a few recommendations for candidates going for online certifications.
- Find out whether the certificate has value in the marketplace.
- Before enrolling, get the curriculum vetted by good data scientists.
- Sound out people who have already done the course: “Did the certification help you in landing the job”, “Did the certification help in broadening the knowledge” and “Did the certification help you in solving the business problem” are some of the relevant questions to ask..