Under Graduate (Bachelor of Technology)
B.Tech in Computer Science and Engineering is designed to make a strong foundation in CSE that includes electronics and hardware. Computer science courses are introduced in the early semesters while non-IT courses in the later stages. IT workshops are specially designed courses allowing the students to have mastery in the use of the latest software technologies. The courses in mathematics, sciences, engineering and humanities enable students to explore the wider applications of technology.
AC Approved Curriculum for B.Tech. CSE
B.Tech in Information Technology is a 4-year engineering degree that primarily focuses on areas related to Computer Networks and computer-based information systems used for data communication, data analysis, cloud computing, etc. It covers both software as well as hardware aspects to generate, manage, and communicate information in the form of certain complex codes. In recent years, the IT sector is evolved as the most lucrative area influencing nearly all the sectors and industries around us. B.Tech in IT program helps to bridge the gap between industry and academia to create an employable workforce for them.
AC Approved Curriculum for B.Tech. IT
B.Tech in Electronics and Communication Engineering is designed to build a strong foundation in both core electronics and modern communication technologies. Fundamental electronics and circuit design courses are introduced early, followed by advanced topics like wireless communication, signal processing, and embedded systems. Specialized lab sessions and hands-on workshops equip students with practical skills in using cutting-edge tools and technologies. Supporting courses in mathematics, computer science, and humanities broaden the scope for interdisciplinary applications and innovation.
B.Tech in Artificial Intelligence is designed to provide a strong foundation in core computer science along with specialized knowledge in AI and machine learning. Early semesters focus on programming, data structures, and mathematics, while advanced courses cover deep learning, natural language processing, and AI ethics. Practical labs and project-based learning help students gain hands-on experience with modern AI tools and frameworks. Supporting courses in statistics, cognitive science, and humanities enable students to understand and apply AI in diverse real-world contexts.
