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B-SC-HONOURS in Computer Science at Sundarban Hazi Desarat College
South 24 Parganas, West Bengal
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About the Specialization
What is Computer Science at Sundarban Hazi Desarat College South 24 Parganas?
This Computer Science Honours program at Sundarban Hazi Desarat College, affiliated with the University of Calcutta, focuses on foundational and advanced computing concepts. It emphasizes core programming, data structures, algorithms, and emerging fields like AI and Big Data, preparing students for the dynamic Indian IT industry. The curriculum is designed to foster critical thinking and problem-solving skills, crucial for innovation.
Who Should Apply?
This program is ideal for high school graduates with a strong aptitude for logical reasoning and mathematics, aspiring to build a career in software development, data science, or research. It also suits individuals passionate about technology and innovation, seeking a robust theoretical and practical foundation in computer science to contribute to India''''s digital transformation.
Why Choose This Course?
Graduates of this program can expect diverse career paths in India, including software developer, data analyst, web developer, or system administrator. Entry-level salaries typically range from INR 3-6 LPA, with significant growth potential up to INR 10-20+ LPA for experienced professionals. The degree provides a solid base for pursuing higher education or specialized certifications.
Student Success Practices
Foundation Stage
Master Programming Fundamentals (C++ & Data Structures)- (Semester 1-2)
Dedicate extensive time to practicing C++ programming and implementing data structures. Solve problems on platforms like HackerRank, LeetCode (easy level), and GeeksforGeeks daily to build strong logical thinking and coding proficiency.
Tools & Resources
HackerRank, GeeksforGeeks, CodeChef, Online C++ Compilers
Career Connection
Strong fundamentals are critical for passing initial coding rounds in placements and form the backbone for advanced topics in software development roles.
Build a Strong Mathematical & Logical Base- (Semester 1-2)
Pay close attention to Discrete Structures and Generic Elective subjects like Mathematics or Statistics. Understanding these concepts thoroughly is vital for algorithms, machine learning, and problem-solving in computer science.
Tools & Resources
NCERT Math textbooks (revisit), Khan Academy, MIT OpenCourseWare (Discrete Math), Study groups
Career Connection
These foundational skills are indispensable for roles in data science, algorithm design, and competitive programming, enhancing analytical abilities.
Engage in Peer Learning and Collaborative Projects- (Semester 1-2)
Form study groups to discuss complex topics, share code, and collaborate on small academic projects. This enhances understanding, communication skills, and exposes you to diverse problem-solving approaches.
Tools & Resources
GitHub (for collaborative coding), Google Meet/Zoom for discussions, College library resources
Career Connection
Teamwork and collaboration are highly valued in the Indian IT industry, preparing you for professional project environments.
Intermediate Stage
Develop Practical Skills in Core CS Domains- (Semester 3-4)
Beyond coursework, actively engage in mini-projects for Operating Systems, Computer Networks, and DBMS. For instance, create a simple shell, a chat application, or a database-driven web application to apply theoretical knowledge practically.
Tools & Resources
Linux/Ubuntu OS, Wireshark (for network analysis), MySQL/PostgreSQL, Eclipse/IntelliJ IDEA
Career Connection
Practical project experience is key to demonstrating competence in job interviews and helps secure roles in system administration, network engineering, and database management.
Participate in Coding Competitions & Hackathons- (Semester 3-5)
Regularly participate in online coding contests on platforms like Codeforces, TopCoder, or college-level hackathons. This sharpens algorithmic thinking, problem-solving speed, and exposes you to real-world challenges.
Tools & Resources
Codeforces, TopCoder, Local college tech fests
Career Connection
Success in these competitions boosts your resume, highlights your capabilities to recruiters, and can open doors to high-paying tech roles in leading companies.
Explore Skill Enhancement Courses for Specialization- (Semester 3-5)
Actively pursue the Skill Enhancement Courses (SEC) like Python or Android Development. Beyond the curriculum, complete online courses from platforms like Coursera or Udemy to gain deeper expertise and build a portfolio of specialized projects.
Tools & Resources
Coursera, Udemy, freeCodeCamp, Official Python/Android documentation
Career Connection
Specialized skills are highly sought after. Building projects in these areas makes you a more attractive candidate for focused roles like web developer, mobile app developer, or data analyst.
Advanced Stage
Undertake Industry-Relevant Projects and Internships- (Semester 5-6)
Focus on developing significant final year projects, ideally incorporating AI, Big Data, or Machine Learning. Seek out internships at Indian startups or established tech companies to gain real-world experience and industry exposure, which are crucial for placements.
Tools & Resources
GitHub (for project showcasing), LinkedIn (for networking and internships), Internshala, College placement cell
Career Connection
Practical industry exposure and a strong project portfolio significantly enhance employability and facilitate direct entry into the job market with valuable experience.
Intensify Placement Preparation and Mock Interviews- (Semester 5-6)
Begin intensive preparation for company-specific aptitude tests, technical interviews, and HR rounds. Participate in mock interviews with faculty, seniors, or professional trainers, focusing on data structures, algorithms, and core computer science concepts.
Tools & Resources
Glassdoor (for company interview experiences), LeetCode (hard problems), InterviewBit, Aptitude test books
Career Connection
Systematic preparation and practice are essential to convert interview opportunities into job offers, ensuring a successful transition from academia to a professional career.
Build a Professional Network and Personal Brand- (Semester 5-6)
Attend industry seminars, workshops, and tech conferences (online or offline) to network with professionals and peers. Create a strong LinkedIn profile, showcase your projects, and contribute to open-source communities to build your personal brand.
Tools & Resources
LinkedIn, GitHub, Meetup.com (for local tech events), Conferences like DevConf, PyCon India
Career Connection
A robust professional network can lead to referrals, mentorship, and awareness of emerging job opportunities, greatly accelerating career growth in the Indian tech ecosystem.
Program Structure and Curriculum
Eligibility:
- 10+2 (Higher Secondary or equivalent) with Computer Science/Mathematics/Physics/Statistics/Electronics as a subject, with minimum aggregate marks as per University of Calcutta norms and college specific cutoffs.
Duration: 3 years / 6 semesters
Credits: 140 Credits
Assessment: Internal: Theory: 20%, Practical: 50%, External: Theory: 80%, Practical: 50%
Semester-wise Curriculum Table
Semester 1
| Subject Code | Subject Name | Subject Type | Credits | Key Topics |
|---|---|---|---|---|
| CSPA-CC1 | Programming Fundamentals using C++ (Theory & Lab) | Core | 6 | Introduction to C++, Control Flow and Functions, Arrays, Pointers, and Structures, Object-Oriented Programming Concepts, Classes, Objects, Inheritance, Polymorphism |
| CSPA-CC2 | Data Structures (Theory & Lab) | Core | 6 | Arrays, Stacks, Queues, Linked Lists and Trees, Graphs and Hashing, Sorting and Searching Algorithms, Algorithm Analysis |
| ENVS-AECC1 | Environmental Studies | Ability Enhancement Compulsory Course | 2 | Ecosystems and Biodiversity, Natural Resources, Environmental Pollution and Management, Social Issues and the Environment, Human Population and Environment |
| GE-1 | Generic Elective - I (Theory & Lab) | Generic Elective | 6 | Subject varies (e.g., Mathematics, Physics, Statistics), Fundamental concepts of chosen discipline, Problem-solving techniques, Basic laboratory experiments (if applicable), Applications in relevant fields |
Semester 2
| Subject Code | Subject Name | Subject Type | Credits | Key Topics |
|---|---|---|---|---|
| CSPA-CC3 | Computer Organization and Architecture (Theory & Lab) | Core | 6 | Digital Logic Circuits, Combinational and Sequential Circuits, CPU Organization and Design, Memory System Hierarchy, Input/Output Organization, Instruction Set Architecture |
| CSPA-CC4 | Discrete Structures (Theory & Lab) | Core | 6 | Set Theory and Relations, Mathematical Logic and Proofs, Counting, Permutations, Combinations, Graph Theory and Trees, Boolean Algebra and Lattices |
| AECC2 | English Communication / MIL Communication | Ability Enhancement Compulsory Course | 2 | Grammar and Usage, Reading Comprehension, Paragraph and Essay Writing, Presentation Skills, Official Communication Formats |
| GE-2 | Generic Elective - II (Theory & Lab) | Generic Elective | 6 | Subject varies (e.g., Mathematics, Physics, Statistics), Advanced concepts of chosen discipline, Analytical problem solving, Data interpretation and analysis, Practical application skills |
Semester 3
| Subject Code | Subject Name | Subject Type | Credits | Key Topics |
|---|---|---|---|---|
| CSPA-CC5 | Operating Systems (Theory & Lab) | Core | 6 | Operating System Concepts, Process Management and CPU Scheduling, Deadlocks and Synchronization, Memory Management, File Systems and I/O Management, Security and Protection |
| CSPA-CC6 | Computer Networks (Theory & Lab) | Core | 6 | Network Models (OSI, TCP/IP), Physical and Data Link Layer, Network Layer Protocols, Transport Layer Services, Application Layer Protocols, Network Security Fundamentals |
| CSPA-CC7 | Database Management Systems (Theory & Lab) | Core | 6 | DBMS Architecture and Data Models, Entity-Relationship (ER) Model, Relational Model and Algebra, Structured Query Language (SQL), Normalization and Query Processing, Transaction Management and Concurrency Control |
| CS-SEC1 | Skill Enhancement Course - I (Python Programming / Web Design) | Skill Enhancement Course | 2 | Python Syntax and Data Structures, Functions, Modules, File I/O (if Python), HTML5, CSS3 for Web Layout (if Web Design), JavaScript Basics for Interactivity (if Web Design), Introduction to Web Hosting (if Web Design) |
| GE-3 | Generic Elective - III (Theory & Lab) | Generic Elective | 6 | Subject varies (e.g., Mathematics, Physics, Statistics), Specialized topics in chosen discipline, Research methodology basics, Advanced practical applications, Interdisciplinary connections |
Semester 4
| Subject Code | Subject Name | Subject Type | Credits | Key Topics |
|---|---|---|---|---|
| CSPA-CC8 | Design and Analysis of Algorithms (Theory & Lab) | Core | 6 | Asymptotic Notations and Recurrence Relations, Divide and Conquer Algorithms, Greedy Algorithms and Dynamic Programming, Graph Algorithms (BFS, DFS, MST, Shortest Path), Backtracking and Branch & Bound, NP-Completeness |
| CSPA-CC9 | Software Engineering (Theory & Lab) | Core | 6 | Software Life Cycle Models, Requirements Engineering, Software Design Principles, Software Testing Techniques, Software Project Management, Software Quality Assurance |
| CSPA-CC10 | Internet Technologies (Theory & Lab) | Core | 6 | Web Standards and Protocols, HTML, CSS, and JavaScript, XML and AJAX, Server-Side Scripting (PHP/ASP.NET), Web Servers and Databases, Web Security Fundamentals |
| CS-SEC2 | Skill Enhancement Course - II (Android Programming / R Programming) | Skill Enhancement Course | 2 | Android Architecture and UI Design (if Android), Activities, Intents, Data Storage (if Android), R Basics, Data Types, Control Structures (if R), Data Frames, Data Manipulation (if R), Data Visualization in R (if R) |
| GE-4 | Generic Elective - IV (Theory & Lab) | Generic Elective | 6 | Subject varies (e.g., Mathematics, Physics, Statistics), Advanced conceptual understanding, Independent study and research skills, Presentation and communication of findings, Preparation for higher studies |
Semester 5
| Subject Code | Subject Name | Subject Type | Credits | Key Topics |
|---|---|---|---|---|
| CSPA-CC11 | Artificial Intelligence (Theory & Lab) | Core | 6 | Introduction to AI and Intelligent Agents, Problem-Solving using Search Techniques, Knowledge Representation and Reasoning, Machine Learning Fundamentals, Natural Language Processing, Expert Systems |
| CSPA-CC12 | Computer Graphics (Theory & Lab) | Core | 6 | Graphics Primitives and Algorithms, 2D and 3D Transformations, Viewing, Clipping, and Projections, Surface Detection and Rendering, Color Models and Illumination, Animation Techniques |
| CSPA-DSE-A1 | Discipline Specific Elective - I (Example: Data Mining / Cloud Computing) (Theory & Lab) | Elective | 6 | Introduction to Data Mining, Data Preprocessing, Association Rule Mining, Classification Algorithms, Clustering Techniques, Anomaly Detection, Cloud Service Models (IaaS, PaaS, SaaS) (if Cloud), Cloud Deployment Models (Public, Private, Hybrid) (if Cloud), Virtualization and Cloud Security (if Cloud) |
| CSPA-DSE-A2 | Discipline Specific Elective - II (Example: Machine Learning / Embedded Systems) (Theory & Lab) | Elective | 6 | Supervised Learning Algorithms (Regression, Classification), Unsupervised Learning (Clustering, PCA), Neural Networks and Deep Learning Basics, Model Evaluation and Validation, Introduction to Embedded Systems (if Embedded), Microcontrollers and Sensors (if Embedded) |
Semester 6
| Subject Code | Subject Name | Subject Type | Credits | Key Topics |
|---|---|---|---|---|
| CSPA-CC13 | Big Data Analytics (Theory & Lab) | Core | 6 | Introduction to Big Data and its Characteristics, Hadoop Ecosystem (HDFS, MapReduce), Big Data Technologies (Hive, Pig, Spark), Data Stream Mining, NoSQL Databases, Big Data Security and Privacy |
| CSPA-CC14 | Advanced Java Programming (Theory & Lab) | Core | 6 | Java Collections Framework, JDBC and Database Connectivity, Servlets and JavaServer Pages (JSP), Enterprise JavaBeans (EJB), Web Services (SOAP, REST), Multithreading and Networking in Java |
| CSPA-DSE-B1 | Discipline Specific Elective - III (Example: Project / Internet of Things) (Theory/Project) | Elective / Project | 6 | Project Planning and Management, Requirement Analysis and System Design, Software Implementation and Testing, Documentation and Presentation, IoT Architecture and Protocols (if IoT), Sensor Networks and IoT Security (if IoT) |
| CSPA-DSE-B2 | Discipline Specific Elective - IV (Example: Network Security / Mobile Computing) (Theory & Lab) | Elective | 6 | Cryptography and Network Security Attacks, Firewalls, VPNs, Intrusion Detection Systems, Web and Email Security, Wireless Communication Technologies (if Mobile Computing), Mobile OS and Application Development (if Mobile Computing), Location-Based Services (if Mobile Computing) |
