M.Tech Integrated - Computer Science Engineering (5-Year Program)
Course Overview
The Integrated M.Tech in Computer Science Engineering is a comprehensive five-year program tailored for high-achieving students who want an accelerated pathway to advanced technical expertise. The curriculum integrates undergraduate fundamentals with postgraduate-level specializations such as AI, cybersecurity, data science, cloud computing, and advanced algorithms.
Course Objectives
- To offer a seamless learning experience combining B.Tech and M.Tech curricula.
- To develop advanced technical competency through research-oriented learning.
- To expose students to modern computing tools, emerging technologies, and industry practices.
- To prepare graduates for leadership roles in technology, R&D, academia, and innovation-driven sectors.
Learning Outcomes
- Mastery of advanced computing concepts and modern engineering skills.
- Ability to conduct research, publish papers, and work on large-scale technical projects.
- Proficiency in specialized domains such as AI, cybersecurity, and cloud technologies.
- Enhanced analytical, programming, and problem-solving capabilities..
- Readiness for roles in research labs, tech development centers, and doctoral studies.
Curriculum
Semester 1
Practical
- Chemistry Lab
- Python Programming Lab
Theory
- Fundamentals of Technical Communication
- Matrices and Calculus
- Applied Chemistry
- Foundations of Engineering
- Python Programming
- Engineering Graphics
Semester 2
Practical
- Physics Lab
- Digital Electronics Lab
- Data Structures and Algorithms Lab
- Workshop Practices Lab
Theory
- Professional Communication Skills
- Analytical Mathematics
- Physics for Computer Science
- Digital Electronics
- Data Structures and Algorithms
- Foundation Course in Quantitative and Logical Aptitude
Semester 3
Practical
- Verbal Reasoning Lab
Theory
- Transforms and Boundary Value Problems
- Object Oriented Design and Programming
- Operating Systems
- Advanced Programming Practice
- Computer Organization and Architecture
- Design Thinking and Methodology
- Professional Ethics
Semester 4
Practical
- Critical and Creative Thinking Skills Lab
Theory
- Probability and Queueing Theory
- Design and Analysis of Algorithms
- Database Management Systems
- Artificial Intelligence
- Professional Elective I
- Social Engineering
- Universal Human Values-II: Understanding Harmony and Ethical Human Conduct
Semester 5
Practical
- Community Connect
- Analytical and Logical Thinking Skills Lab
Theory
- Discrete Mathematics
- Formal Language and Automata
- Computer Networks
- Machine Learning
- Professional Elective II
- Open Elective I
- Indian Art Form
Semester 6
Practical
- Project Work
- Employability Skills and Practices Lab
Theory
- Data Science
- Software Engineering and Project Management
- Compiler Design
- Professional Elective III
- Professional Elective IV
- Open Elective II
- MOOC
- Indian Traditional Knowledge
Semester 7
Theory
- Behavioral Psychology
- Professional Elective V
- Professional Elective VI
- Web Technologies
- Report Writing
- Open Elective III
Semester 8
Practical / Project
- Major Project / Semester Internship-I
Theory
- Parallel Computing
- Wireless and Mobile Computing
- Research Methodology
Semester 9
Theory
- Professional Elective VII
- Professional Elective VIII
- Professional Elective IX
- Professional Elective X
- Professional Elective XI
- Open Elective IV
Semester 10
Project
- Specialization Project / Semester Internship-II with Domain Internship
Open Electives
- Web Programming
- Programming in Python for Interdisciplinary Applications
- Mobile Application Development
- Data Analytics
Professional Electives
- Digital Image Processing
- Biometrics
- Internet of Things
- Bio Inspired Computing
- Computer Graphics and Animation
- Quantum Computation
- Cloud Computing for Data Analytics
- Computational Logic
- Neuro Fuzzy and Genetic Programming
- Augmented, Virtual and Mixed Reality
- Full Stack Web Development
- Data Mining and Analytics
- Natural Language Processing
- Distributed Computing
- Network Security and Cryptography
- Information Storage and Management
- High Performance Computing
- Database Security and Privacy
- Cloud Computing
- Robotics: Computational Motion Planning
- Reinforcement Learning Techniques
- Cyber Physical Systems
- Business Intelligence and Analytics
- Convolutional Neural Networks
- Advanced Machine Learning
- Financial Machine Learning
- Healthcare Analytics
- Pattern Recognition Techniques
- Semantic Web
- Speech Recognition
- Computer Vision
- Social Network Analysis
- Software Defined Networks
- Service Oriented Architecture
- Wireless Sensor Networks
- Network Protocols and Algorithms
- Functional Programming
- Cyber Security Operations
- Network Intrusions and Computer Forensics
- Mobile Forensics
- Probabilistic Graphical Models: Principles and Techniques
- Deep Generative Models
- Brain Machine Interface: Science, Technology and Application
- Data Analysis and Visualization
- Computational Perception and Cognition
- Spatial and Temporal Computing
- Neural Network Models of Cognition
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