Coding vs. Core Engineering: Which One to Pursue?
Jayanth K Singh, Professor - Department of Chemical Engineering, IIT Kanpur, during an interaction with Higher Education Review, shared his views on the evolving dynamics between coding and core engineering. He highlighted the significance of mastering fundamental concepts, whether in coding or traditional engineering domains. Emphasizing the growing importance of AI, machine learning, and interdisciplinary knowledge, he discusses how students can prepare for their futures by combining coding skills with their area of expertise.
Many students struggle to decide between coding and core engineering. How should one determine which path aligns better with their skills and interests?
Since the inception of information technology and the dynamic changes in the job market, students have been concerned about whether they should prioritize coding or focus on the code itself. The decision should align with their interests. The only thing that will matter to the market is that you have a good understanding of the fundamental concepts that you pursue. If coding is the focus, then you have to be able to understand the fundamental concepts of coding from a computer science point of view. Most of the basic coding will be taken out by ChatGPT and other tools. Therefore, it is important to develop a potential for fundamental knowledge in coding and integration with the core knowledge, because at the end of the day, if you are a coder, you would be expected to develop new things in today's and tomorrow's time. If you are a core engineer, you will be expected to learn from this new dimension of AI and accelerate the core engineering.
Moreover, it is equally important to have a strong foundation in core engineering. Students should decide whether to learn coding or pursue core engineering based on their passion, not the job market. It is crucial to learn new methodologies and technologies. However, it is equally important to assess whether you are truly passionate about them. If you are not passionate about those specific technologies but want to leverage them, then focus on understanding the underlying principles and how to deploy secure technologies into the process of acceleration, discovery, and innovation the core dimension.
In recent years, we have seen an increasing number of engineers from core fields transitioning into software roles. What does this trend indicate for the future of core engineering?
This was largely the case over the past decade. Individuals who have a strong expertise in core engineering, a good understanding of coding and software will be valued more in the core industry. The reason is most mundane coding tasks will be done by tools such as ChatGPT, DeepSeek, and other similar technologies. But there will be a requirement to develop a large model, called a machine, specifically designed for engineering. This will require people who have an understanding of engineering fundamentals and understand the logic of these models.
AI and machine learning are being adopted by core engineering sectors. As a result, having an interdisciplinary knowledge, combining knowledge of IT, software, and core engineering is becoming critically important across industries. Moving from core to software or vice versa should not be done superficially. It is important to get into a full-scale course, such as a major in computer science or electrical engineering that will help in this transitioning phase of this world where AI is becoming the core of all engineering and innovation.
For students aspiring to work in emerging fields such as robotics, IoT, or AI-driven manufacturing, which career path would be more beneficial?
All these areas, especially robotics, reflect that machines are becoming more intelligent, which is relevant to core engineering. In past years, industries such as chemical, power, petrochemical, and alchemical have gone through significant phases of automation. However, even with automation, the understanding of the operations of the whole plant was still important. Even when troubleshooting, knowing the relevance of each of the parameters requires a deep understanding of the core engineering. With consistent practice and hands-on experience, one can build expertise in these domains. There is a need for understanding mechanics, core engineering, and how to interface AI and ML, in fields such as robotics, while fields such as robotics and others have yet to reach saturation. As a result, the concept of a double major is expected to have a significant impact and will likely become more popular in the next decade. People will be looking to combine core engineering with an additional subject so they can interface and integrate this learning with their core area of expertise.
The challenge in today's time, especially in India, is that the market has not adopted this model as quickly as one had thought or hoped, especially within manufacturing, chemical, and other core engineering domains. This is going to take some time. The other factor is, due to the talent field, patent issues, and related factors, innovation and research and development in core engineering are expected to rise. So the students in core engineering are the ones who will mainly benefit over the next 10 to 15 years. If you are considering this area, it is best to go with core engineering and add some AI and machine learning. A dual-focus or interdisciplinary approach during your undergraduate studies will greatly improve your competency and job opportunities.
However, if you are interested precisely in coding, then try to get into a program wherein you develop models, become an innovator, and a tool developer, because those roles are going to be more valuable. One cannot expect a simple programmer to survive in the market, as there will be no requirement for such simple programmers. Instead, individuals who think critically, who are developing tools, methods, and packages to meet the needs of both today's and tomorrow's industry and society, will be more valued. Therefore, entering those dimensions is going to be more lucrative.
What are some essential software tools or programming languages that core engineers should learn to complement their domain knowledge?
The standard tools are evolving rapidly. However, Python remains one of the most versatile packages, integrating across a wide range of areas from numerical analysis to modeling, AI, ML, and beyond. Besides Python, other tools are useful from an engineering aspect, MATLAB for instance, which works extremely well in an engineering domain. Many of the tools and functions that you can find in MATLAB are also being incorporated into Python packages, which are open source. Python is one of the essential tools that everyone must have. Furthermore, every engineering student takes a fundamental course in numerical modeling, machine learning, and advanced AI. These are essential courses that everyone should understand and complete, as they will be critical in navigating the challenges and opportunities of the future.
How should students balance traditional engineering skills with coding to stay competitive in the future workforce?
All educational institutions need to adopt and modify the course curriculum to provide the rightful structure for students to follow. Students should focus fundamentally because of a large set of questions or the problem statement with machine learning models or the DeepSeq and others which has a billion parameters. However, whether the output is correct or incorrect, it needs to be interpreted by someone with expertise. Therefore, having a sound knowledge of core subjects is far more important than possessing only problem-solving skills. It is important to focus on building strong foundational knowledge rather than acquiring overly vast knowledge.
Having sound knowledge in one core area will be relevant in a core industry, but if you want to cater to the interdisciplinary aspect that every engineering field will involve, it is important to also learn the languages of other fields. Therefore, at the undergraduate level, it is going to be very useful to augment core knowledge and skills with additional knowledge from other fields, particularly computer science. If you are interested in computer science or if you are interested in finance, then take courses in economics as one of the important parts. If you are interested in robotics, then it is important to add robotics from mechanical engineering and electrical engineering from that standpoint. It is an advantage to pursue further courses to build your knowledge base as it prepares you for future challenges. While becoming an expert requires advanced degrees like a master's program. But to understand the language and nuances requires you to have a fundamental sound knowledge of these areas.
