M.Tech in Computer Science Engineering is a 2-year full time Postgraduate Course which imparts a breadth of advanced knowledge in various areas of Computer Science. Today, Computers have changed the very texture of life. The phenomenal technological advancements made in the field of Computer Science are really mind-boggling. We are heading towards an era of self-driven cars, unmanned airplanes, the robot managed business centers. The day is not far when the computers will read and translate the thoughts of a human being. The emergence of new technologies like multi-core processor, mobile computing and cloud computing is redefining the boundaries of computing. The inter-disciplinary approach has brought with it new challenges. Good technical know-how and skills are in demand by employers across the world. The strong, well equipped Computer Science& Engineering Department of GIFT is one of the most preferred destinations for students. The faculties of the Computer Science & Department are highly experienced and research oriented. The students under the guidance of teachers undertake various projects to explore new horizons of knowledge.
What is the eligibility for M.Tech CSE?
To be eligible to pursue this course at GIFT, a student must have completed a Bachelor’s Degree in Computer Science or any related subject from a well-recognized university/institute/college. The eligible students must have appeared OJEE-PGAT/ GATE and secure a good rank.
| M.Tech 1st Semester | |||
|---|---|---|---|
| Slno | Course | Course Outcomes | |
| 1 | COMPUTATIONAL METHODS AND TECHNIQUES | CO1 | Solve a set of algebraic equations representing steady state models formed in engineering problems |
| CO2 | Apply optimization techniques to real life problems. | ||
| CO3 | Predict the system dynamic behavior through solution of ODEs modeling the system | ||
| CO4 | Solve PDE models representing spatial and temporal variations in physical systems through numerical methods | ||
| CO5 | Acquire and use knowledge of genetic algorithm to optimize real life problems. | ||
| CO6 | Learn and applyfuzzy logic & neural network prediction algorithm to solve engineering problems | ||
| 2 | INTERNET OF THINGS | CO1 | Understand the concepts of Internet of Things |
| CO2 | Apply the concepts of IOT | ||
| CO3 | Apply IOT to different applications | ||
| CO4 | Analysis and evaluate protocols used in IOT | ||
| CO5 | Design and develop smart city in IOT | ||
| CO6 | Analysis and evaluate the data received through sensors in IOT | ||
| 3 | ADVANCED COMPUTER ARCHITECTURE | CO1 | Demonstrate concepts of parallelism in hardware/software |
| CO2 | Discuss memory organization and mapping techniques. | ||
| CO3 | Describe architectural features of advanced processors. | ||
| CO4 | Interpret performance of different pipelined processors. | ||
| CO5 | Explain data flow in arithmetic algorithms | ||
| CO6 | Development of software to solve computationally intensive problems. | ||
| 4 | ADAVANCED DATA STRUCTURE AND ALGORITHM | CO1 | Analyze the asymptotic performance of algorithms. |
| CO2 | Write rigorous correctness proofs for algorithms. | ||
| CO3 | Choose appropriate data structures and algorithms, understand the ADT/libraries, and use it to design algorithms for a specific problem. | ||
| CO4 | Understand the necessary mathematical abstraction to solve problems. | ||
| CO5 | Come up with analysis of efficiency and proofs of correctness | ||
| CO6 | Comprehend and select algorithm design approaches in a problem specific manner. | ||
| 5 | ADVANCED OPERATING SYSTEM | CO1 | Describe and explain the fundamental components of a computer operating system. |
| CO2 | Define, restate, discuss, and explain the policies for scheduling, deadlocks, memory management, synchronization, system calls, and file systems. | ||
| CO3 | Describe and extrapolate the interactions among the various components of computing systems. | ||
| CO4 | Design and construct the following OS components: System calls, Schedulers, Memory management systems, Virtual Memory and Paging systems. | ||
| CO5 | Illustrate, construct, compose and design solutions via C/C++ programs, and through NACHOS. | ||
| CO6 | Measure, evaluate, and compare OS components through instrumentation for performance analysis. | ||
| M.Tech 2nd Semester CSE | |||
| Slno | Course | Course Outcomes | |
| 1 | Computer Graphics | CO1 | Understand the basics of computer graphics, different graphics systems and applications of computer graphics. |
| CO2 | Discuss various algorithms for scan conversion and filling of basic objects and their comparative analysis | ||
| CO3 | Use of geometric transformations on graphics objects and their application in composite form | ||
| CO4 | Extract scene with different clipping methods and its transformation to graphics display device. | ||
| CO5 | Explore projections and visible surface detection techniques for display of 3D scene on 2D screen | ||
| CO6 | Render projected objects to naturalize the scene in 2D view and use of illumination models for this. | ||
| 2 | Software Engineering | CO1 | Apply software engineering principles and techniques and develop, maintain and evaluate large-scale software systems. |
| CO2 | Produce efficient, reliable, robust and cost-effective software solutions. | ||
| CO3 | Communicate and coordinate competently by listening, speaking, reading and writing english for technical and general purposes. | ||
| CO4 | Work as an effective member or leader of software engineering teams. | ||
| CO5 | Manage time, processes and resources effectively by prioritising competing demands to achieve personal and team goals Identify and analyzes the common threats in each domain. | ||
| CO6 | Understand and meet ethical standards and legal responsibilities. | ||
| 3 | Fast Machine Learning | CO1 | understanding of the fundamental issues and challenges of machine learning |
| CO2 | Identify data,model selection and model complexity. | ||
| CO3 | Describe the strengths and weaknesses of many popular machine learning approaches. | ||
| CO4 | Discuss the underlying mathematical relationships within and across Machine Learning algorithms | ||
| CO5 | Apply the paradigms of supervised and un-supervised learning in various problem domain. | ||
| CO6 | Design and implement various machine learning algorithms in a range of real-world applications | ||
| 4 | Cloud Computing | CO1 | Articulate the main concepts, key technologies, strengths, and limitations of cloud computing and the possible applications for state-of-the-art cloud computing |
| CO2 | Identify the architecture and infrastructure of cloud computing, including SaaS, PaaS, IaaS, public cloud, private cloud, hybrid cloud, etc. | ||
| CO3 | Choose the appropriate technologies, algorithms, and approaches for the related issues. | ||
| CO4 | Identify problems, and explain, analyze, and evaluate various cloud computing solutions. | ||
| CO5 | Explain the core issues of cloud computing such as security, privacy, and interoperability. | ||
| CO6 | Provide the appropriate cloud computing solutions and recommendations according to the applications used. | ||
| 5 | Big Data Analytic | CO1 | Identify the characteristics of datasets and compare the trivial data and big data for various applications. |
| CO2 | Select and implement machine learning techniques and computing environment that are suitable for the applications under consideration. | ||
| CO3 | Solve problems associated with batch learning and online learning, and the big data characteristics such as high dimensionality, dynamically growing data and in particular scalability issues. | ||
| CO4 | Apply scaling up machine learning techniques and associated computing techniques and technologies. | ||
| CO5 | Recognize and implement various ways of selecting suitable model parameters for different machine learning techniques. | ||
| CO6 | Integrate machine learning libraries and mathematical and statistical tools with modern technologies like hadoop and mapreduce. | ||
| M.Tech 3rd Semester | |||
| Slno | Course | Course Outcomes | |
| 1 | Reserach Methodology | CO1 | Develop understanding on various kinds of research, objectives of doing research, research process, research designs and sampling. |
| CO2 | Understand qualitative research techniques | ||
| CO3 | Discuss the issues and concepts salient to the research process | ||
| CO4 | Design complex issues inherent in selecting a research problem, selecting an appropriate research design, and implementing a research project. | ||
| CO5 | Apply measurement & scaling techniques as well as the quantitative data analysis for a research problem | ||
| CO6 | Implement hypothesis testing procedures | ||
| 2 | Intellectual Property Rights | CO1 | Identify different types of Intellectual Properties (IPs), the right of ownership, scope of protection as well as the ways to create and to extract value from IP. |
| CO2 | Recognize the crucial role of IP in organizations of different industrial sectors for the purposes of product and technology development. | ||
| CO3 | Identify activities and constitute IP infringements and the remedies available to the IP owner and describe the precautious steps to be taken to prevent infringement of proprietary rights in products and technology development. | ||
| CO4 | Describe the processes of Intellectual Property Management (IPM) and various approaches for IPM and conducting IP and IPM auditing and explain how IP can be managed as a strategic resource and suggest IPM strategy. | ||
| CO5 | Anticipate and subject to critical analysis arguments relating to the development and reform of intellectual property right institutions and their likely impact on creativity and innovation. | ||
| CO6 | Demonstrate a capacity to identify, apply and assess ownership rights and marketing protection under intellectual property law as applicable to information, ideas, new products and product marketing | ||
Detailed Subjects & Credit Structure for 2 years
