Data science is rapidly gaining popularity, with big data and generative AI tools like ChatGPT transforming the field. The market size for data science platforms is projected to grow from $48 billion in 2022 to $484 billion by 2029. As a result, data scientists are highly sought-after job roles worldwide, including India, where around 45,000 data science and AI positions remain vacant. Average salary levels remain higher than other technology industry roles.
Therefore, students are joining data science courses in droves to cash in the emerging demand. However, the dilemma appears in the minds of every student concerning the best way to obtain the skills he or she needs to enter the data science domain. Whether to enroll for a degree or diploma education from a recognised college or university, which is the conventional way of entering into a new job, or opt for a bootcamp that imparts a skill-based education in the data science field are the other questions that cross the young minds. From this perspective, it is important to understand the nuances of evolving workplaces. The world is slowly moving towards skill-based recruitment than a degree-based education approach. So, upskilling and reskilling initiatives, where skills hold the sway, are better imparted through bootcamp model than through traditional colleges. However, a closer look at all the nitty-gritty with a comparative study of both options will help in making an informed decision for students, and professionals.
Career in data science:
Choosing the right educational path is of foremost importance in establishing a successful career in data science. Every student or professional should consider multiple factors like learning preferences, career goals, and long-term aspirations while choosing a career path. And data science is no exception. In the dynamic world of technology, data science has emerged as one of the chosen fields, but without proper skillsets, the degree alone doesn’t carry much weight.
Data science degree:
A conventional degree in data science provides an opportunity for the learner to have a comprehensive study of all aspects of this evolving field. As it covers many topics, it takes several years to complete. An education from a formal educational institution like an engineering college have higher credentials than bootcamps. Given the time and energy spent on a degree or diploma course, in-depth knowledge is acquired. This helps in tackling challenging real-world problems, and contributes to innovative research. It provides students with a clear and well-defined learning path. Usually, a degree or diploma is well-structured that spread over several semesters. So, breaking down complex topics or tasks into smaller steps is another advantage of opting for a degree education. Educational institutions are only known for imparting education. They also provide an opportunity for building lifelong personal and professional relationships. Building lasting relationships with tutors and lecturers can greatly benefit any budding professional in building his/her career. Peer-to-peer learning is another advantage of a degree or diploma course. Usually, colleges are great places for student participation and engagement. This develops key skills like critical thinking, collaborative work, and understanding of the subject. Such a slow and steady learning process proves to be a boon for students.
Challenges of degree programmes in data science:
Despite the obvious advantages of a degree programme, it has its own limitations. Firstly, technical education is a rapidly evolving field and needs upgradation with changes in the field of data science. It is a known fact that changes in the data science field have been rapid. Ironically, the curriculum of academic institutions has remained outdated as they have limited scope to change it frequently. Therefore, students find themselves equipped with outdated knowledge when they pass out of college. Secondly, formal degrees across the world are known for their theoretical learning method with less or no exposure to the external world. While it provides a foundation of concepts and principles, it often fails to impart hands-on experience and practical skills for using and implementing technologies. Such lack of industry orientation turns a learner without the necessary knowledge and understanding of industry-specific practices and expectations. So, a student may leave the college campus without being prepared for entering the workforce. This leads to a lack of job opportunities, leading to frustration. Moreover, formal degrees are mostly examination-oriented programmes. An individual’s ability is gauged through his/her ability to score good marks in the examinations. This works in contrary to the workplace where outcome is the key for which practical skill is the necessary currency. Formal degree programmes also have their limitations in terms of high-cost structure, and entry barriers. Against this backdrop, many students passing out of engineering colleges remain unemployed despite having degrees. As per a NASSCOM study, more than 80 per cent of all engineering university graduates in India remain unemployed owing to a lack of necessary skillsets.
Data Science bootcamps:
In comparison to formal degrees or diplomas, data science bootcamps are becoming popular on the back of multiple factors. For instance, bootcamps are those places that are designed to make a student or professional industry ready. Dynamic curriculum and flexible learning are the biggest advantages of bootcamps. Data science as a field is rapidly evolving with many new technology aspects coming into play every quarter. For instance, generative AI tools like ChatGPT are transforming the face of this domain. In this regard, bootcamps can integrate new developments into their courses and impart skills necessary for the industry. Moreover, as a working professional, flexibility is critical for any reskilling purpose. Bootcamps provide the flexibility of studying on weekends or at certain free time. Importantly, bootcamps are more affordable than degree programmes. Some bootcamp programmes even provide scholarships to the students and encourage more students to join in. Industry interface is another big advantage of such programmes. These courses usually are designed by industry experts and taught by professionals with rich experience in the field with regular interactions with industry veterans. This type of learning combines theory with practical application, real-world experience, and active engagement. Moreover, dynamic support and doubt clarification sessions provide necessary handholding to learners. As these programmes are career-focussed, a learner is ready for the job market after completion of the course.
Limitations of bootcamp programmes:
However, bootcamp programmes also its own set of challenges. Usually, all bootcamp programmes are not qualitative. Not all bootcamps adhere to the same rigorous standards or have a proven track record of success. Therefore, it is essential to choose a reputable bootcamp with a credible track record for enrolling in such programmes. Programmes run by OdinSchool have demonstrated a high rate of success both in learning and job aspects in recent years and can be considered for enrollment. Moreover, rapid learning methods and their isolated nature can be counted as limitations of these programmes. However, it can be overcome if the learner has a keen mind and willingness to learn.
All-in-all, both options for learning data science come with their own set of strengths and weaknesses. Each of these programmes provides unique opportunities for various sets of people. Given the dynamic nature of data science as a field, every learner should choose its way of learning the programme. Undoubtedly, data science as a field is ever-evolving and provides myriad opportunities as a professional. Choosing the right learning partner, however, holds the key.
(The writer, Arvind Thoopurani, is the General Manager of OdinSchool)
