Few years ago, engineering was mainly focused on mathematics, coding, and machinery. But now, AI is a foundation subject. In specializations such as BTech in AI or BTech CSE AI ML, students learn how machines process data, mimic human intelligence, and make smart decisions. Artificial intelligence is revolutionizing B.Tech education by rethinking what is taught, how it is taught, and the skills students need for future professions. It creates a personalized, interactive and industry-aligned learning experience.  AI has evolved from a specialized subject to a fundamental part of the curriculum, resulting in more individualized, engaging, and sector-specific learning opportunities.
In B.Tech programs, AI is not just a subject of study; it’s becoming a tool, a teaching assistant for innovation in pedagogy and research. Artificial Intelligence has moved beyond research labs and has entered classrooms thereby transforming how engineering students learn, think, and prepare for their careers.

AI-driven learning platforms analyze student data to identify strengths and weaknesses by offering practice exercises and learning paths. To name a few, examples are Coursera, Khan Academy, Udemy where the students can learn at their own pace, improving retention and engagement.

 AI chatbots and virtual teaching assistants can answer student queries any time, thereby providing hints, or evaluating code automatically. Examples are like ChatGPT or Google’s Socratic; these help in clarifying complex engineering concepts.

 AI-based tools can evaluate coding assignments, MCQs, or even essays, saving time for educators and providing instant feedback to students. AI tools are used to automate grading for assignments and offer continuous, real-time feedback. This reduces the administrative burden on instructors and provides consistent evaluation.

AI also helps teachers to analyze classroom feedback and student performance data to identify topics that are causing confusion. This allows instructors to proactively adjust lesson plans. 

AI has also transformed few curriculum and integrates in many courses. These are as follows:

1. Majority of the B.Tech programs now include:

• Core AI subject like Machine Learning, Neural Networks, Data Science, Cyber security.
• AI electives like Robotics, NLP, Computer Vision
• AI-driven labs and projects

Apart from computer branch, there are other branches of engineering where smart manufacturing, robotics, and predictive maintenance are used. These are:

• Civil Engineering: AI is used for optimizing urban planning and monitoring infrastructure health.
• Electrical and Electronics: AI is used for smart grids, automated circuit design, and optimizing power systems.
• Biomedical engineering: AI is used for medical image analysis and disease diagnosis using machine learning algorithms and neural network.

Smart and immersive laboratories have also been opened and these are powered by virtual and augmented reality (VR/AR) labs to let the students to carry out challenging and frequently hazardous experiments in a secure virtual setting. For example, civil engineers can simulate structural behavior, electrical engineers test electronic circuitry.

2.   AI can bridge the gap between academia and industry 

• Industry-relevant projects enable students to work on real-world issues, universities are partnering with tech firms. For example, businesses provide datasets to universities so that students can develop computer vision, machine learning based prediction models.
• For skill development,  coding lessons and interviews are provided by AI-powered platforms to help students get ready for the workplace. Students can identify their areas for improvement with the use of the systems’ feedback.
• Placement cells leverage AI-driven analytics to connect students’ project experience and skill sets with recruiters’ needs, assisting graduates in finding suitable employment possibilities.
• As AI is developing so quickly, a continuous learning strategy is crucial. In order to remain current, B.Tech programs now place a strong emphasis on flexibility and encourage students to acquire temporary certifications.

3. AI is not limited to academics and industries; it is also beneficial to administration and management. This minimizes the time. These are as follows:

• Predictive analytics for student performance and dropout prevention
• AI chatbots for admissions and student support
• Smart classrooms with facial recognition and automated attendance of students thereby minimizing the time in taking manual attendance.

4. AI is enabling B.Tech students and faculty to conduct research in many areas. AI tools accelerate data analysis, reduce manual effort, and allow rapid prototyping using simulation models. The following areas are:

• Predictive modeling and simulation
• Smart manufacturing
• Environmental monitoring
• Healthcare technology

According to IndiaAI, around 70% of the engineering colleges include AI-based courses in different branches, ranging from civil to mechanical to computer engineering. The Future of AI in B.Tech Education proposes AI-augmented campuses, virtual labs, and AI mentors leading customized engineering education. By 2030, AI is expected to be integrated into every engineering specialization, making AI literacy a critical engineering competency.

Author

Tamalika Chaira
Associate Professor
Computer Science and Engineering, The Northcap University, Gurugram