School of Engineering

The M.Tech. in Computer Science & Engineering is a 2-year postgraduate degree that provides advanced specialization in artificial intelligence, machine learning, computer networks, cybersecurity, and software engineering. The program encompasses cutting-edge topics like as deep learning, cloud computing, the Internet of Things, and data mining. Through hands-on projects, industrial internships, and research, students acquire expertise in designing and implementing innovative computing solutions to complicated real-world issues. Graduates of this degree have the opportunity to work as software architects, data scientists, cybersecurity professionals, and research engineers in the fast-changing field of computer science and information technology.

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.

 

Bachelor of Technology (B.Tech.) in Data Science is a 4-year undergraduate program that equips students with skills in data analysis, machine learning, artificial intelligence, and big data management. This course combines technical and analytical training, including programming languages like Python and R, statistical methods, and data visualization techniques to prepare graduates for the growing demand in data-driven industries. Throughout the program, students learn to process, analyze, and interpret complex data sets, turning raw data into actionable insights. Graduates find career opportunities as data scientists, data engineers, and business analysts across various sectors, including technology, finance, and healthcare.

M.Tech. in Software Engineering is a postgraduate course designed to provide in-depth knowledge and skills in software development, design, and management. Typically spanning 2 years, this program equips students with advanced techniques in areas such as software architecture, programming languages, database management, and software testing. It emphasizes both theoretical concepts and practical applications, preparing graduates for leadership roles in the IT industry. Students engage in hands-on projects, research, and internships, ensuring they are industry-ready. The curriculum also covers emerging technologies like artificial intelligence, cloud computing, and machine learning. Upon completion, graduates can pursue careers as software engineers, system architects, or project managers, with the ability to handle complex software solutions and lead development teams effectively.

B.Tech. in Full Stack Development is a comprehensive undergraduate program designed to equip students with the skills required to become proficient full-stack developers. The course typically spans 4 years and covers a wide range of subjects, including front-end technologies (HTML, CSS, JavaScript), back-end development (Node.js, Java, Python), databases (SQL, NoSQL), and cloud computing. Students also gain expertise in software development methodologies, version control systems like Git, and frameworks such as React and Angular. The curriculum integrates hands-on projects, internships, and industry collaboration to provide practical experience. Graduates of this course are well-prepared to work in various domains, such as web development, software engineering, and application development, with strong problem-solving and programming skills.

 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.

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.