Why AI integration is a must for tomorrow’s engineers?

Dhriti Mukherjee, a fourth-year Computer Science Engineering student, is having sleepless nights due to her inability to secure a job. Despite her strong coding skills, she’s realizing that in today’s job market, proficiency in coding alone isn’t enough. With the rise of AI, coding has become a complementary skill to AI expertise. She has understood that AI specialists, who can code and understand AI algorithms, are in high demand.

With WB HS, ISC results out and CBSE 2024 results to be out soon, students find themselves standing at the crossroads of decision-making. Traditional engineering courses have long been seen as lucrative career options, but in the age of AI, it’s crucial for students and their guardians to recognise the importance of integrating AI into these courses to stay relevant in the evolving job market. Many students, like Dhriti, studying traditional engineering courses, understand the growing influence of AI in job prospects. They realise that while traditional engineering skills are valuable, adding AI knowledge is essential for future success.

“AI is a transformational technology that is going to affect all professions and even our way of life. Everybody should know about the impact of AI in their everyday interaction. At the same time, every profession should learn about the impact of AI in their job… what AI tools are available for me to complete my job more effectively. Be it a doctor, a lawyer, an accountant, or engineer, AI is changing the way people will go about doing their job. Just as it is imperative to learn computing today regardless of your profession, it will be important to learn about AI tools in the near future. AI tools are improving at a rapid pace that learning a specific programming language might not be required in the near future. For the time being, python is the language of choice and student should certainly learn Python to get into AI development,” said Prof Balaraman Ravindran, Head, Wadhwani Department of Data Science and AI. He is also the Head of Centre for Responsible AI & Robert Bosch Centre for Data Science and AI, IIT Madras.

In the tech industry, the rise of AI indicates a future where human intelligence and AI will collaborate, reshaping how work is done. To succeed in this changing landscape, tech workers must adapt, said Deepak Bharadwaj, PhD (Humanoid Robotics), Associate Professor, Computer Science Engineering, School of Engineering and Sciences, GD Goenka University. “Traditional engineering students can opt for the minor specialisation course on AI/ML, IoT-enabled manufacturing, and soft computing along with their regular engineering courses. For traditional engineering students to be competitive and stay on the cutting edge of technological breakthroughs, they must adapt and embrace AI. It is crucial to understand the fundamental concepts of AI and its evolving role in traditional engineering to navigate the changing employment landscape effectively. Preparing for AI-driven changes in employment is not just a prudent choice. It is a necessity in the face of a rapidly evolving job market,” he said.

According to Kusuma Sri, HR Manager, ODA Class, traditional engineering students can integrate AI into their coursework by taking elective courses or pursuing additional certifications in AI-related fields. “For example, students studying mechanical engineering can explore AI applications in robotics or autonomous systems, while those in electrical engineering can delve into AI-driven control systems or ML algorithms for signal processing,” she said.

Last year, the government of India had launched AI for India 2.0, a new programme that provided free online training. Several online certificate programmes on AI, ML are available. Microsoft has a 12-lesson course on Generative AI for Beginners, Havard Business School offers an AI course, and upGrad and Coursera have courses on AI where participants can develop job-relevant skills with hands-on projects. Also, AICTE constituted team of experts to prepare the model curriculum of UG degree course in Robotics and Artificial Intelligence Engineering. Similar exercise is done for other UG, Diploma and PG level in engineering, MBA, PGDM, Architecture, etc.

AR Ramesh, CEO, TeamLease Degree Apprenticeship believes it is essential to have a stronger industry-academia collaboration to design curricula which are relevant and aligned with industry needs. “Institutes can collaborate with tech companies to understand the latest applications of AI technology across various sectors such as healthcare, finance, and manufacturing. Through these partnerships, institutes can tailor their AI courses to include specific use cases and practical examples relevant to these industries,” said Ramesh. He further added how institutes can leverage apprenticeship programmes as a means to bridge the gap between classroom learning and industry needs. Meanwhile, Hariom Seth, Founder, Tagglabs, stresses the importance of institutes building strong ties with industry partners to truly grasp their needs and adjust their courses accordingly. He also suggested how institutions can extend their collaboration in internships, guest lectures and workshops.

According to Prof Rajesh K Singh, Professor, Operations Management Area, Chairperson - PGDM, MDI Gurgaon, colleges and institutes can enrich their curriculum by weaving AI into existing programmes. “This can involve creating interdisciplinary courses that merge AI with other subjects, fostering a holistic approach to education. Through industry-led workshops and hackathons, students can apply AI concepts in practical settings, transforming their learning experience,” he said.

LinkedIn’s chief product officer, Tomer Cohen, mentioned in an interview how there’s been a 21-fold increase in job postings mentioning GPT or ChatGPT. Today, candidates have diverse career options in AI and ML, including roles as research engineers, business intelligence analysts, data scientists, and ML engineers, with all IITs offering dedicated courses in these fields, alongside institutions like Chandigarh University, Jadavpur University, SRM Institute of Science and Technology, LPU, and VIT Vellore, among others.

“ML courses are already an important part of the curriculum in most engineering programmes. Developing proficiency in data analytics, statistics, and programming languages like Python and R will certainly boost their value in the job market. Candidates with statistics and certain math topics, such as Linear Algebra, Machine learning packages such as Tensorflow, PyTorch, Scikit-Learn and Image packages such as OpenCV and YOLO hold a competitive advantage in the job market,” said Prof Kaushik Gopalan, Associate Professor, Computer Science, FLAME University.

Dr Shamik Tiwari, Professor and Dean, School of Computer Science and Engineering, IILM University, Gurugram, emphasised the importance of exploring interdisciplinary coursework or research projects that combine AI with their primary field of study. “As per NEP-2020 vision, these courses must be offered to the students as multidisciplinary courses. Many engineering programmes now offer courses specifically focused on AI, ML, and data science these days. Engineering students interested in AI should prioritise learning programming languages such as Python, along with skills in ML algorithms, data analysis, deep learning, natural language processing, computer vision, and cloud computing platforms like AWS or Azure,” he said.

With AI constantly evolving, it’s crucial for students, employers, and policymakers to work together. This means investing in education and training, promoting lifelong learning, and creating policies that help students shift into new roles shaped by AI while maximising its benefits and addressing challenges effectively. Also, as students begin their engineering journey, let’s remind them again to consider the importance of AI in their course selections for a well-rounded education.