.
by Disha Saxena
Technology Bachelor's (B.Tech) Computer science or data science? One area of engineering is well-known, whereas the other is more recent and in high demand. Both have certain similarities and differences in the way the courses are structured.
A basic explanation of the history of the disciplines and what they have to offer is as follows:
Tracing the origins:
According to experts, computer science is the parent discipline of data science.
The first emphasis in computer science was on computation and algorithms, if you follow its development. The data was incidental. Databases grew increasingly crucial as more systems became automated. In the 1990s, data warehousing and data mining first became popular, according to Shreekanth M. Prabhu, chairman of the computer science and engineering department of CMR Institute of Technology. "Big Data" is a phenomena characterized by the 4 v's - volume, variety, velocity, and variety," he continued. "With the growth of the web and social media in the previous two decades, data got even more diversified."
The Connections:
As a result, there are some connections between the two courses. Data science combines arithmetic, statistics, and computer science, whereas a computer science degree focuses on software creation and development.
The computational problems in data science are related to the algorithmic problems in computer science through the use of machine learning and related methods.
According to Robin P. Mathur, dean of the department of big data and data science at Lovely Professional University, "Those on the inside realize that the two are part of a symbiotic relationship, with intricacies to one that support the other. In order to sort through the massive amounts of data that flow via network systems and to derive insights that can be used on top of the foundation that computer science has built, data scientists offer unique methodologies.
A computer science student could opt to become a data science researcher, but the opposite may not happen, according to Taruna Gautam, vice chancellor of the Institute of Integrated Learning Management University, despite the fact that some people think the two courses are nearly identical.
"It is clear that computer science enables students to study all the fundamentals that prepare them to be adaptable with various engineering specialties. It encourages them to pursue a master's degree and a PhD in specialized fields. They can also work in domains like transdisciplinary research, full stack development, IT, and electronics," the speaker continued.
Job prospects:
Despite the fact that data science is a relatively young field, there is a growing demand for graduates in the field.
LinkedIn designated data science the industry with the fastest rate of job growth in 2017. Data scientist was listed as one of the finest occupations in the US in 2018 by the business review site Glassdoor.
By 2020, there will be a 39% increase in demand from employers for data scientists and data engineers, according to an IBM report. According to AIM research, which was carried out by Analytics India Magazine, the number of data science or analytics jobs in India increased by 30.1% in April 2022 compared to April 2021.
"Students who want to earn big salaries might consider specializing in data science. The prospects for both are same, with the exception that some businesses are developing specialized career categories like data analyst or data engineer. They prefer data science students in these situations. Programming abilities, communication, and exposure to current technologies are the primary determining factors in the selection process, according to K Thammi Reddy, professor of GITAM's computer science department (Deemed to be University).
Gautam continued, "The rise of social media platforms and data sets may result in an increase in demand for data study, but building these platforms from the ground up is where the B.Tech in Computer Science will shine as students are able to understand the development requirements of these platforms, allowing them to support the daily upgradability and scalability.
Computer science graduates are employed as software developers, software testing engineers, quality analysts, and web developers, among other positions, whereas data scientists are in demand in the insurance, banking, social media, analytics, advertising, and more.
The final choice:
Both courses call for analytical, problem-solving abilities as well as attention to detail.
Computer science would be the best option for someone who is interested in developing and testing software and apps, as well as network security and system design. Data science is an option for those who love learning about and analyzing data.
If a student can't decide between the two, they can also choose to major in computer science with a focus on data science in their second year of engineering.
Click Here for More Latest News