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BSC-COMPUTER-SCIENCE in Computer Science at Sree Sankara College, Kalady
Ernakulam, Kerala
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About the Specialization
What is Computer Science at Sree Sankara College, Kalady Ernakulam?
This Computer Science program at Sree Sankara College focuses on equipping students with a strong foundation in theoretical computer science and practical programming skills. Aligned with Indian industry demands, the curriculum covers programming languages, data structures, algorithms, database management, operating systems, and web technologies. The program emphasizes problem-solving and prepares graduates for diverse roles in the rapidly evolving IT sector.
Who Should Apply?
This program is ideal for high school graduates with a keen interest in logical reasoning and technology, aspiring to build a career in software development, data analysis, or IT support. It suits freshers seeking entry into the tech industry, individuals with a foundational understanding of mathematics, and those passionate about learning contemporary computing paradigms to solve real-world challenges.
Why Choose This Course?
Graduates can expect robust career paths in India as Software Developers, Data Analysts, Web Developers, or System Administrators. Entry-level salaries typically range from INR 2.5 to 4 LPA, growing significantly with experience. The program fosters critical thinking and analytical skills, aligning with requirements for higher studies or professional certifications in cloud computing, cybersecurity, or data science.
Student Success Practices
Foundation Stage
Master Programming Fundamentals- (Semester 1-2)
Dedicate consistent time to practice C programming and data structures. Actively solve coding problems on platforms like HackerRank or CodeChef to solidify logic and algorithm implementation. Understand concepts thoroughly before moving on.
Tools & Resources
CodeChef, HackerRank, GeeksforGeeks, NPTEL tutorials for C and Data Structures
Career Connection
Strong programming fundamentals are essential for cracking entry-level developer roles and technical interviews at Indian IT companies like TCS, Infosys, and Wipro.
Develop Strong Study Habits and Time Management- (Semester 1-2)
Establish a structured study routine. Prioritize understanding core concepts over rote learning, especially for Discrete Mathematics and Calculus. Form study groups to discuss complex topics and clarify doubts, fostering collaborative learning.
Tools & Resources
Google Calendar for scheduling, Pomodoro Technique, Peer study groups, University library resources
Career Connection
Effective time management and analytical thinking honed in early semesters are vital for meeting project deadlines and managing workload in the corporate world.
Engage in Early Skill Building Workshops- (Semester 1-2)
Look for college-organized or local workshops on basic web development (HTML/CSS), Linux commands, or intro to Python. These early exposures can spark interest and provide a practical edge beyond the core curriculum.
Tools & Resources
freeCodeCamp, W3Schools, Local tech meetups, College departmental clubs
Career Connection
Early practical exposure helps build a diverse skill set, making students more competitive for internships and better prepared for specialized roles later on.
Intermediate Stage
Build Practical Projects and Portfolio- (Semester 3-5)
Apply learned concepts from Python, OS, DBMS, and Web Programming to build small, tangible projects. Collaborate with peers on projects, documenting your contributions. Utilize platforms like GitHub to showcase your work.
Tools & Resources
GitHub, VS Code, MySQL, XAMPP/WAMP, Udemy/Coursera project-based learning resources
Career Connection
A strong project portfolio is crucial for demonstrating practical skills to recruiters, especially for roles in Indian startups and product companies.
Seek Industry Exposure through Internships/Mini-Projects- (Semester 4-5)
Actively search for summer internships or part-time mini-project opportunities in local tech companies, even if unpaid initially. This provides invaluable real-world experience and helps build a professional network within the Indian IT ecosystem.
Tools & Resources
LinkedIn, Internshala, College placement cell, Local tech job boards
Career Connection
Internships are often a direct gateway to pre-placement offers or significantly enhance employability for roles in IT services and product development.
Participate in Coding Competitions & Hackathons- (Semester 3-5)
Join college coding clubs and participate in inter-college or national-level coding competitions (e.g., ICPC, Smart India Hackathon). This enhances problem-solving under pressure and builds competitive programming skills.
Tools & Resources
LeetCode, CodeForces, College coding clubs, National hackathon platforms
Career Connection
Success in such competitions is highly valued by top tech companies during recruitment drives and demonstrates strong analytical abilities.
Advanced Stage
Intensive Placement Preparation and Skill Refinement- (Semester 6)
Focus on mock interviews, aptitude tests, and resume building. Practice technical questions (DSA, OS, DBMS, Networks) rigorously. Identify your target roles and specialize in relevant technologies like Android, Data Mining, or an elective.
Tools & Resources
InterviewBit, Glassdoor, Online aptitude test platforms, College placement cell workshops, Specialized online courses
Career Connection
This focused preparation is critical for securing placements in MNCs and major Indian tech firms during campus recruitment drives.
Advanced Project Development and Research- (Semester 6)
Leverage your final year project (Phase II) to delve into advanced areas like Machine Learning, Cloud Computing, or IoT. Aim for innovation, practical utility, and publishable quality if possible. Consider presenting at college tech fests.
Tools & Resources
Research papers, Advanced libraries (TensorFlow, PyTorch), Cloud platforms (AWS Free Tier), Academic mentors
Career Connection
A high-quality, innovative final project can differentiate you for specialized roles, research positions, or even entrepreneurial ventures.
Network Strategically and Explore Further Studies/Certifications- (Semester 6)
Connect with alumni, industry professionals on LinkedIn, and attend virtual career fairs. Explore postgraduate options (MCA, M.Sc. CS) or industry-recognized certifications (AWS, Azure, Google Cloud, relevant to your elective) to specialize further.
Tools & Resources
LinkedIn, Alumni networks, Career guidance counsellors, Official certification websites
Career Connection
Strategic networking can open doors to unadvertised opportunities, while certifications can validate expertise and accelerate career progression in specialized fields in India and globally.
Program Structure and Curriculum
Eligibility:
- A pass in Plus Two or equivalent examination with Mathematics/Computer Science/Informatics Practices as one of the subjects.
Duration: 6 semesters / 3 years
Credits: 120 Credits
Assessment: Internal: 20%, External: 80%
Semester-wise Curriculum Table
Semester 1
| Subject Code | Subject Name | Subject Type | Credits | Key Topics |
|---|---|---|---|---|
| EN1CCT01 | Critical Reasoning, Writing and Presentation | Common Course - English | 4 | Introduction to Critical Reasoning, Argumentation and Logic, Academic Writing Techniques, Presentation Skills, Language and Communication |
| EN1CCT02 | Literature, Culture and Environment | Common Course - English | 4 | Literary Forms and Genres, Cultural Studies, Environmental Literature, Critical Reading and Analysis, Interdisciplinary Perspectives |
| ML1CCT01/HS1CCT01/etc. | Additional Language (e.g., Malayalam/Hindi) | Common Course - Additional Language | 4 | Language Comprehension, Grammar and Usage, Basic Communication Skills, Cultural Context of Language, Writing and Translation |
| CS1CRT01 | Introduction to Computers and Programming in C | Core Theory | 4 | Computer Fundamentals, Problem Solving Methodologies, Introduction to C Programming, Control Structures and Loops, Functions, Arrays and Pointers, Structures and Unions |
| CS1PRP01 | Practical I | Core Lab | 2 | C Programming Lab Exercises, Implementation of Basic Algorithms, Debugging and Testing C Programs |
| MM1CMT01 | Discrete Mathematics | Complementary Theory - Mathematics | 4 | Set Theory and Logic, Relations and Functions, Graph Theory, Trees and Combinatorics, Recurrence Relations |
Semester 2
| Subject Code | Subject Name | Subject Type | Credits | Key Topics |
|---|---|---|---|---|
| EN2CCT03 | Paradigms of Research and Advanced Writing | Common Course - English | 4 | Research Methodologies, Academic Research Skills, Advanced Writing Strategies, Thesis Development, Citation and Referencing |
| EN2CCT04 | Reading Fiction | Common Course - English | 4 | Elements of Fiction, Literary Criticism, Narrative Techniques, Genre Studies, Critical Approaches to Fiction |
| ML2CCT02/HS2CCT02/etc. | Additional Language (e.g., Malayalam/Hindi) | Common Course - Additional Language | 4 | Advanced Grammar and Syntax, Literary Appreciation, Composition and Essay Writing, Communication Strategies, Cultural Readings |
| CS2CRT02 | Data Structures | Core Theory | 4 | Arrays and Linked Lists, Stacks and Queues, Trees (Binary, AVL, B-Trees), Graphs and Graph Traversal, Hashing Techniques, Sorting and Searching Algorithms |
| CS2PRP02 | Practical II | Core Lab | 2 | Implementation of Data Structures in C, Application of Sorting Algorithms, Graph Traversal Implementations |
| MM2CMT02 | Calculus | Complementary Theory - Mathematics | 4 | Differential Calculus, Integral Calculus, Sequences and Series, Vector Calculus, Partial Derivatives |
Semester 3
| Subject Code | Subject Name | Subject Type | Credits | Key Topics |
|---|---|---|---|---|
| CS3CCT05 | Python Programming | Common Course - General | 4 | Python Basics and Data Types, Control Flow and Functions, Modules and Packages, Object-Oriented Programming in Python, File Handling and Exception Handling |
| CS3CRT03 | Computer Organization and Architecture | Core Theory | 4 | Digital Logic Circuits, Basic Computer Organization, Central Processing Unit Design, Memory Hierarchy and Management, Input/Output Organization, Pipelining and Parallel Processing |
| CS3CRT04 | Operating Systems | Core Theory | 4 | Operating System Concepts, Process Management and Scheduling, Memory Management Techniques, File Systems and I/O Systems, Deadlocks and Concurrency Control |
| CS3PRP03 | Practical III | Core Lab | 2 | Python Programming Lab, Shell Scripting and Linux Commands, Operating System Utilities |
| ST3CMT01 | Statistical Inference | Complementary Theory - Statistics | 4 | Probability Distributions, Sampling Theory, Estimation (Point and Interval), Hypothesis Testing, Correlation and Regression |
Semester 4
| Subject Code | Subject Name | Subject Type | Credits | Key Topics |
|---|---|---|---|---|
| CS4CCT06 | Data Communication and Computer Networks | Common Course - General | 4 | Network Models (OSI, TCP/IP), Physical Layer and Data Link Layer, Network Layer (IP Addressing, Routing), Transport Layer (TCP, UDP), Application Layer Protocols, Network Security Basics |
| CS4CRT05 | Design and Analysis of Algorithms | Core Theory | 4 | Algorithm Analysis and Efficiency, Divide and Conquer Algorithms, Greedy Algorithms, Dynamic Programming, Graph Algorithms, NP-Completeness and Approximation Algorithms |
| CS4CRT06 | Database Management Systems | Core Theory | 4 | DBMS Architecture and Models, Relational Model and Algebra, Structured Query Language (SQL), Entity-Relationship Modeling, Normalization and Denormalization, Transaction Management and Concurrency Control |
| CS4PRP04 | Practical IV | Core Lab | 2 | SQL Lab: DDL, DML Operations, SQL Joins and Subqueries, Implementation of Algorithms in Python/C |
| ST4CMT02 | Probability and Random Variables | Complementary Theory - Statistics | 4 | Probability Theory and Axioms, Random Variables (Discrete and Continuous), Expectation and Variance, Probability Distributions, Central Limit Theorem |
Semester 5
| Subject Code | Subject Name | Subject Type | Credits | Key Topics |
|---|---|---|---|---|
| CS5CRT07 | System Administration and Ethical Hacking | Core Theory | 4 | Linux/Windows System Administration, Network Services Configuration, Cyber Security Fundamentals, Penetration Testing Phases, Ethical Hacking Tools and Techniques |
| CS5CRT08 | Web Programming using PHP | Core Theory | 4 | HTML and CSS Fundamentals, JavaScript Basics, PHP Core Concepts, Form Handling and Validation, Database Connectivity with MySQL, Session Management and Cookies |
| CS5CRT09 | Object-Oriented Programming in Java | Core Theory | 4 | OOP Concepts (Encapsulation, Inheritance), Polymorphism and Abstraction, Java Syntax and Data Types, Exception Handling, Collections Framework, Multithreading |
| CS5CRT10 | Software Engineering | Core Theory | 4 | Software Development Life Cycle Models, Requirements Engineering, Software Design Principles, Software Testing Strategies, Software Quality Assurance, Project Management and Estimation |
| CS5PRP05 | Practical V | Core Lab | 4 | Linux Administration Exercises, PHP Web Application Development, Java Programming Lab, Database Integration with Web Applications |
| CS5OCT01 | Web Designing | Open Course - Elective | 3 | HTML5 and CSS3 for Responsive Design, JavaScript and DOM Manipulation, UI/UX Principles, Web Graphics and Tools, Web Hosting Basics |
| CS5OCT02 | Cyber Security | Open Course - Elective | 3 | Network Security Concepts, Cryptography and Ciphers, Malware and Viruses, Cyber Laws and Ethics, Digital Forensics Basics |
| CS5OCT03 | Fundamentals of Data Science | Open Course - Elective | 3 | Data Science Lifecycle, Data Collection and Cleaning, Exploratory Data Analysis, Data Visualization Techniques, Introduction to Machine Learning |
| CS5PRP01 | Project Work (Phase I) | Project | 2 | Problem Identification and Scope, Literature Survey, Feasibility Study, Requirements Analysis, Initial Design and Planning |
Semester 6
| Subject Code | Subject Name | Subject Type | Credits | Key Topics |
|---|---|---|---|---|
| CS6CRT11 | Android Programming | Core Theory | 4 | Android Architecture and Components, User Interface Design (Layouts, Widgets), Activities and Intents, Data Storage (SQLite, Shared Preferences), Networking and API Integration, App Publishing and Monetization |
| CS6CRT12 | Computer Graphics and Image Processing | Core Theory | 4 | Graphics Primitives and Algorithms, 2D and 3D Transformations, Viewing and Projections, Image Enhancement and Restoration, Image Segmentation, Color Models and Shading |
| CS6CRT13 | Data Mining and Data Warehousing | Core Theory | 4 | Data Warehousing Concepts and Architecture, OLAP Operations, Data Preprocessing, Association Rule Mining, Classification Algorithms, Clustering Techniques |
| CS6PRP06 | Practical VI | Core Lab | 4 | Android App Development Lab, Computer Graphics Programming, Image Processing Techniques, Data Mining Tool Usage |
| CS6CET01 | Distributed Systems | Core Elective | 3 | Distributed System Architectures, Inter-process Communication, Distributed Synchronization, Consistency and Replication, Fault Tolerance, Distributed File Systems |
| CS6CET02 | Big Data Analytics | Core Elective | 3 | Big Data Concepts and Challenges, Hadoop Ecosystem (HDFS, MapReduce), Apache Spark Basics, NoSQL Databases, Data Visualization for Big Data, Introduction to Predictive Analytics |
| CS6CET03 | Embedded Systems | Core Elective | 3 | Embedded System Architecture, Microcontrollers and Processors, Real-Time Operating Systems (RTOS), Sensors and Actuators, Embedded Programming (C/Assembly), IoT Integration |
| CS6CET04 | Software Testing and Quality Assurance | Core Elective | 3 | Software Testing Principles, Test Levels and Types (Unit, Integration), Black Box and White Box Testing, Quality Assurance Techniques, Test Automation Concepts, Performance and Security Testing |
| CS6CET05 | Cloud Computing | Core Elective | 3 | Cloud Computing Architecture, Service Models (IaaS, PaaS, SaaS), Deployment Models (Public, Private, Hybrid), Virtualization Technologies, Cloud Security Challenges, Introduction to AWS/Azure/GCP |
| CS6CET06 | Machine Learning | Core Elective | 3 | Introduction to Machine Learning, Supervised Learning (Regression, Classification), Unsupervised Learning (Clustering), Model Evaluation and Validation, Neural Networks and Deep Learning Basics, Feature Engineering |
| CS6PRP02 | Project Work (Phase II) | Project | 4 | System Design and Implementation, Software Testing and Quality Assurance, Project Documentation and Report Writing, Presentation and Demonstration, Project Deployment |
| CS6VVT01 | Viva Voce | Viva Voce | 2 | Comprehensive Oral Examination, Project Defense and Q&A, General Computer Science Concepts |
