School of Engineering

B.Tech. Mechanical Engineering is a 4-year undergraduate curriculum that focuses on the design, manufacture, and maintenance of mechanical systems. Students study thermodynamics, fluid mechanics, materials science, and machine design. The curriculum integrates academic knowledge with practical applications via laboratory work and projects. Graduates are prepared to work in industries such as automotive, aerospace, robotics, and energy, or to further their education in specific disciplines of mechanical engineering.

B.Tech. in Computer Science and Engineering is a 4-year undergraduate degree that provides students with a solid foundation in computer science principles and engineering methods. The course content includes programming languages, algorithms, data structures, software engineering, database management, computer networks, and artificial intelligence. Students receive practical experience through projects and internships. This degree prepares graduates for professions in software development, system analysis, cybersecurity, and other technical industries, as well as advanced computing studies.

B.Tech. Civil Engineering is a 4-year undergraduate curriculum that prepares students to design, build, and maintain infrastructure projects. The curriculum includes topics such as structural engineering, geotechnical engineering, transportation systems, water resource management, and environmental engineering. This course taught about how to apply mathematical and scientific principles to real-world civil engineering problems, how to use advanced software tools, and how to obtain hands-on experience through laboratory and field projects. This degree equips graduates to work in building, urban planning, and infrastructure development.

The 4-year undergraduate Bachelor of Technology (B.Tech.) in Electrical and Electronics Engineering degree integrates concepts of electronic systems and electrical engineering. Circuit theory, power and control systems, digital electronics, and microprocessors are just few of the topics covered over here. Through design projects, laboratory work, and frequently finishing industry internships, students obtain practical experience. Modules on cutting-edge technology like robots, IoT, and renewable energy systems are frequently included in curriculum. Graduates are equipped for jobs in various  fields, like automation, consumer electronics, telecommunications, and power generation and distribution. With an emphasis on creativity, problem-solving abilities, and sustainable practices, the program prepares students to tackle today's issues in smart grids, energy efficiency, and electronic device design.

 M.Tech. in Data Science is a 2-year postgraduate program designed to equip students with advanced knowledge and skills in data analytics, machine learning, and big data technologies. This course covers various aspects such as data mining, statistical analysis, data visualization, and artificial intelligence, preparing students for roles in industries like IT, finance, healthcare, and e-commerce. The curriculum includes a blend of theoretical knowledge and practical experience, with hands-on training on industry tools and techniques. Students also work on real-time projects and case studies to develop problem-solving abilities. Upon completion, graduates can pursue career opportunities as data scientists, analysts, engineers, or researchers, contributing to data-driven decision-making processes in organizations.

 M.Tech. in Artificial Intelligence (AI) is a postgraduate program designed to equip students with advanced knowledge and skills in AI technologies. Typically spanning 2 years, this course covers a wide range of topics including machine learning, deep learning, natural language processing, computer vision, robotics, and data science. Students engage in both theoretical studies and practical applications, preparing them for careers in AI research, development, and implementation across various industries such as healthcare, finance, and technology. The curriculum includes core subjects, electives, and hands-on projects, fostering problem-solving abilities and innovation. By the end of the program, graduates are ready to tackle complex challenges in AI and contribute to the rapidly evolving field.

M.Tech. in Machine Learning is a specialized postgraduate program designed to equip students with advanced skills in machine learning, artificial intelligence, and data science. Typically spanning 2 years, the course covers core subjects such as statistical learning, deep learning, reinforcement learning, natural language processing, and algorithm design. Students gain hands-on experience in building models, data analysis, and implementing machine learning algorithms across various domains like healthcare, finance, and robotics. The program is ideal for individuals aiming for careers as data scientists, AI researchers, or machine learning engineers. Admission requirements usually include a background in computer science or related fields, and graduates are well-prepared to tackle complex problems in industries increasingly driven by AI and automation.