.png&w=1920&q=75)
M-TECH in Advanced Computing at Maulana Azad National Institute of Technology, Bhopal
Bhopal, Madhya Pradesh
.png&w=1920&q=75)
About the Specialization
What is Advanced Computing at Maulana Azad National Institute of Technology, Bhopal Bhopal?
This M.Tech Advanced Computing program at Maulana Azad National Institute of Technology Bhopal focuses on cutting-edge domains like Artificial Intelligence, Machine Learning, Cloud Computing, and Big Data Analytics. It aims to equip students with theoretical knowledge and practical skills crucial for India''''s rapidly evolving digital economy. The program emphasizes innovative problem-solving, preparing graduates for advanced roles in research and development within the Indian tech industry.
Who Should Apply?
This program is ideal for engineering graduates with a B.E./B.Tech in Computer Science, Information Technology, or a related discipline, possessing a valid GATE score. It caters to fresh graduates aspiring to make significant contributions in core computing fields and working professionals seeking to enhance their expertise in advanced computational technologies to meet growing industry demands in India.
Why Choose This Course?
Graduates of this program can expect to pursue high-demand careers as AI/ML Engineers, Data Scientists, Cloud Architects, and Research Engineers in top Indian and multinational companies. Entry-level salaries typically range from INR 6-12 LPA, with substantial growth potential for experienced professionals. The curriculum also prepares students for further academic pursuits like PhDs and for obtaining industry certifications relevant to the Indian IT sector.
Student Success Practices
Foundation Stage
Master Core Algorithms and Data Structures- (Semester 1-2)
Dedicate consistent effort to practicing advanced algorithms and complex data structures using platforms like LeetCode, HackerRank, and GeeksforGeeks. This solidifies foundational problem-solving skills critical for technical interviews in top Indian product and service-based companies.
Tools & Resources
LeetCode, HackerRank, GeeksforGeeks, C++/Python IDEs
Career Connection
Strong algorithmic thinking is a non-negotiable for securing high-paying roles as a Software Development Engineer or Data Scientist in India.
Engage Actively in Labs and Minor Projects- (Semester 1-2)
Go beyond assigned lab tasks by exploring extensions and building small, self-initiated projects in areas like network programming or database design. Document code meticulously using Git and participate in departmental coding competitions to refine practical skills.
Tools & Resources
GitHub, Bitbucket, Visual Studio Code, Jupyter Notebooks, Competitive Programming Platforms
Career Connection
Practical project experience and a visible code portfolio on GitHub significantly enhance employability for developer and analyst roles.
Develop Research Acumen Early- (Semester 1-2)
Collaborate with faculty on minor research problems or literature reviews, even before the major project phase. Explore academic databases like IEEE Xplore, ACM Digital Library, and NPTEL research courses to understand current trends and formulate potential research ideas.
Tools & Resources
IEEE Xplore, ACM Digital Library, Google Scholar, Mendeley/Zotero, NPTEL
Career Connection
Cultivates critical thinking for innovation-driven roles and provides a strong base for pursuing PhDs or R&D positions in India.
Intermediate Stage
Specialize through Electives and Advanced Projects- (Semester 3)
Choose electives strategically based on career aspirations (e.g., Deep Learning, Big Data Analytics). Complement coursework with advanced projects, perhaps participating in Kaggle challenges for data science or developing a cloud-native application using AWS/Azure free tiers.
Tools & Resources
Kaggle, AWS Free Tier, Microsoft Azure Student Account, TensorFlow, PyTorch
Career Connection
Demonstrates specialized skills highly valued by companies recruiting for AI/ML, Cloud, and Data Engineering roles.
Seek Quality Internships and Industry Exposure- (Semester 3 (during summer/winter breaks))
Actively apply for internships at reputed Indian tech companies, startups, or research labs. Utilize the college''''s placement cell, LinkedIn, and professional networking events. A strong internship often converts into a Pre-Placement Offer (PPO), a common pathway to jobs in India.
Tools & Resources
LinkedIn, Internshala, College Placement Portal, Industry Meetups
Career Connection
Real-world experience and industry connections are invaluable for placements and understanding corporate culture in India.
Build a Professional Network- (Semester 3)
Attend webinars, workshops, and conferences (virtual or local) focused on advanced computing. Connect with alumni, industry experts, and peers on LinkedIn. Participate in hackathons or tech competitions to collaborate and showcase skills, expanding professional circles.
Tools & Resources
LinkedIn, Meetup.com, Devfolio, Major Tech Conference Websites (e.g., AI Summit India)
Career Connection
Networking opens doors to mentorship, job opportunities, and staying updated with industry trends in the competitive Indian market.
Advanced Stage
Excel in Major Project and Research Publication- (Semester 4)
Treat Major Project Phase II as a capstone, aiming for a robust, innovative solution with potential for publication in national/international conferences (e.g., IEEE India, Springer). Focus on meticulous documentation, testing, and presenting the research effectively.
Tools & Resources
LaTeX, Overleaf, Mendeley/Zotero, Researchgate, Academic Journals/Conferences
Career Connection
A high-quality project and publication significantly boosts credibility for R&D roles, academic positions, or as a strong differentiator in placements.
Intensive Placement Preparation and Mock Interviews- (Semester 4)
Engage in rigorous placement preparation covering aptitude, technical coding, and HR rounds. Leverage the college''''s career services for mock interviews, group discussions, and resume reviews. Practice scenario-based questions relevant to the Indian tech job market.
Tools & Resources
InterviewBit, GeeksforGeeks Interview Prep, Mock Interview Platforms, College Placement Cell
Career Connection
Essential for converting technical skills into successful job offers from dream companies during campus placements.
Continuous Skill Upgradation and Soft Skills- (Semester 4 and beyond)
Beyond academics, commit to continuous learning through MOOCs (Coursera, edX, NPTEL) on emerging technologies like Ethical AI or Quantum Machine Learning. Simultaneously, hone presentation, communication, and teamwork skills, which are highly valued by Indian employers for leadership and client-facing roles.
Tools & Resources
Coursera, edX, NPTEL, Toastmasters (if available), Professional Development Workshops
Career Connection
Ensures long-term career growth, adaptability, and leadership potential in a dynamic industry.
Program Structure and Curriculum
Eligibility:
- B.E./B.Tech. or equivalent degree in relevant discipline (e.g., Computer Science & Engineering/Information Technology) with minimum 60% marks or 6.5 CGPA on a 10-point scale, and a valid GATE score. (Based on general M.Tech admission criteria at MANIT Bhopal)
Duration: 4 semesters
Credits: 67 Credits
Assessment: Internal: 50%, External: 50%
Semester-wise Curriculum Table
Semester 1
| Subject Code | Subject Name | Subject Type | Credits | Key Topics |
|---|---|---|---|---|
| CSN-101 | Advanced Data Structures & Algorithms | Core | 3 | Data Structures (Trees, Graphs, Heaps), Hashing Techniques, Algorithm Design Paradigms (Dynamic Programming, Greedy), Graph Algorithms (BFS, DFS, Shortest Paths), NP-Hard and NP-Complete Problems |
| CSN-102 | Advanced Computer Networks | Core | 3 | Network Architectures and Protocols, Data Link and Medium Access Control, Routing Protocols (OSPF, BGP), Transport Layer (TCP, UDP, Congestion Control), Network Security and Application Layer Protocols |
| CSN-103 | Advanced Database Management Systems | Core | 3 | Relational Database Design, Query Processing and Optimization, Transaction Management (ACID properties, Concurrency Control), Database Recovery Techniques, Distributed Databases and NoSQL Concepts |
| CSN-104 | Research Methodology | Core | 2 | Research Problem Formulation, Research Design and Methods, Data Collection and Analysis Techniques, Hypothesis Testing and Statistical Inference, Technical Report Writing and Research Ethics |
| CSN-105 | Advanced Data Structures & Algorithms Lab | Lab | 2 | Implementation of Trees and Graphs, Sorting and Searching Algorithms, Dynamic Programming Solutions, Hashing and Priority Queues, Algorithm Analysis and Profiling |
| CSN-106 | Advanced Computer Networks Lab | Lab | 2 | Network Simulation Tools (NS2/NS3), Socket Programming in C/Python, Network Protocol Implementation, Packet Sniffing and Analysis, Network Configuration and Troubleshooting |
| CSN-107 | Advanced Database Management Systems Lab | Lab | 2 | Advanced SQL Queries and Optimization, Database Schema Design and Normalization, PL/SQL Programming for Stored Procedures, Transaction Management Scenarios, Introduction to NoSQL Database Operations |
| CSN-108 | Seminar - I | Seminar | 1 | Literature Review Techniques, Technical Presentation Skills, Scientific Writing for Research Papers, Identifying Research Gaps, Effective Communication of Technical Ideas |
Semester 2
| Subject Code | Subject Name | Subject Type | Credits | Key Topics |
|---|---|---|---|---|
| CSN-201 | Machine Learning | Core | 3 | Supervised Learning (Regression, Classification), Unsupervised Learning (Clustering, PCA), Neural Networks and Deep Learning Basics, Ensemble Methods (Bagging, Boosting), Model Evaluation and Hyperparameter Tuning |
| CSN-202 | Cloud Computing | Core | 3 | Cloud Computing Architectures, Service Models (IaaS, PaaS, SaaS), Deployment Models (Public, Private, Hybrid), Virtualization Technologies, Cloud Security and Big Data on Cloud |
| CSN-203 | Advance Programming Techniques | Core | 3 | Object-Oriented Programming Principles, Multithreading and Concurrency, Design Patterns (Creational, Structural, Behavioral), Memory Management and Garbage Collection, Performance Optimization and Debugging Techniques |
| CSN-204 A | Elective – I: Data Warehousing & Data Mining | Elective | 3 | Data Warehouse Architecture, OLAP Operations, Data Preprocessing, Association Rule Mining, Classification and Prediction |
| CSN-204 B | Elective – I: Soft Computing | Elective | 3 | Fuzzy Logic Systems, Neural Networks, Genetic Algorithms, Hybrid Soft Computing Techniques, Applications of Soft Computing |
| CSN-204 C | Elective – I: Distributed Systems | Elective | 3 | Distributed System Architectures, Interprocess Communication, Distributed Transactions and Concurrency Control, Distributed File Systems, Fault Tolerance and Replication |
| CSN-204 D | Elective – I: Digital Forensics | Elective | 3 | Introduction to Digital Forensics, Evidence Acquisition and Analysis, Network Forensics, Mobile Device Forensics, Legal Aspects of Digital Forensics |
| CSN-204 E | Elective – I: Compiler Design | Elective | 3 | Lexical Analysis, Syntax Analysis (Parsing), Semantic Analysis, Intermediate Code Generation, Code Optimization and Code Generation |
| CSN-204 F | Elective – I: Ad-Hoc & Sensor Networks | Elective | 3 | Ad-Hoc Network Routing Protocols, MAC Protocols for Ad-Hoc Networks, Sensor Network Architecture, Deployment and Localization, Security in Ad-Hoc and Sensor Networks |
| CSN-204 G | Elective – I: Quantum Computing | Elective | 3 | Quantum Mechanics Basics (Qubits, Superposition), Quantum Gates and Circuits, Quantum Algorithms (Shor''''s, Grover''''s), Quantum Cryptography, Quantum Error Correction |
| CSN-205 A | Elective – II: Parallel & Distributed Algorithms | Elective | 3 | Parallel Computing Models, Shared Memory and Distributed Memory, Parallel Sorting and Searching, Distributed Graph Algorithms, Performance Metrics for Parallel Algorithms |
| CSN-205 B | Elective – II: Internet of Things | Elective | 3 | IoT Architecture and Protocols, Sensors and Actuators, Edge Computing and Cloud Integration, IoT Security and Privacy, IoT Applications and Case Studies |
| CSN-205 C | Elective – II: Mobile Computing | Elective | 3 | Mobile Communication Systems (GSM, LTE), Mobile Ad-Hoc Networks (MANETs), Mobile IP and Wireless TCP, Location-Based Services, Mobile Application Development Concepts |
| CSN-205 D | Elective – II: Big Data Analytics | Elective | 3 | Big Data Characteristics and Challenges, Hadoop Ecosystem (HDFS, MapReduce), Spark for Big Data Processing, NoSQL Databases, Data Stream Analytics |
| CSN-205 E | Elective – II: Semantic Web | Elective | 3 | Web 3.0 and Semantic Web Vision, RDF and RDFS, Ontology Languages (OWL), Semantic Web Services, Knowledge Representation and Reasoning |
| CSN-205 F | Elective – II: Image Processing | Elective | 3 | Image Enhancement Techniques, Image Restoration, Image Compression, Segmentation and Feature Extraction, Morphological Image Processing |
| CSN-205 G | Elective – II: Augmented & Virtual Reality | Elective | 3 | Fundamentals of AR/VR, AR/VR Hardware and Software, 3D Graphics and Interaction Techniques, Tracking and Registration, Applications and Ethical Considerations |
| CSN-206 | Machine Learning Lab | Lab | 2 | Python Libraries for ML (Scikit-learn, Pandas), Implementation of Supervised Learning Algorithms, Unsupervised Learning Techniques, Introduction to TensorFlow/Keras, Model Evaluation and Cross-Validation |
| CSN-207 | Cloud Computing Lab | Lab | 2 | Virtual Machine Deployment on Cloud Platforms, Cloud Storage Services (S3, Blob Storage), Serverless Computing (Lambda, Azure Functions), Containerization with Docker and Kubernetes Basics, Cloud Network Configuration and Security |
| CSN-208 | Advance Programming Techniques Lab | Lab | 2 | Object-Oriented Programming in Java/C++, Multithreading and Concurrency Control, Design Patterns Implementation, Exception Handling and Debugging, Developing Robust and Efficient Code |
| CSN-209 | Seminar - II | Seminar | 1 | In-depth Technical Literature Review, Advanced Presentation Techniques, Critical Analysis of Research Papers, Formulating Research Questions, Effective Public Speaking for Technical Topics |
Semester 3
| Subject Code | Subject Name | Subject Type | Credits | Key Topics |
|---|---|---|---|---|
| CSN-301 | Advanced Data Science | Core | 3 | Statistical Inference and Hypothesis Testing, Predictive Modeling and Time Series Analysis, Feature Engineering and Selection, Big Data Processing (Hadoop, Spark), A/B Testing and Experiment Design |
| CSN-302 A | Elective – III: Digital Image Processing | Elective | 3 | Image Acquisition and Representation, Image Enhancement and Restoration, Color Image Processing, Wavelets and Multi-resolution Processing, Image Compression and Segmentation |
| CSN-302 B | Elective – III: Natural Language Processing | Elective | 3 | Text Preprocessing and Tokenization, Syntactic and Semantic Analysis, Language Models and Word Embeddings, Text Classification and Sentiment Analysis, Machine Translation and Chatbots |
| CSN-302 C | Elective – III: Blockchain Technologies | Elective | 3 | Cryptographic Primitives (Hashing, Digital Signatures), Distributed Ledger Technologies, Consensus Algorithms (PoW, PoS), Smart Contracts and DApps, Blockchain Platforms (Ethereum, Hyperledger) |
| CSN-302 D | Elective – III: Pattern Recognition | Elective | 3 | Feature Extraction and Selection, Statistical Pattern Recognition, Neural Network Classifiers, Clustering Algorithms, Support Vector Machines |
| CSN-302 E | Elective – III: Cryptography and Network Security | Elective | 3 | Symmetric and Asymmetric Cryptography, Hash Functions and Digital Signatures, Key Management and Distribution, Network Security Protocols (SSL/TLS, IPsec), Firewalls and Intrusion Detection Systems |
| CSN-302 F | Elective – III: Deep Learning | Elective | 3 | Feedforward Neural Networks, Convolutional Neural Networks (CNNs), Recurrent Neural Networks (RNNs, LSTMs), Generative Adversarial Networks (GANs), Deep Learning Frameworks (PyTorch, TensorFlow) |
| CSN-302 G | Elective – III: Software Defined Networks | Elective | 3 | SDN Architecture and Components, OpenFlow Protocol, Network Virtualization, SDN Controllers (OpenDaylight, ONOS), SDN Applications and Use Cases |
| CSN-303 A | Elective – IV: Speech Processing | Elective | 3 | Speech Production and Perception, Speech Feature Extraction (MFCC, LPC), Speech Recognition Techniques (HMM, DNN), Speech Synthesis, Speaker Recognition |
| CSN-303 B | Elective – IV: Bio-Informatics | Elective | 3 | Biological Databases, Sequence Alignment (BLAST, FASTA), Phylogenetic Tree Construction, Protein Structure Prediction, Genomic Data Analysis |
| CSN-303 C | Elective – IV: Computer Vision | Elective | 3 | Image Formation and Camera Models, Feature Detection and Matching, Object Recognition and Detection, Motion Analysis and Tracking, 3D Reconstruction |
| CSN-303 D | Elective – IV: Human Computer Interaction | Elective | 3 | HCI Design Principles, Usability Engineering, User Interface Prototyping, Evaluation Techniques (Heuristic, User Testing), Interaction Styles and Paradigms |
| CSN-303 E | Elective – IV: Web Engineering | Elective | 3 | Web Application Architecture, Web Design and Development Frameworks, Web Security, Web Services and APIs, Performance Optimization for Web Applications |
| CSN-303 F | Elective – IV: Embedded Systems | Elective | 3 | Microcontrollers and Microprocessors, Embedded System Design, Real-Time Operating Systems, Sensors and Actuators, Interfacing and Communication Protocols |
| CSN-303 G | Elective – IV: Advanced Operating Systems | Elective | 3 | Distributed Operating Systems, Network Operating Systems, Real-Time Operating Systems, Process Synchronization and Deadlocks, Memory Management in Distributed Systems |
| CSN-304 | Major Project Phase – I | Project | 6 | Problem Identification and Scope Definition, Comprehensive Literature Survey, Methodology Design and Planning, Initial Implementation and Prototyping, Technical Report Writing and Presentation |
Semester 4
| Subject Code | Subject Name | Subject Type | Credits | Key Topics |
|---|---|---|---|---|
| CSN-401 | Major Project Phase – II | Project | 12 | Advanced System Implementation, Extensive Testing and Validation, Performance Analysis and Optimization, Thesis Writing and Documentation, Project Defense and Viva-Voce |
