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INTEGRATED-M-SC in Computer Science at Central University of Rajasthan
Ajmer, Rajasthan
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About the Specialization
What is Computer Science at Central University of Rajasthan Ajmer?
This Integrated M.Sc. Computer Science program at Central University of Rajasthan focuses on a comprehensive and evolving curriculum. It integrates foundational computer science principles with advanced specializations like AI, Machine Learning, Data Science, and Blockchain, reflecting the dynamic Indian IT industry. The program aims to equip students with theoretical knowledge and practical skills for cutting-edge technology domains, addressing the high demand for skilled professionals in India''''s digital transformation journey.
Who Should Apply?
This program is ideal for 10+2 graduates with a strong aptitude in Mathematics seeking a rigorous and extended academic journey into computer science. It caters to aspiring software developers, data scientists, AI/ML engineers, and cybersecurity experts who desire a holistic five-year curriculum. It is particularly suited for individuals aiming to build a solid foundation before specializing, ready to contribute to India''''s burgeoning tech and startup ecosystem.
Why Choose This Course?
Graduates of this program can expect diverse career paths in India, including roles such as Software Engineer, Data Analyst, AI/ML Specialist, Cybersecurity Analyst, and Cloud Solutions Architect. Entry-level salaries typically range from INR 4-8 lakhs per annum, with significant growth potential up to INR 15-25 lakhs or more for experienced professionals in top-tier companies. The curriculum prepares students for industry-recognized certifications and advanced studies, fostering continuous growth in the Indian IT sector.
Student Success Practices
Foundation Stage
Master Core Programming & Data Structures- (Semester 1-2)
Dedicate significant time in Semesters 1-2 to deeply understand C/C++ programming fundamentals and essential data structures. Practice extensively by solving problems on platforms like HackerRank, LeetCode, and GeeksforGeeks to build strong logical thinking and coding proficiency.
Tools & Resources
GeeksforGeeks, HackerRank, LeetCode, Online C++ Compilers
Career Connection
A strong grasp of these fundamentals is crucial for cracking coding rounds in placement interviews for software development roles in Indian tech companies.
Build a Solid Mathematical Foundation- (Semester 1-2)
Focus diligently on Discrete Mathematics, Probability, and Statistics. Utilize online courses from NPTEL or platforms like Khan Academy to supplement classroom learning. Engage in problem-solving groups with peers to strengthen understanding of theoretical concepts.
Tools & Resources
NPTEL courses, Khan Academy, Peer Study Groups
Career Connection
These mathematical skills are foundational for advanced computer science subjects like Machine Learning and Data Science, highly valued in analytics and AI roles in India.
Develop Effective Communication Skills- (Semester 1-2)
Actively participate in English Communication and Professional Ethics & Values courses. Join college clubs like Toastmasters or debating societies to improve public speaking and presentation skills. Practice technical writing for lab reports and assignments.
Tools & Resources
Toastmasters International (local chapters), College Debating Societies, Grammarly
Career Connection
Excellent communication is vital for presenting projects, collaborating in teams, and acing HR rounds in Indian companies, ensuring professional success.
Intermediate Stage
Engage in Project-Based Learning- (Semester 3-5)
Translate theoretical knowledge from courses like OS, DBMS, Web Technologies, and Machine Learning into practical projects. Participate in hackathons (e.g., Smart India Hackathon) or contribute to open-source projects on GitHub. Build a portfolio of small to medium-scale applications.
Tools & Resources
GitHub, Kaggle, Smart India Hackathon, Local Hackathons
Career Connection
Practical projects demonstrate application skills to recruiters and are essential for showcasing expertise during technical interviews for product and service-based companies.
Seek Early Industry Exposure via Internships- (Semester 3-5 (Summer breaks))
Actively search for summer internships after your 4th or 6th semester. Even short-term internships, virtual internships, or unpaid opportunities with startups in India can provide invaluable real-world experience, expose you to industry tools, and help build professional networks.
Tools & Resources
Internshala, LinkedIn, College Placement Cell
Career Connection
Internships are critical for gaining practical experience, making industry contacts, and often lead to pre-placement offers from Indian companies, significantly boosting career prospects.
Specialise in a Niche Area- (Semester 4-6)
Based on your interests in AI, Data Science, Cyber Security, or Cloud Computing, start taking relevant online courses or certifications from platforms like Coursera, Udemy, or NPTEL. Focus on one or two areas to build in-depth expertise through elective choices.
Tools & Resources
Coursera, Udemy, NPTEL, Certifications (e.g., Google Cloud, AWS, Microsoft Azure)
Career Connection
Specialized skills are highly sought after by Indian tech companies, leading to targeted job roles and potentially higher starting salaries in high-demand fields.
Advanced Stage
Undertake a Significant Final Year Project/Dissertation- (Semester 9-10)
Invest deeply in your Minor Project and Dissertation, focusing on a challenging, innovative problem. Aim for a solution with real-world applicability or publishable research potential. Collaborate with faculty or industry mentors to ensure high-quality output.
Tools & Resources
Research papers (IEEE, ACM), Academic Databases, Mentorship from Faculty/Industry
Career Connection
A strong final year project is a major talking point in interviews, demonstrating problem-solving ability, technical depth, and research acumen to potential employers in India and abroad.
Intensive Placement Preparation & Networking- (Semester 8-10)
Start rigorous preparation for placements well in advance. Practice aptitude tests, mock interviews (technical and HR), and group discussions. Network with alumni and industry professionals on LinkedIn, attending career fairs and technical seminars to explore opportunities.
Tools & Resources
Placement Training Modules, Mock Interview Platforms, LinkedIn, Alumni Network
Career Connection
This holistic preparation maximizes your chances of securing desirable placements in leading Indian IT companies, PSUs, or research organizations.
Develop Leadership & Professional Acumen- (Semester 7-9)
Take on leadership roles in student chapters of professional bodies (e.g., ACM, IEEE), organize workshops, or mentor junior students. Participate in technical seminars (CS-904) to hone presentation and critical thinking skills. Understand entrepreneurship concepts to consider startup ventures in India.
Tools & Resources
ACM/IEEE Student Chapters, Entrepreneurship Cells, Startup Incubation Centers
Career Connection
Leadership experience and professional acumen are highly valued by employers, indicating potential for growth into managerial or entrepreneurial roles within the Indian corporate landscape.
Program Structure and Curriculum
Eligibility:
- 10+2 with at least 50% marks or equivalent grade with Mathematics as one of the subjects from recognized board/university.
Duration: 10 semesters / 5 years
Credits: 223 Credits
Assessment: Internal: 40%, External: 60%
Semester-wise Curriculum Table
Semester 1
| Subject Code | Subject Name | Subject Type | Credits | Key Topics |
|---|---|---|---|---|
| GE-101 | Environmental Studies | Generic Elective Course | 3 | Concept of Environment and Ecosystem, Biodiversity and its Conservation, Environmental Pollution and Control, Social Issues and the Environment, Human Population and Environment, Field Work and Case Studies |
| GE-102 | Mathematics-I | Generic Elective Course | 3 | Calculus of Single Variable, Sequences and Series, Differential Equations, Vector Algebra, Matrices and Determinants, Linear Transformations |
| GE-103 | Physics-I | Generic Elective Course | 3 | Classical Mechanics, Oscillations and Waves, Optics and Wave Phenomena, Thermal Physics, Special Theory of Relativity, Quantum Mechanics Introduction |
| CS-101 | Introduction to Computer Science & Programming | Core Course | 3 | Computer Fundamentals, Problem Solving Techniques, Algorithms and Flowcharts, Introduction to C Programming, Data Types, Operators, Expressions, Control Structures and Functions |
| CS-102P | Computer Science & Programming Lab | Practical Course | 2 | Basic C Programming Exercises, Control Flow Implementation, Function Calls and Parameter Passing, Array and String Manipulations, Debugging and Testing, Basic Algorithm Implementation |
| CS-103 | Digital Electronics | Core Course | 3 | Number Systems and Codes, Boolean Algebra and Logic Gates, Combinational Logic Circuits, Sequential Logic Circuits, Registers and Counters, Memory and Programmable Logic |
| CS-104P | Digital Electronics Lab | Practical Course | 2 | Logic Gate Realization, Combinational Circuit Design, Sequential Circuit Implementation, Flip-Flops and Latches, Counters and Registers Experiments, Basic ALU Design |
| HS-101 | English Communication | Humanities & Social Science Course | 3 | Grammar and Vocabulary Building, Reading Comprehension Strategies, Written Communication Skills, Oral Communication and Presentation, Listening Skills, Non-Verbal Communication |
Semester 2
| Subject Code | Subject Name | Subject Type | Credits | Key Topics |
|---|---|---|---|---|
| GE-201 | Indian Culture & Heritage | Generic Elective Course | 3 | Ancient Indian Civilizations, Art, Architecture and Sculpture, Indian Philosophical Systems, Religious Traditions of India, Science and Technology in Ancient India, Cultural Diversity and Unity |
| GE-202 | Mathematics-II | Generic Elective Course | 3 | Multivariable Calculus, Vector Calculus, Linear Algebra and Eigenvalues, Complex Numbers and Functions, Laplace Transforms, Numerical Methods Introduction |
| GE-203 | Physics-II | Generic Elective Course | 3 | Electromagnetism and Maxwell''''s Equations, Semiconductor Physics, Solid State Physics, Nuclear Physics, Laser Physics, Applications of Modern Physics |
| CS-201 | Data Structures | Core Course | 3 | Introduction to Data Structures, Arrays, Linked Lists, Stacks, Queues, Trees and Binary Trees, Graphs and Graph Traversal, Sorting and Searching Algorithms, Hashing Techniques |
| CS-202P | Data Structures Lab | Practical Course | 2 | Implementation of Linked Lists, Stack and Queue Operations, Binary Tree Traversal, Graph Representation and Algorithms, Sorting and Searching Implementations, Hashing Applications |
| CS-203 | Object Oriented Programming with C++ | Core Course | 3 | Concepts of OOP, Classes and Objects, Inheritance and Polymorphism, Abstraction and Encapsulation, Constructors and Destructors, File Handling and Exception Handling |
| CS-204P | Object Oriented Programming Lab | Practical Course | 2 | Class and Object Creation, Implementation of Inheritance, Polymorphism using Virtual Functions, Operator Overloading, Template Programming, File I/O in C++ |
| HS-201 | Professional Ethics & Values | Humanities & Social Science Course | 3 | Ethical Theories and Principles, Professionalism and Integrity, Workplace Ethics, Moral Values and Decision Making, Corporate Social Responsibility, Cyber Ethics and Data Privacy |
Semester 3
| Subject Code | Subject Name | Subject Type | Credits | Key Topics |
|---|---|---|---|---|
| CS-301 | Discrete Mathematics | Core Course | 3 | Mathematical Logic and Proofs, Set Theory and Functions, Relations and Posets, Graph Theory Fundamentals, Combinatorics and Counting, Algebraic Structures |
| CS-302 | Computer Organization & Architecture | Core Course | 3 | Basic Computer Organization, CPU Design and Pipelining, Memory Hierarchy, Input/Output Organization, Instruction Set Architecture, Control Unit Design |
| CS-303 | Operating Systems | Core Course | 3 | Introduction to Operating Systems, Process Management and Scheduling, Memory Management Techniques, Virtual Memory and Paging, File Systems and I/O Management, Deadlocks and Concurrency Control |
| CS-304 | Database Management System | Core Course | 3 | Database System Architecture, Entity-Relationship Model, Relational Data Model and Algebra, SQL Query Language, Normalization and Dependencies, Transaction Management and Concurrency |
| CS-305P | Operating Systems Lab | Practical Course | 2 | Shell Scripting Exercises, Process Management using System Calls, CPU Scheduling Algorithms Implementation, Memory Allocation Strategies, File Management Operations, Inter-Process Communication |
| CS-306P | Database Management System Lab | Practical Course | 2 | SQL DDL and DML Commands, Advanced SQL Queries, Database Design and ER Diagrams, Stored Procedures and Functions, Trigger Implementation, Report Generation using SQL |
| CS-307 | Software Engineering | Core Course | 3 | Software Development Life Cycle Models, Requirements Engineering, Software Design Principles, Software Testing Techniques, Software Project Management, Software Quality Assurance |
| CS-308 | Data Communication & Networks | Core Course | 3 | Data Communication Fundamentals, Network Models (OSI, TCP/IP), Physical Layer and Data Link Layer, Network Layer: IP Addressing and Routing, Transport Layer Protocols (TCP, UDP), Application Layer Protocols |
Semester 4
| Subject Code | Subject Name | Subject Type | Credits | Key Topics |
|---|---|---|---|---|
| CS-401 | Design & Analysis of Algorithms | Core Course | 3 | Algorithm Analysis and Asymptotic Notation, Divide and Conquer Algorithms, Dynamic Programming, Greedy Algorithms, Graph Algorithms, NP-Completeness |
| CS-402 | Theory of Computation | Core Course | 3 | Finite Automata and Regular Expressions, Context-Free Grammars and Pushdown Automata, Turing Machines, Decidability and Undecidability, Chomsky Hierarchy, Computational Complexity Classes |
| CS-403 | Artificial Intelligence | Core Course | 3 | Introduction to AI and Intelligent Agents, Search Algorithms (Uninformed, Informed), Knowledge Representation, Logic Programming and AI Planning, Introduction to Machine Learning, Expert Systems and Fuzzy Logic |
| CS-404 | Web Technologies | Core Course | 3 | HTML5 and CSS3, JavaScript and DOM, Web Servers and Clients, Server-Side Scripting (PHP/Node.js concepts), Database Connectivity for Web, Web Security Fundamentals |
| CS-405P | Design & Analysis of Algorithms Lab | Practical Course | 2 | Implementation of Sorting Algorithms, Dynamic Programming Problems, Graph Traversal Algorithms, Greedy Algorithm Applications, Time and Space Complexity Analysis, Backtracking and Branch & Bound |
| CS-406P | Web Technologies Lab | Practical Course | 2 | Responsive Web Page Design, Client-Side Scripting with JavaScript, Server-Side Scripting Setup, Database Integration for Web Applications, AJAX and JSON Usage, Web Framework Introduction |
| CS-407 | Probability & Statistics | Core Course | 3 | Basic Probability Theory, Random Variables and Distributions, Joint and Conditional Probability, Hypothesis Testing, Regression and Correlation, ANOVA and Chi-Square Tests |
| CS-408 | Compiler Design | Core Course | 3 | Introduction to Compilers, Lexical Analysis, Syntax Analysis (Parsing), Semantic Analysis, Intermediate Code Generation, Code Optimization and Code Generation |
Semester 5
| Subject Code | Subject Name | Subject Type | Credits | Key Topics |
|---|---|---|---|---|
| CS-501 | Computer Graphics | Core Course | 3 | Graphics Hardware and Software, 2D and 3D Transformations, Clipping and Viewing, Color Models and Shading, Projection Techniques, Basic Animation Principles |
| CS-502 | Data Warehousing & Data Mining | Core Course | 3 | Data Warehousing Concepts, OLAP Operations, Data Mining Tasks, Classification Algorithms, Clustering Algorithms, Association Rule Mining |
| CS-503 | Machine Learning | Core Course | 3 | Introduction to Machine Learning, Supervised Learning (Regression, Classification), Unsupervised Learning (Clustering), Neural Networks Fundamentals, Support Vector Machines, Ensemble Methods |
| CS-504 | Cyber Security | Core Course | 3 | Fundamentals of Cryptography, Network Security Concepts, Web Application Security, Malware and Viruses, Firewalls and Intrusion Detection, Cyber Laws and Ethics |
| CS-505P | Computer Graphics Lab | Practical Course | 2 | OpenGL/Graphics Library Setup, 2D Drawing and Transformations, 3D Object Rendering, Clipping Algorithms Implementation, Simple Animation, Interactive Graphics Programming |
| CS-506P | Machine Learning Lab | Practical Course | 2 | Python for Machine Learning (Scikit-learn), Data Preprocessing and Feature Engineering, Implementing Regression Models, Implementing Classification Models, Clustering Algorithms, Neural Network Basics with Keras/TensorFlow |
| CS-CE-507(A) | Cloud Computing | Core Elective Course | 3 | Cloud Computing Concepts, Service Models (IaaS, PaaS, SaaS), Deployment Models (Public, Private, Hybrid), Virtualization Technology, Cloud Security, Cloud Platforms Overview (AWS, Azure, GCP) |
| CS-CE-507(B) | Distributed Systems | Core Elective Course | 3 | Introduction to Distributed Systems, Inter-Process Communication, Distributed File Systems, Concurrency Control, Fault Tolerance and Replication, Distributed Consensus |
| CS-CE-507(C) | High Performance Computing | Core Elective Course | 3 | Parallel Computing Architectures, Message Passing Interface (MPI), OpenMP for Shared Memory, GPU Programming (CUDA/OpenCL), Cluster and Grid Computing, Performance Evaluation |
| CS-OE-E1 | Open Elective-1 | Open Elective Course | 3 |
Semester 6
| Subject Code | Subject Name | Subject Type | Credits | Key Topics |
|---|---|---|---|---|
| CS-601 | Mobile Application Development | Core Course | 3 | Introduction to Mobile App Development (Android/iOS), UI/UX Design for Mobile, Activity Lifecycle and Intents, Data Storage and SQLite, Web Services and APIs, App Deployment and Monetization |
| CS-602 | Natural Language Processing | Core Course | 3 | NLP Fundamentals and Text Preprocessing, Language Models and N-grams, Part-of-Speech Tagging, Syntactic Parsing and Grammars, Sentiment Analysis and Text Classification, Machine Translation Introduction |
| CS-603 | Digital Image Processing | Core Course | 3 | Image Fundamentals and Representation, Image Enhancement Techniques, Image Restoration, Image Segmentation, Feature Extraction, Image Compression |
| CS-604 | Internet of Things | Core Course | 3 | IoT Architecture and Paradigms, Sensors, Actuators, and Microcontrollers, IoT Communication Protocols, Data Analytics for IoT, IoT Security and Privacy, Edge and Fog Computing in IoT |
| CS-605P | Mobile Application Development Lab | Practical Course | 2 | Android Studio/Xcode Setup, UI Layouts and Widgets, Event Handling and Listeners, Working with Databases, Consuming RESTful APIs, Building a Simple Mobile Application |
| CS-606P | Digital Image Processing Lab | Practical Course | 2 | Image Manipulation with Python/MATLAB, Image Filtering and Smoothing, Edge Detection Algorithms, Image Segmentation Techniques, Feature Extraction using OpenCV, Image Compression and Decompression |
| CS-CE-607(A) | Deep Learning | Core Elective Course | 3 | Introduction to Artificial Neural Networks, Deep Neural Networks Architectures, Convolutional Neural Networks (CNNs), Recurrent Neural Networks (RNNs), Optimization and Regularization, Deep Learning Frameworks (TensorFlow/PyTorch) |
| CS-CE-607(B) | Big Data Analytics | Core Elective Course | 3 | Introduction to Big Data, Hadoop Ecosystem (HDFS, MapReduce), Spark Framework, NoSQL Databases, Stream Processing, Big Data Visualization |
| CS-CE-607(C) | Ad-Hoc & Sensor Networks | Core Elective Course | 3 | Introduction to Ad-Hoc Networks, MANET Routing Protocols, Wireless Sensor Networks (WSN) Architecture, WSN MAC Protocols, Localization and Time Synchronization, Security in Ad-Hoc and Sensor Networks |
| CS-OE-E2 | Open Elective-2 | Open Elective Course | 3 |
Semester 7
| Subject Code | Subject Name | Subject Type | Credits | Key Topics |
|---|---|---|---|---|
| CS-701 | Data Science & Analytics | Core Course | 3 | Introduction to Data Science Workflow, Data Collection and Cleaning, Exploratory Data Analysis, Statistical Inference and Modeling, Predictive Analytics, Data Visualization Techniques |
| CS-702 | Computer Vision | Core Course | 3 | Image Formation and Perception, Feature Detection and Extraction, Object Recognition and Classification, Motion Analysis and Tracking, 3D Computer Vision, Deep Learning for Computer Vision |
| CS-703 | Blockchain Technology | Core Course | 3 | Cryptographic Primitives (Hashing, Digital Signatures), Distributed Ledger Technology (DLT), Consensus Mechanisms, Bitcoin and Cryptocurrencies, Ethereum and Smart Contracts, Blockchain Applications |
| CS-704 | Research Methodology | Core Course | 3 | Introduction to Research Process, Literature Review and Problem Formulation, Research Design and Methods, Data Collection and Analysis, Scientific Writing and Report Preparation, Ethics in Research |
| CS-705P | Data Science & Analytics Lab | Practical Course | 2 | Python/R for Data Analysis, Data Cleaning and Preprocessing, Statistical Modeling Implementations, Predictive Model Building, Interactive Data Visualizations, Working with Real-World Datasets |
| CS-706P | Computer Vision Lab | Practical Course | 2 | Image Acquisition and Preprocessing, Object Detection using OpenCV, Face Recognition Implementation, Motion Tracking, Image Stitching, Deep Learning based Vision Tasks |
| CS-CE-707(A) | Quantum Computing | Core Elective Course | 3 | Introduction to Quantum Mechanics, Qubits and Quantum Gates, Quantum Superposition and Entanglement, Quantum Algorithms (Shor''''s, Grover''''s), Quantum Error Correction, Quantum Cryptography |
| CS-CE-707(B) | Bio-Inspired Computing | Core Elective Course | 3 | Introduction to Bio-Inspired Algorithms, Genetic Algorithms and Genetic Programming, Ant Colony Optimization, Particle Swarm Optimization, Artificial Immune Systems, Neural Networks and Deep Learning |
| CS-CE-707(C) | Reinforcement Learning | Core Elective Course | 3 | Introduction to Reinforcement Learning, Markov Decision Processes (MDPs), Dynamic Programming, Monte Carlo Methods, Temporal-Difference Learning (Q-Learning, SARSA), Deep Reinforcement Learning |
| CS-OE-E3 | Open Elective-3 | Open Elective Course | 3 |
Semester 8
| Subject Code | Subject Name | Subject Type | Credits | Key Topics |
|---|---|---|---|---|
| CS-801 | Human Computer Interaction | Core Course | 3 | Foundations of HCI, User-Centered Design Principles, Interaction Design Paradigms, Usability Evaluation Methods, Interface Design Guidelines, Accessibility in HCI |
| CS-802 | Software Project Management | Core Course | 3 | Project Planning and Estimation, Project Scheduling and Tracking, Risk Management, Configuration Management, Software Quality Management, Agile Project Management |
| CS-803 | Data Privacy & Security | Core Course | 3 | Privacy Concepts and Models, Data Anonymization Techniques, Differential Privacy, Legal Frameworks (GDPR, HIPAA), Secure Multi-Party Computation, Homomorphic Encryption |
| CS-804 | Distributed Ledger Technologies | Core Course | 3 | Advanced Blockchain Architectures, Permissioned vs. Permissionless Blockchains, Hyperledger Fabric, Corda Platform, Interoperability in DLTs, Decentralized Autonomous Organizations (DAOs) |
| CS-805P | Human Computer Interaction Lab | Practical Course | 2 | User Research and Persona Creation, Wireframing and Prototyping Tools, Usability Testing Sessions, Heuristic Evaluation, Designing for Different Platforms, User Interface Implementation |
| CS-806P | Software Project Management Lab | Practical Course | 2 | Project Planning with Tools (Jira, Trello), Version Control with Git, Agile Sprint Planning, Risk Assessment and Mitigation, Quality Assurance Practices, Project Documentation |
| CS-CE-807(A) | Game Theory | Core Elective Course | 3 | Introduction to Game Theory, Strategic Form Games, Extensive Form Games, Nash Equilibrium, Cooperative Games, Mechanism Design |
| CS-CE-807(B) | Digital Forensics | Core Elective Course | 3 | Introduction to Digital Forensics, Evidence Acquisition and Handling, File System Forensics, Network Forensics, Mobile Forensics, Reporting and Legal Aspects |
| CS-CE-807(C) | Ethical Hacking | Core Elective Course | 3 | Introduction to Ethical Hacking, Footprinting and Reconnaissance, Scanning and Enumeration, Vulnerability Analysis, System Hacking Techniques, Web Application and Wireless Hacking |
| CS-OE-E4 | Open Elective-4 | Open Elective Course | 3 |
Semester 9
| Subject Code | Subject Name | Subject Type | Credits | Key Topics |
|---|---|---|---|---|
| CS-901 | Entrepreneurship & Startup Management | Core Course | 3 | Entrepreneurial Mindset and Opportunity Recognition, Business Plan Development, Market Analysis and Strategy, Funding and Venture Capital, Legal and Regulatory Aspects of Startups, Startup Ecosystem in India |
| CS-902 | Industrial Training / Internship | Core Course | 3 | Practical Industry Experience, Project Execution and Management, Problem Solving in Real-World Scenarios, Technical Report Writing, Professional Communication Skills, Exposure to Industry Best Practices |
| CS-903 | Minor Project | Core Course | 3 | Project Proposal and Literature Survey, System Design and Architecture, Implementation and Coding, Testing and Debugging, Project Report Writing, Presentation and Viva-voce |
| CS-904 | Technical Seminar | Core Course | 3 | Literature Review on Advanced Topics, Technical Research Paper Analysis, Scientific Presentation Skills, Effective Technical Communication, Question and Answer Handling, Recent Trends in Computer Science |
| CS-905P | Minor Project Lab | Practical Course | 2 | Practical Implementation of Minor Project, Software Development Tools Usage, Testing and Validation of Modules, Troubleshooting and Optimization, Version Control for Project Code, Documentation of Code and Processes |
| CS-CE-906(A) | Fuzzy Logic & Neural Networks | Core Elective Course | 3 | Introduction to Fuzzy Logic, Fuzzy Set Theory and Operations, Fuzzy Inference Systems, Artificial Neural Network Architectures, Learning Algorithms for ANNs, Hybrid Neuro-Fuzzy Systems |
| CS-CE-906(B) | Real-Time Systems | Core Elective Course | 3 | Introduction to Real-Time Systems, Real-Time Operating Systems, Real-Time Scheduling Algorithms, Resource Management and Control, Real-Time Communication, Fault Tolerance in RTS |
| CS-CE-906(C) | Robotics | Core Elective Course | 3 | Introduction to Robotics, Robot Kinematics and Dynamics, Sensors and Actuators, Robot Motion Planning, Robot Control Architectures, AI in Robotics and Machine Vision |
| CS-OE-E5 | Open Elective-5 | Open Elective Course | 3 | |
| HS-901 | Values & Ethics in Science | Humanities & Social Science Course | 3 | Scientific Integrity and Misconduct, Research Ethics and Responsible Conduct, Plagiarism and Intellectual Property Rights, Social Responsibility of Scientists, Ethical Dilemmas in Scientific Research, Impact of Science on Society |
Semester 10
| Subject Code | Subject Name | Subject Type | Credits | Key Topics |
|---|---|---|---|---|
| CS-1001 | Dissertation Part-I | Project/Dissertation | 6 | Problem Identification and Formulation, Extensive Literature Review, Methodology Design and Planning, Initial Data Collection/Experiment Design, Project Proposal and Planning, Review and Feedback |
| CS-1002 | Dissertation Part-II & Project | Project/Dissertation | 18 | Data Analysis and Interpretation, Implementation and System Development, Results, Discussion and Conclusion, Thesis Writing and Documentation, Presentation and Demonstration, Viva-Voce Examination |
