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MTECH in Information Technology at Sant Gadge Baba Amravati University
Amravati, Maharashtra
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About the Specialization
What is Information Technology at Sant Gadge Baba Amravati University Amravati?
This MTech Information Technology program at Sant Gadge Baba Amravati University focuses on advanced concepts and research in cutting-edge IT domains. It equips students with expertise in areas like advanced data structures, mobile computing, cloud technologies, and soft computing, addressing the critical demand for highly skilled IT professionals in the Indian industry. The program emphasizes both theoretical foundations and practical application, preparing graduates for complex roles.
Who Should Apply?
This program is ideal for engineering graduates (B.E./B.Tech in CS/IT/Electronics) or MCA/M.Sc. (CS/IT) holders seeking to deepen their technical knowledge and specialize in advanced IT fields. It''''s suitable for fresh graduates aiming for R&D roles or senior technical positions, as well as working professionals looking to upskill in emerging technologies like AI/ML, IoT, and Big Data for career advancement in the Indian tech sector.
Why Choose This Course?
Graduates of this program can expect to pursue advanced careers as Software Architects, Data Scientists, AI/ML Engineers, Cloud Solution Architects, or Cybersecurity Analysts in leading Indian and multinational companies. Entry-level salaries typically range from INR 6-10 LPA, with experienced professionals earning significantly more. The program aligns with certifications in cloud platforms, data science, and cybersecurity, enhancing professional growth trajectories in India''''s booming digital economy.
Student Success Practices
Foundation Stage
Master Core Algorithms & Data Structures- (Semester 1-2)
Dedicate significant time to thoroughly understand and implement advanced data structures (e.g., AVL trees, Red-Black trees) and complex algorithms (e.g., graph traversal, dynamic programming). This foundational strength is crucial for solving real-world computational problems.
Tools & Resources
HackerRank, LeetCode, GeeksforGeeks, Competitive Programming Platforms
Career Connection
Strong algorithmic thinking is a primary requirement for top tech companies (e.g., TCS, Infosys, Wipro, product-based companies) and R&D roles in India, directly impacting placement success in coding rounds.
Build Proficiency in Network & System Fundamentals- (Semester 1-2)
Complement coursework in Advanced Computer Architecture, Wireless Ad-hoc Networks, and Distributed Operating Systems with hands-on labs and personal projects. Focus on understanding network protocols, distributed system concepts, and OS internals through simulations and mini-implementations.
Tools & Resources
Wireshark, NS2/NS3 Simulators, Linux System Programming, Virtualization Tools (VirtualBox, VMware)
Career Connection
Essential for roles in network engineering, system administration, cloud infrastructure management, and cybersecurity, which are highly sought after in Indian IT service and product companies.
Develop Practical Skills in Database & Mobile App Development- (Semester 1-2)
Go beyond theoretical knowledge of Advanced DBMS by actively working with different database types (NoSQL, Distributed DBs) and applying mobile computing principles to build functional applications. Participate in hackathons focused on mobile and database challenges.
Tools & Resources
MongoDB, Cassandra, Oracle, MySQL, Android Studio, Flutter, React Native
Career Connection
Opens doors to roles as Database Administrators, Backend Developers, and Mobile Application Developers, with high demand in India''''s digital transformation and startup ecosystem.
Intermediate Stage
Specialize through Elective Exploration & Research- (Semester 3)
Deep dive into your chosen elective (e.g., Cyber Security, Cloud Computing, IoT, Deep Learning, Big Data Analytics). Actively engage in research methodology, identify a research problem related to your specialization, and start preliminary work for your Dissertation Stage-I.
Tools & Resources
Research Papers (IEEE Xplore, ACM Digital Library), Python/R for Data Analytics, AWS/Azure/GCP Free Tiers, Relevant Development Frameworks (TensorFlow, Keras)
Career Connection
Direct path to advanced roles like Data Scientist, Cloud Architect, Cybersecurity Engineer, or AI/ML Specialist. It also prepares for PhD programs or R&D positions in India.
Initiate Dissertation with Industry Relevance- (Semester 3)
For Dissertation Stage-I, aim to select a project topic that addresses a current industry problem or leverages an emerging technology. Seek guidance from faculty and, if possible, collaborate with industry mentors to ensure your research has practical applicability and relevance.
Tools & Resources
Project Management Tools (Jira, Trello), Collaboration Platforms (GitHub), Domain-Specific Software/APIs
Career Connection
A well-executed, industry-relevant dissertation significantly boosts placement chances by demonstrating problem-solving skills and practical expertise to potential employers in India.
Attend Workshops & Network with Professionals- (Semester 3)
Participate in university-organized workshops, national/international conferences (even virtual ones), and tech meetups. Network with professionals, alumni, and guest speakers to gain insights into industry trends and potential job opportunities.
Tools & Resources
LinkedIn, Professional Body Memberships (e.g., CSI, ACM Student Chapters), Event Platforms (Eventbrite, Meetup)
Career Connection
Builds professional connections for internships and job referrals, provides exposure to industry best practices, and helps in understanding specific company requirements for job roles in India.
Advanced Stage
Complete High-Impact Dissertation & Publish- (Semester 4)
Focus intensely on completing Dissertation Stage-II. Ensure rigorous implementation, thorough analysis, and comprehensive thesis writing. Aim to publish your research findings in a reputable conference or journal, even if it''''s a student workshop or national conference.
Tools & Resources
LaTeX for Thesis Writing, Academic Databases, Plagiarism Checkers, University Research Support
Career Connection
A published paper adds significant weight to your resume, showcasing research capabilities and innovation, highly valued by R&D departments, startups, and academic institutions in India.
Prepare for Placements with Mock Interviews & Aptitude Tests- (Semester 4)
Actively prepare for technical interviews by solving coding problems, revising core computer science concepts, and practicing behavioral questions. Participate in mock interviews conducted by the university placement cell or external training programs. Strengthen aptitude and logical reasoning skills.
Tools & Resources
InterviewBit, LeetCode, GeeksforGeeks, IndiaBix, University Placement Cell Resources
Career Connection
Direct preparation for placement drives by major recruiters (e.g., Cognizant, Infosys, IBM, Capgemini) in India, increasing the likelihood of securing a desirable job offer upon graduation.
Build a Professional Portfolio & Online Presence- (Semester 4)
Compile all major projects, research work, and certifications into a well-structured online portfolio (e.g., GitHub, personal website). Optimize your LinkedIn profile, showcasing your skills, achievements, and career aspirations to attract potential employers.
Tools & Resources
GitHub, GitLab, Personal Website Builders (WordPress, Google Sites), LinkedIn
Career Connection
A strong portfolio and professional online presence are crucial for demonstrating practical skills and attracting recruiters, especially in a competitive job market like India, setting you apart from other candidates.
Program Structure and Curriculum
Eligibility:
- B.E. (Computer Sci. & Engg. /Information Tech./Instrumentation/Electronics/Elect. Power System/Electronic & Telecommunication Engg.) or MCA / M.Sc. (Computer Sci. / Information Tech. / Computer Application) with minimum 50% marks in aggregate (45% for backward class categories) (as per 2023-24 prospectus, generally applicable)
Duration: 4 semesters / 2 years
Credits: 86 Credits
Assessment: Internal: 20% (for theory), 50% (for practicals/project), External: 80% (for theory), 50% (for practicals/project)
Semester-wise Curriculum Table
Semester 1
| Subject Code | Subject Name | Subject Type | Credits | Key Topics |
|---|---|---|---|---|
| MIT101 | Advanced Computer Architecture | Core | 4 | Pipeline Architecture, Instruction Level Parallelism, Multiprocessors and Parallel Processing, Memory Hierarchy and Cache Coherence, Interconnection Networks and Clusters |
| MIT102 | Advanced Data Structures and Algorithm | Core | 4 | Advanced Tree Structures (AVL, Red-Black Trees), Graph Algorithms and Network Flow, Hashing and Amortized Analysis, Dynamic Programming and Greedy Algorithms, NP-completeness and Approximation Algorithms |
| MIT103 | Wireless Ad-hoc Networks | Core | 4 | Ad-hoc Network Characteristics and Applications, MAC Protocols for Ad-hoc Networks, Routing Protocols (AODV, DSR, OLSR), Transport Layer and QoS Issues, Security in Ad-hoc Networks |
| MIT104 | Digital Image Processing | Core | 4 | Image Fundamentals and Sensing, Image Enhancement in Spatial and Frequency Domains, Image Restoration and Filtering, Image Compression Techniques, Morphological Image Processing and Segmentation |
| MIT105 | Lab-I (ADS & A) | Lab | 2 | Implementation of Advanced Data Structures, Graph Algorithms Implementation, Dynamic Programming Problem Solving, Algorithm Analysis and Performance Evaluation |
| MIT106 | Lab-II (Wireless Ad-hoc & DIP) | Lab | 2 | Simulation of Wireless Ad-hoc Networks, Implementation of MAC and Routing Protocols, Digital Image Processing Techniques using Tools, Image Enhancement and Segmentation Practical |
| MIT107 | Seminar-I | Project/Seminar | 2 | Research Topic Selection and Literature Review, Technical Presentation Skills, Report Writing and Documentation, Critical Analysis of Research Papers |
Semester 2
| Subject Code | Subject Name | Subject Type | Credits | Key Topics |
|---|---|---|---|---|
| MIT201 | Distributed Operating System | Core | 4 | Distributed System Architectures, Message Passing and Remote Procedure Call, Distributed Shared Memory and Consistency Models, Distributed File Systems and Clock Synchronization, Distributed Deadlock Detection and Recovery |
| MIT202 | Advanced Database Management System | Core | 4 | Distributed Database Systems, Object-Oriented and Object-Relational Databases, XML Databases and Data Warehousing, Data Mining Concepts and Techniques, Big Data Fundamentals and NoSQL Databases |
| MIT203 | Mobile Computing | Core | 4 | Mobile Computing Architecture, Wireless Technologies (GSM, GPRS, CDMA, 3G, 4G), Mobile IP and Wireless Application Protocol (WAP), Mobile Operating Systems and Platforms, Mobile Application Development Concepts |
| MIT204 | Elective-I (Human Computer Interaction) | Elective | 4 | HCI Foundations and Design Principles, Usability Engineering and User-Centered Design, Interaction Design Process and Models, Interface Design and Evaluation Techniques, Cognitive Aspects of HCI |
| MIT204-2 | Elective-I (Cyber Security) | Elective | 4 | Security Fundamentals and Threat Landscape, Cryptography and Network Security Protocols, Web Application Security and Vulnerabilities, Intrusion Detection and Prevention Systems, Cyber Law and Ethical Hacking Principles |
| MIT204-3 | Elective-I (Cloud Computing) | Elective | 4 | Cloud Computing Architecture and Deployment Models, Virtualization Technologies, Cloud Service Models (IaaS, PaaS, SaaS), Cloud Security Challenges and Solutions, Cloud Platforms and Management |
| MIT204-4 | Elective-I (Data Analytics) | Elective | 4 | Data Preprocessing and Exploration, Statistical Methods for Data Analysis, Regression and Classification Techniques, Clustering Algorithms and Association Rules, Big Data Analytics Tools and Ecosystem |
| MIT205 | Lab-III (A-DBMS) | Lab | 2 | Distributed Database Implementation, Object-Oriented Database Concepts, Data Warehousing Queries and OLAP, Data Mining Tool Usage (e.g., Weka), NoSQL Database Operations |
| MIT206 | Lab-IV (Mobile Comp. & Elective-I) | Lab | 2 | Mobile Application Development (Android/iOS Basics), Wireless Communication Simulation, Practicals based on chosen Elective-I (HCI/Cyber Security/Cloud/Data Analytics), Security Tools Usage or Cloud Platform Services |
| MIT207 | Seminar-II | Project/Seminar | 2 | Advanced Research Topic Presentation, Project Proposal Development, Advanced Technical Communication, Literature Review and Problem Definition |
Semester 3
| Subject Code | Subject Name | Subject Type | Credits | Key Topics |
|---|---|---|---|---|
| MIT301 | Soft Computing | Core | 4 | Fuzzy Logic and Fuzzy Set Theory, Artificial Neural Networks Architectures, Genetic Algorithms and Evolutionary Computing, Hybrid Systems (Neuro-Fuzzy, Genetic-Neural), Applications of Soft Computing Techniques |
| MIT302-1 | Elective-II (Internet of Things) | Elective | 4 | IoT Architecture and Components, Sensors, Actuators and Microcontrollers for IoT, IoT Protocols (MQTT, CoAP, HTTP), Data Analytics and Cloud Integration in IoT, IoT Security and Privacy |
| MIT302-2 | Elective-II (Deep Learning) | Elective | 4 | Neural Network Fundamentals and Backpropagation, Convolutional Neural Networks (CNNs), Recurrent Neural Networks (RNNs) and LSTMs, Autoencoders and Generative Adversarial Networks (GANs), Deep Learning Frameworks (TensorFlow, Keras, PyTorch) |
| MIT302-3 | Elective-II (Big Data Analytics) | Elective | 4 | Hadoop Ecosystem and MapReduce, HDFS (Hadoop Distributed File System), Apache Spark for Big Data Processing, NoSQL Databases for Big Data, Stream Processing with Kafka and Storm |
| MIT302-4 | Elective-II (Software Testing and Quality Assurance) | Elective | 4 | Software Testing Principles and Life Cycle, Test Plan, Test Case Design and Execution, Black Box Testing Techniques, White Box Testing and Code Coverage, Software Quality Metrics and Assurance Standards |
| MIT303 | Research Methodology | Core | 4 | Research Problem Formulation and Objective Setting, Literature Survey and Gap Analysis, Research Design and Methodologies, Data Collection, Analysis and Interpretation, Research Report Writing and Ethical Considerations |
| MIT304 | Lab-V (Soft Computing & Elective-II) | Lab | 2 | Implementation of Fuzzy Logic Systems, Neural Network Training and Evaluation, Genetic Algorithm Application Development, Practicals based on chosen Elective-II, IoT device programming or Deep Learning model building |
| MIT305 | Dissertation Stage-I | Project/Dissertation | 8 | Problem Identification and Scope Definition, In-depth Literature Review, Methodology Design and Experimental Setup, Preliminary Results and Analysis, Dissertation Proposal and Presentation |
Semester 4
| Subject Code | Subject Name | Subject Type | Credits | Key Topics |
|---|---|---|---|---|
| MIT401 | Dissertation Stage-II | Project/Dissertation | 20 | Full System Implementation and Development, Extensive Experimentation and Data Analysis, Result Validation and Interpretation, Comprehensive Thesis Writing and Documentation, Final Presentation and Viva-Voce Examination |
