School of Engineering

B.Tech. in CSE (Cyber Security) is a 4-year undergraduate program that combines computer science and engineering with a concentration on cybersecurity. The curriculum includes core computer science ideas, programming languages, and network security, as well as more advanced topics such as cryptography, ethical hacking, and digital forensics.This course taught us about how to secure computer systems, networks, and data against cyber attacks. The program also offers hands-on training, projects, and internships to prepare students for careers in cybersecurity, information security, and related sectors.

B.Tech. in Computer Science and Engineering (CSE) with a Specialization in Artificial Intelligence is an undergraduate degree program that combines regular computer science study with an emphasis on AI technology. This 4-year course provides students with a solid foundation in programming, data structures, algorithms, and software engineering, as well as deep dives into AI-specific topics including machine learning, deep learning, natural language processing, computer vision, and robotics. Program will help to learn how to use AI approaches to create intelligent systems, evaluate complex data, and solve real-world problems. Hands-on projects, internships, and research opportunities are frequently included in the curriculum to provide students with actual experience using AI ideas. 

The M.Tech. in Cyber Security is a 2-year postgraduate program that emphasizes advanced topics in information security, cryptography, network defense, and digital forensics. The program includes topics including ethical hacking, cloud security, IoT security, and security analytics. Students acquire practical experience through lab sessions and industrial assignments, acquiring competence in creating and executing robust cybersecurity solutions. The program of study prepares graduates for leadership roles in cybersecurity, including security analysts, penetration testers, security architects, and information security managers in a variety of sectors, as well as research and development positions in information security.

B.Tech. in Machine Learning is a 4-year undergraduate program that teaches students fundamental computer science principles as well as specialized abilities in machine learning algorithms, data analysis, and artificial intelligence (AI). The curriculum usually incorporates programming, data structures, mathematics, and fundamental machine learning concepts like supervised and unsupervised learning, neural networks, and deep learning. Labs, projects, and internships provide students with practical knowledge as they prepare for careers in data science, AI development, robotics, and other fields. Graduates are well-prepared to work in industries such as banking, healthcare, and technology, or to pursue additional studies in AI and machine learning.

 

 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.

B.Tech. in Cloud Computing is a  4-year undergraduate program that focuses on the study of cloud computing technologies, services, and solutions. The course covers various aspects of cloud architecture, cloud security, data management, virtualization, and cloud-based application development. Students learn to design, deploy, and manage cloud services and gain proficiency in platforms like AWS, Google Cloud, and Microsoft Azure. The program emphasizes hands-on learning, problem-solving, and the development of scalable and efficient cloud infrastructure. Graduates of this program are equipped to pursue careers as cloud engineers, cloud architects, DevOps engineers, and system administrators in various industries, such as IT, finance, and healthcare, making it a highly sought-after course in today’s tech-driven world.

 M.Tech. in Cloud Computing is a postgraduate program that focuses on advanced concepts in cloud infrastructure, architecture, and services. The course typically spans 2 years, divided into 4 semesters. Students learn about various cloud platforms, virtualization, big data, network security, and cloud storage, along with practical skills in designing and managing cloud-based systems. The curriculum combines theoretical knowledge with hands-on training, preparing graduates to work in roles such as cloud architects, cloud engineers, and IT consultants. The program also covers emerging technologies such as edge computing, artificial intelligence, and machine learning as applied to the cloud. This course equips students with the necessary skills to meet the growing demand for cloud computing professionals across industries.

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.