Compute science: What should students choose?

With so many flavours of computer science, what should students choose? Rao says the first year syllabus is the same for all the streams, but many colleges and universities are not yet clear what to include in the different courses in the following years. Around 80% of the syllabus, he expects, will be the same for all courses, as they all belong to one family.
He says CSE understandably is the most popular course because those who have a base in CSE can learn emerging technologies in a few months. “Besides, we do not know what will be the situation of the emerging areas in four years,” he says.

K N Subramanya, principal of Bengaluru’s RV College of Engineering, says around 60% of all the courses are fundamental computer science. He expects the placement opportunities to be the same for all the branches.
S Sadagopan, former director of IIIT-Bangalore, says CSE is the plain vanilla and the ever favourite. “If you choose something special, everyone might not like it. With plain vanilla, no one dislikes it,” he says. He compares it with MBA, and MBA in finance. “A general degree has more advantage,” he says, adding, “CS is more holistic, and the discipline will have value for a longer period.”
He notes that just as computer science emerged out of maths, all of the emerging areas have emerged out of computer science. CS is the mother discipline. “This is a huge value chain – IoT to big data, big data to analytics, analytics to AI, AI to deep learning, deep learning to robotics, robotics to drone, and drone to robotic surgery… Many of these things used to be done by CS folks, just like maths folks did CS earlier. What is going to be important in the future, nobody knows. Right now analytics is big. But how long will it be big, we don’t know,” Sadagopan says,
Gopakumaran Thampi, principal of Thadomal Shahani Engineering College, Mumbai, advises students to choose the subjects based on “what resonates with their life rhythm” (interest). But he does have a preference for CSE with AI, encompassing ML, deep learning, and natural language processing. “Even in the 1990s, there was AI. We used to teach about software systems that learn from previous experiences. But now, there are cost-effective, pervasive, hardware systems available that enable theory to be converted into practice. There is a huge market. Every software system that is implemented needs to be built with some sort of intelligence. And as time progresses, the level of intelligence will increase. The market for conversational AI is evolving. There is a big market for AI in manufacturing, controls, and mass customisation,” he says.
Colleges, he says, can proactively prepare students for the rapidly evolving technologies. “Even while syllabuses are prepared by the university, the curriculum is flexible, as every semester there is a mini project to be done. If the department is active, it can look out for the market trends, new technology and tools. The departments can get open source resources free of charge (to teach new tech),” he says. But, he reiterates, at the end of the day, “it is all about the mathematical inclination and the interest of the students.”