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M-TECH in Computer Science And Engineering at SRM Institute of Science and Technology
Chengalpattu, Tamil Nadu
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About the Specialization
What is Computer Science and Engineering at SRM Institute of Science and Technology Chengalpattu?
This M.Tech Computer Science and Engineering program at SRM Institute of Science and Technology focuses on equipping students with advanced theoretical knowledge and practical skills in cutting-edge computing domains. It is tailored to meet the evolving demands of the Indian IT industry, emphasizing areas like AI, Machine Learning, Data Science, and Cybersecurity. The program''''s interdisciplinary approach prepares graduates for leadership roles in a rapidly growing technology landscape.
Who Should Apply?
This program is ideal for engineering graduates with a B.E./B.Tech in Computer Science, IT, or related fields, and MCA/M.Sc (CS/IT) degree holders, who aspire to pursue advanced research or take on specialized roles in the technology sector. It also caters to working professionals seeking to upskill, transition into advanced computing roles, or delve deeper into specific areas like AI/ML or distributed systems within Indian tech companies.
Why Choose This Course?
Graduates of this program can expect to secure roles as AI/ML Engineers, Data Scientists, Cloud Architects, Cybersecurity Analysts, or Research Scientists in top-tier Indian and multinational companies. Entry-level salaries typically range from INR 6-10 lakhs per annum, with experienced professionals earning significantly more. The program fosters a strong foundation for higher studies like Ph.D. or pursuing entrepreneurial ventures in India''''s vibrant startup ecosystem.
Student Success Practices
Foundation Stage
Master Advanced Data Structures and Algorithms- (Semester 1-2)
Dedicate significant time to understanding and implementing complex data structures and algorithms covered in CS2101. Regularly solve problems on platforms like HackerRank, LeetCode, and GeeksforGeeks to strengthen problem-solving skills, which are crucial for technical interviews in India.
Tools & Resources
HackerRank, LeetCode, GeeksforGeeks, Coursera (Algorithm Specialization)
Career Connection
A strong grasp of DSA is fundamental for cracking product-based company interviews and forms the backbone of efficient software development.
Build a Strong Research Foundation- (Semester 1-2)
Actively engage with the ''''Research Methodology and IPR'''' course (RM2101). Start identifying potential research interests early, read relevant research papers, and discuss ideas with faculty. This lays the groundwork for your mini-project and eventual thesis, fostering critical thinking.
Tools & Resources
Google Scholar, IEEE Xplore, ACM Digital Library, SRMIST Library Resources
Career Connection
Develops analytical skills and prepares you for research-oriented roles or higher academic pursuits.
Participate in Coding Competitions & Hackathons- (Semester 1-2)
Join competitive programming clubs and participate in internal and external hackathons or coding contests. This practical application of theoretical knowledge enhances coding speed, teamwork, and ability to work under pressure, invaluable skills for any tech role.
Tools & Resources
CodeChef, TopCoder, Internal SRMIST Hackathons, Major League Hacking (MLH)
Career Connection
Showcases practical skills to recruiters, builds a project portfolio, and offers networking opportunities.
Intermediate Stage
Specialize through Electives and Certifications- (Semester 2-3)
Carefully choose professional electives (Semesters 2 & 3) that align with your career goals (e.g., AI/ML, Cloud, Cybersecurity). Supplement these with industry-recognized certifications from platforms like AWS, Google Cloud, or deeplearning.ai to gain specialized expertise highly valued in the Indian job market.
Tools & Resources
Coursera, edX, Udemy, AWS Certifications, Google Cloud Certifications
Career Connection
Positions you as a specialist, making you a more attractive candidate for targeted roles in niche tech areas.
Engage in Mini-Projects and Internships- (Semester 2-3)
Leverage the ''''Mini Project with Seminar'''' (CS2209) to build a substantial project. Actively seek internships (even short-term ones) during semester breaks. Practical industry exposure is critical for understanding real-world challenges and building a strong resume for Indian companies.
Tools & Resources
LinkedIn, Internshala, College Placement Cell, GitHub for project showcasing
Career Connection
Provides real-world experience, enhances problem-solving, and significantly improves placement prospects.
Network with Faculty and Industry Experts- (Semester 2-3)
Regularly interact with your professors, especially those whose research aligns with your interests. Attend webinars, workshops, and industry events hosted by SRMIST or external bodies to connect with professionals. These connections can lead to mentorship, project opportunities, and job referrals.
Tools & Resources
LinkedIn, Industry conferences (e.g., AI India, Data Science Congress), Departmental seminars
Career Connection
Expands your professional circle, opening doors to unadvertised opportunities and valuable career guidance.
Advanced Stage
Excel in Project Work and Thesis- (Semester 3-4)
Your ''''Project Work - Phase I & II'''' (CS2304, CS2401) is the culmination of your M.Tech. Choose a challenging and relevant research problem, deliver a high-quality solution, and meticulously document your findings. A strong thesis can be a major differentiator in placements or Ph.D. admissions.
Tools & Resources
LaTeX for thesis writing, Mendeley/Zotero for referencing, Domain-specific software tools, Faculty mentors
Career Connection
Showcases your advanced technical and research capabilities, directly impacting your employability in R&D or senior roles.
Intensive Placement Preparation- (Semester 3-4)
Start rigorous preparation for placements well in advance. This includes mock interviews (technical and HR), aptitude test practice, resume building, and refining communication skills. Utilize SRMIST''''s career services and alumni network for guidance specific to Indian recruiters.
Tools & Resources
Aptitude test books (e.g., R.S. Aggarwal), InterviewBit, Glassdoor for company-specific interview questions, SRMIST Placement Cell
Career Connection
Directly prepares you for the competitive Indian job market, maximizing your chances of securing a desirable placement.
Contribute to Open Source Projects- (Semester 3-4)
Engage with relevant open-source projects in your area of specialization (e.g., TensorFlow, PyTorch, Kubernetes). Contributing to real-world codebases demonstrates practical skills, collaboration abilities, and proficiency with version control, highly valued by tech companies in India.
Tools & Resources
GitHub, GitLab, Online communities (Stack Overflow, Reddit), Specific project documentation
Career Connection
Builds a public portfolio, demonstrates practical coding skills, and showcases your ability to work in a team environment.
Program Structure and Curriculum
Eligibility:
- A pass in B.E / B.Tech or equivalent Degree with 50% in Computer Science and Engineering / Computer Engineering / Information Technology / Software Engineering / Electrical and Electronics Engineering / Electronics and Communication Engineering / Electronics and Instrumentation Engineering / Information and Communication Technology / Telecommunication Engineering / Mechatronics Engineering, or MCA, or M.Sc in Computer Science / Information Technology / Software Engineering / Data Science or equivalent from a recognized university.
Duration: 4 semesters / 2 years
Credits: 76 Credits
Assessment: Internal: 50%, External: 50%
Semester-wise Curriculum Table
Semester 1
| Subject Code | Subject Name | Subject Type | Credits | Key Topics |
|---|---|---|---|---|
| RM2101 | Research Methodology and IPR | Core | 4 | Research Problem Formulation, Research Design, Data Collection Methods, Data Analysis Techniques, Intellectual Property Rights |
| CS2101 | Advanced Data Structures and Algorithms | Core | 4 | Advanced Tree Structures, Graph Algorithms, Dynamic Programming, Amortized Analysis, Geometric Algorithms |
| CS2102 | Advanced Computer Architecture | Core | 4 | Pipelining and ILP, Memory Hierarchy, Multiprocessors and Cache Coherence, Vector Processors, GPU Architecture |
| CS2103 | Advanced Operating Systems | Core | 4 | Distributed Operating Systems, Process Synchronization, Distributed File Systems, Security in OS, Virtualization and Cloud OS |
| CS21E1 | Wireless and Mobile Networks | Professional Elective | 3 | Wireless Transmission, Mobile Network Layer, Mobile Transport Layer, Mobile Ad-hoc Networks, Wireless Application Protocol |
| CS21E2 | Digital Image Processing | Professional Elective | 3 | Image Fundamentals, Image Enhancement, Image Restoration, Image Segmentation, Image Compression |
| CS21E3 | Soft Computing | Professional Elective | 3 | Fuzzy Logic Systems, Artificial Neural Networks, Genetic Algorithms, Hybrid Soft Computing, Rough Sets |
| CS21E4 | Quantum Computing | Professional Elective | 3 | Quantum Mechanics Basics, Qubits and Quantum Gates, Quantum Algorithms, Quantum Cryptography, Quantum Error Correction |
| CS2107 | Advanced Data Structures and Algorithms Lab | Lab | 2 | Implementation of Trees, Graph Algorithms, Hashing Techniques, Dynamic Programming Solutions, Amortized Analysis Examples |
| CS2108 | Advanced Operating Systems Lab | Lab | 2 | OS System Calls, Process Synchronization, Inter-process Communication, Distributed System Concepts, Virtual Machine Management |
Semester 2
| Subject Code | Subject Name | Subject Type | Credits | Key Topics |
|---|---|---|---|---|
| CS2201 | Machine Learning | Core | 4 | Supervised Learning Models, Unsupervised Learning Techniques, Deep Learning Fundamentals, Reinforcement Learning, Model Evaluation and Tuning |
| CS2202 | Advanced Database Management Systems | Core | 4 | Distributed Databases, Object-Oriented Databases, Data Warehousing and OLAP, NoSQL Databases, Query Processing and Optimization |
| CS22E1 | Cryptography and Network Security | Professional Elective | 3 | Classical Encryption Techniques, Public Key Cryptography, Hash Functions and Digital Signatures, Network Security Applications, System Security |
| CS22E2 | Data Analytics | Professional Elective | 3 | Data Preprocessing, Statistical Methods for Analytics, Predictive Modeling, Big Data Technologies, Data Visualization |
| CS22E3 | Cloud Computing | Professional Elective | 3 | Cloud Architecture and Models, Virtualization, Cloud Services (IaaS, PaaS, SaaS), Cloud Security, Cloud Management |
| CS22E4 | Natural Language Processing | Professional Elective | 3 | Text Preprocessing, Language Models, Part-of-Speech Tagging, Sentiment Analysis, Machine Translation |
| CS22E5 | Internet of Things | Professional Elective | 3 | IoT Architecture, Sensing and Actuation, Communication Protocols, IoT Platforms, Security and Privacy in IoT |
| CS22E6 | Distributed Systems | Professional Elective | 3 | Distributed System Architectures, Remote Procedure Calls, Distributed Consensus, Fault Tolerance, Distributed Transactions |
| CS22E7 | Web Technologies | Professional Elective | 3 | Web Servers and Clients, HTML5 and CSS3, JavaScript Frameworks, Server-Side Scripting, Web Security |
| CS22E8 | Bio-inspired Computing | Professional Elective | 3 | Neural Networks, Evolutionary Computation, Swarm Intelligence, Artificial Immune Systems, DNA Computing |
| CS2207 | Machine Learning Lab | Lab | 2 | Implementation of Supervised Algorithms, Unsupervised Clustering Techniques, Model Training and Evaluation, Data Preprocessing with Scikit-learn, Neural Network Implementation |
| CS2208 | Advanced Database Management Systems Lab | Lab | 2 | Advanced SQL Queries, NoSQL Database Operations, Distributed Database Configuration, Data Warehousing Tools, Query Optimization Techniques |
| CS2209 | Mini Project with Seminar | Project | 2 | Problem Identification, Literature Survey, System Design, Implementation and Testing, Technical Presentation |
Semester 3
| Subject Code | Subject Name | Subject Type | Credits | Key Topics |
|---|---|---|---|---|
| CS23E1 | Big Data Technologies | Professional Elective | 3 | Hadoop Ecosystem, MapReduce Programming, Apache Spark, Data Stream Processing, NoSQL for Big Data |
| CS23E2 | Deep Learning | Professional Elective | 3 | Neural Network Architectures, Convolutional Neural Networks (CNN), Recurrent Neural Networks (RNN), Generative Adversarial Networks (GAN), Deep Reinforcement Learning |
| CS23E3 | Blockchain Technologies | Professional Elective | 3 | Cryptography for Blockchain, Distributed Ledger Technology, Smart Contracts, Consensus Mechanisms, Decentralized Applications (DApps) |
| CS23E4 | Cyber Forensics | Professional Elective | 3 | Digital Evidence Collection, Investigation Process, Network Forensics, Mobile Device Forensics, Legal and Ethical Aspects |
| CS23E5 | Augmented and Virtual Reality | Professional Elective | 3 | AR/VR Devices and Displays, 3D Graphics Fundamentals, Interaction Techniques, Tracking and Sensing, AR/VR Applications |
| CS23E6 | Human Computer Interaction | Professional Elective | 3 | User Centered Design Principles, Usability Engineering, Interaction Models, Evaluation Techniques, UI Prototyping |
| CS23E7 | Computer Vision | Professional Elective | 3 | Image Formation and Representation, Feature Detection and Extraction, Object Recognition, Motion Analysis, 3D Reconstruction |
| CS23E8 | Compiler Design | Professional Elective | 3 | Lexical Analysis, Syntax Analysis (Parsing), Semantic Analysis, Intermediate Code Generation, Code Optimization |
| CS23E9 | Data Mining | Professional Elective | 3 | Data Preprocessing, Association Rule Mining, Classification Techniques, Clustering Algorithms, Anomaly Detection |
| CS23EA | Software Defined Networks | Professional Elective | 3 | SDN Architecture, OpenFlow Protocol, Network Virtualization, Network Function Virtualization (NFV), SDN Security |
| CS23EB | Information Retrieval | Professional Elective | 3 | Text Indexing, Query Processing, Ranking Models, Evaluation Metrics, Web Search |
| CS23EC | Game Theory | Professional Elective | 3 | Strategic Form Games, Extensive Form Games, Nash Equilibrium, Cooperative Games, Mechanism Design |
| CS2304 | Project Work - Phase I | Project | 6 | Problem Identification and Definition, Extensive Literature Review, Project Proposal Development, Initial System Design, Methodology and Tools Selection |
Semester 4
| Subject Code | Subject Name | Subject Type | Credits | Key Topics |
|---|---|---|---|---|
| CS2401 | Project Work - Phase II | Project | 18 | System Implementation and Development, Testing and Debugging, Performance Evaluation and Optimization, Thesis Writing and Documentation, Project Defense and Presentation |
