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M-SC in Computer Science at CHRIST (Deemed to be University)
Bengaluru, Karnataka
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About the Specialization
What is Computer Science at CHRIST (Deemed to be University) Bengaluru?
This M.Sc Computer Science program at CHRIST (Deemed to be University), Bengaluru, focuses on providing advanced knowledge and practical skills in cutting-edge areas of computing. It''''s designed to meet the growing demand for highly skilled professionals in India''''s booming IT and technology sector. The program differentiates itself through a blend of theoretical foundations and hands-on experience, preparing students for dynamic industry roles in areas like AI, Cloud, and Big Data.
Who Should Apply?
This program is ideal for Bachelor of Computer Applications (BCA), B.Sc in Computer Science/IT, or B.Tech/B.E. Computer Science Engineering graduates seeking advanced specialization. It caters to fresh graduates aspiring for entry-level roles as data scientists, cloud architects, or software developers, as well as working professionals looking to upskill and transition into more specialized and leadership positions within the Indian tech landscape.
Why Choose This Course?
Graduates of this program can expect to pursue diverse career paths in India, including roles such as AI/ML Engineer, Cloud Developer, Big Data Analyst, or Cybersecurity Specialist. Entry-level salaries typically range from INR 6-10 LPA, with experienced professionals earning significantly more. The program’s curriculum is aligned with industry certifications and global technology trends, fostering strong growth trajectories in leading Indian companies and startups.
Student Success Practices
Foundation Stage
Master Programming Fundamentals- (Semester 1-2)
Consistently practice core programming concepts like Data Structures, Algorithms, and Object-Oriented Programming (OOPs) using multiple languages. Focus on competitive programming to sharpen problem-solving skills and enhance logical thinking.
Tools & Resources
HackerRank, LeetCode, GeeksforGeeks, CodeChef, NPTEL courses
Career Connection
Strong fundamentals are essential for cracking technical interviews at top Indian IT firms and startups, forming the bedrock for advanced technical roles.
Build a Strong Mathematical and Logical Base- (Semester 1-2)
Pay close attention to Discrete Mathematical Structures and Algorithm Design and Analysis. These subjects form the bedrock for advanced topics in AI, Machine Learning, and Cryptography. Actively participate in math puzzles and logic challenges.
Tools & Resources
Khan Academy, MIT OpenCourseWare, Standard textbooks for discrete math and logic
Career Connection
Crucial for roles in data science, AI, and algorithmic development, significantly improving analytical and problem-solving abilities.
Engage in Early Project Development- (Semester 1-2)
Start small projects based on concepts learned in labs, such as a simple Database Management System application, an Operating System simulator component, or a basic Java application. Collaborate with peers on these initial projects.
Tools & Resources
GitHub for version control, Integrated Development Environments (IDEs) like IntelliJ IDEA, VS Code, Online tutorials
Career Connection
Building a project portfolio from the start helps showcase practical skills and initiative to recruiters for internships and placements.
Intermediate Stage
Gain Hands-on Experience with Emerging Technologies- (Semester 3)
Actively engage with labs focused on Cloud Computing, Big Data Analytics, and Internet of Things (IoT). Pursue online certifications from major providers like AWS, Azure, or Google Cloud. Work on mini-projects to apply these technologies.
Tools & Resources
AWS Free Tier, Azure for Students, Google Cloud Platform, Coursera/edX for specialized courses, Kaggle for datasets
Career Connection
These are highly sought-after skills in the Indian job market, directly leading to roles such as Cloud Engineer, Data Engineer, or IoT Developer.
Specialize through Electives and Self-Learning- (Semester 3)
Choose electives strategically based on your career interests, such as Advanced Cryptography for security or Natural Language Processing for AI. Deep dive into these areas through additional reading, research papers, and advanced online courses beyond the syllabus.
Tools & Resources
IEEE Xplore, SpringerLink, Specialized MOOCs on platforms like edX or Udacity, Industry whitepapers
Career Connection
Developing specialized skills makes you a more competitive candidate for niche technical roles and advanced research opportunities in your chosen field.
Network and Participate in Tech Events- (Semester 3)
Attend tech meetups, workshops, and seminars in Bengaluru, a vibrant tech hub. Connect with industry professionals on LinkedIn. Participate in hackathons and coding competitions to apply knowledge, gain exposure, and build a professional network.
Tools & Resources
LinkedIn, Meetup.com, Eventbrite, College career services for industry contacts
Career Connection
Builds a professional network crucial for internships, mentorship, and job referrals within the thriving Bengaluru tech ecosystem.
Advanced Stage
Excel in Dissertation and Internship- (Semester 4)
Choose a dissertation topic that is well-researched, innovative, and aligned with your specialization and career goals. Approach the internship as a serious opportunity to learn, contribute, and network, aiming to convert it into a potential pre-placement offer.
Tools & Resources
Research databases like Scopus and Web of Science, Academic advisors, Company mentors, LaTeX for professional document formatting
Career Connection
A strong dissertation showcases research and problem-solving abilities, while a successful internship is often the most direct path to a full-time role.
Intensive Placement Preparation- (Semester 4)
Engage in intensive placement preparation, including practicing mock interviews (technical, HR, behavioral), revising core computer science concepts, and solving company-specific coding questions. Prepare a compelling resume and optimize your LinkedIn profile.
Tools & Resources
InterviewBit, Glassdoor, LinkedIn, College placement cell resources, Alumni network for guidance
Career Connection
Direct and focused preparation for securing placements in top-tier Indian and multinational companies, maximizing success rate.
Develop Professional and Soft Skills- (Semester 4)
Focus on improving communication, teamwork, presentation skills, and professional etiquette. These are crucial for corporate success in the Indian context. Participate in workshops and group activities to hone these competencies.
Tools & Resources
Toastmasters International, College workshops on communication and leadership, Mock group discussions, Online courses on professional etiquette
Career Connection
Essential for effective collaboration in a corporate environment, excelling in team roles, and progressing into leadership positions within the industry.
Program Structure and Curriculum
Eligibility:
- Candidates who have passed BCA, B.Sc. in Computer Science, B.Sc. in Information Technology, B.Sc. in Computer Applications, B.Voc. in Computer Science/IT/Software Development, B.Tech. / B.E. in Computer Science Engineering / Information Technology / Electronics & Communication Engineering or equivalent with 50% aggregate marks from any recognized University in India or abroad.
Duration: 4 semesters / 2 years
Credits: 85 Credits
Assessment: Internal: 50%, External: 50%
Semester-wise Curriculum Table
Semester 1
| Subject Code | Subject Name | Subject Type | Credits | Key Topics |
|---|---|---|---|---|
| CSCP131 | Discrete Mathematical Structures | Core Theory | 4 | Set Theory, Relations and Functions, Mathematical Logic, Graph Theory, Trees and Algorithms, Algebraic Structures |
| CSCP132 | Advanced Data Structures and Algorithms | Core Theory | 4 | Data Structure Concepts, Advanced Trees and Heaps, Hashing Techniques, Graph Algorithms, Sorting and Searching, Algorithm Analysis |
| CSCP133 | Computer Networks | Core Theory | 4 | Network Topologies and Layers, OSI and TCP/IP Models, Data Link Layer Protocols, Network Layer Addressing and Routing, Transport Layer Protocols, Application Layer Protocols |
| CSCP134 | Advanced Database Management Systems | Core Theory | 4 | Relational Database Concepts, SQL and PL/SQL, Normalization and Query Processing, Transaction Management, Concurrency Control and Recovery, Distributed Databases and Security |
| CSCP171 | Lab – I (Data Structures, Algorithms and DBMS) | Core Lab | 3 | Implementation of Data Structures, Algorithm Design and Testing, SQL Query Writing, PL/SQL Programming, Database Operations, Mini Project Development |
| CSCP172 | Research and Publications | Soft Core | 2 | Research Methodology, Literature Review, Scientific Writing and Ethics, Referencing Styles, Plagiarism and Integrity, Research Tools |
| CSSC121 | Holistic Education | Soft Core | 2 | Self-Awareness and Self-Management, Interpersonal Skills, Critical Thinking and Problem Solving, Communication Skills, Ethical Values and Social Responsibility, Stress Management |
Semester 2
| Subject Code | Subject Name | Subject Type | Credits | Key Topics |
|---|---|---|---|---|
| CSCP231 | Operating Systems | Core Theory | 4 | Operating System Structures, Process Management and Scheduling, Deadlocks and Synchronization, Memory Management, File System Implementation, I/O Systems and Protection |
| CSCP232 | Design and Analysis of Algorithms | Core Theory | 4 | Algorithm Design Paradigms, Greedy Algorithms, Dynamic Programming, Graph Algorithms, Backtracking and Branch and Bound, NP-Hard and NP-Complete Problems |
| CSCP233 | Advanced Java Programming | Core Theory | 4 | Java Fundamentals and OOPs, Exception Handling and Multithreading, Collections Framework, JDBC and Database Connectivity, Servlets and JSP, Web Services |
| CSCP234 | Machine Learning | Core Theory | 4 | Introduction to Machine Learning, Supervised Learning, Unsupervised Learning, Regression and Classification, Model Evaluation and Validation, Deep Learning Basics |
| CSCP271 | Lab – II (OS, DAA and Java) | Core Lab | 3 | Operating System System Calls, Shell Scripting, Algorithm Implementation in Java, Advanced Java Programming, Machine Learning Model Implementation, Project on OS/Java/ML |
| CSEC251 | Compiler Design | Elective Theory | 3 | Compiler Structure, Lexical Analysis, Syntax Analysis, Semantic Analysis, Intermediate Code Generation, Code Optimization |
| CSEC252 | Digital Image Processing | Elective Theory | 3 | Image Fundamentals, Image Enhancement, Image Restoration, Image Compression, Morphological Image Processing, Image Segmentation |
| CSEC253 | Advanced Computer Architecture | Elective Theory | 3 | Pipelining and Instruction Level Parallelism, Multiprocessors and Cache Coherence, Memory Hierarchy Design, Vector Processors, GPU Architecture, Parallel Computing |
Semester 3
| Subject Code | Subject Name | Subject Type | Credits | Key Topics |
|---|---|---|---|---|
| CSCP331 | Cloud Computing | Core Theory | 4 | Cloud Computing Concepts, Service Models (IaaS, PaaS, SaaS), Deployment Models, Virtualization Technology, Cloud Security and Management, Cloud Platforms (AWS/Azure basics) |
| CSCP332 | Big Data Analytics | Core Theory | 4 | Big Data Introduction and Challenges, Hadoop Ecosystem (HDFS, MapReduce), Spark Framework, Data Warehousing and Data Mining, NoSQL Databases, Big Data Visualization |
| CSCP333 | Internet of Things (IoT) | Core Theory | 4 | IoT Architecture and Paradigms, Sensors, Actuators, and Devices, IoT Communication Protocols, IoT Platforms and Analytics, IoT Security and Privacy, Smart Applications |
| CSCP371 | Lab – III (Cloud, Big Data and IoT) | Core Lab | 3 | Cloud Service Deployment, Hadoop and Spark Programming, IoT Device Interfacing, Data Collection and Processing for IoT, Big Data Analytics Tools, Cloud-based Application Development |
| CSEC351 | Advanced Cryptography | Elective Theory | 3 | Classical Cryptography, Symmetric Key Cryptography, Asymmetric Key Cryptography, Hashing and Message Authentication, Digital Signatures, Cryptographic Protocols |
| CSEC352 | Natural Language Processing | Elective Theory | 3 | NLP Basics and Text Preprocessing, N-grams and Language Models, Part-of-Speech Tagging, Sentiment Analysis, Machine Translation, Deep Learning for NLP |
| CSEC353 | Soft Computing | Elective Theory | 3 | Fuzzy Logic and Fuzzy Sets, Artificial Neural Networks, Genetic Algorithms, Hybrid Systems, Swarm Intelligence, Optimization Techniques |
Semester 4
| Subject Code | Subject Name | Subject Type | Credits | Key Topics |
|---|---|---|---|---|
| CSCP471 | Dissertation | Project/Dissertation | 12 | Research Problem Formulation, Extensive Literature Review, Methodology Design and Implementation, Data Collection and Analysis, Report Writing and Documentation, Presentation and Viva Voce |
| CSCP481 | Internship | Internship | 6 | Real-world Project Experience, Industry Best Practices, Professional Skill Development, Teamwork and Collaboration, Problem Solving in Industry Setting, Internship Report and Presentation |
