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B-SC in Computer Science Hons at Panjab University
Chandigarh, Chandigarh
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About the Specialization
What is Computer Science (Hons.) at Panjab University Chandigarh?
This B.Sc. (Hons.) Computer Science program at Panjab University, Chandigarh focuses on building a strong foundational and advanced understanding of computing principles. Rooted in a robust curriculum, it covers core areas like programming, data structures, algorithms, operating systems, and database management, with advanced topics including artificial intelligence, data mining, and computer networks. The program aims to equip students with theoretical knowledge and practical skills crucial for the rapidly evolving Indian IT and tech industry, preparing them for diverse roles in software development, data analytics, and research.
Who Should Apply?
This program is ideal for high school graduates with a strong aptitude for mathematics and logical reasoning, seeking a comprehensive education in computer science. It caters to fresh aspirants aiming for entry-level roles in software engineering, data analysis, or IT support, providing a solid academic base. Students interested in pursuing higher studies like MCA or M.Sc. in Computer Science will also find the curriculum beneficial, laying the groundwork for advanced research and specialization.
Why Choose This Course?
Graduates of this program can expect to secure roles as junior software developers, data analysts, system administrators, or web developers in various Indian IT firms, startups, and public sector organizations. Entry-level salaries typically range from INR 3-6 LPA, with potential for significant growth with experience and advanced skills. The strong theoretical foundation also prepares students for competitive exams for government jobs and further academic pursuits, enabling them to adapt to new technologies and drive innovation in the Indian tech landscape.
Student Success Practices
Foundation Stage
Master Programming Fundamentals- (Semester 1-2)
Dedicate significant time to understanding core programming concepts (C/C++, OOP). Practice daily coding challenges to solidify logic and syntax. Focus on error handling and debugging techniques early on to build a robust programming foundation.
Tools & Resources
HackerRank, GeeksforGeeks, CodeChef, online C++ tutorials, peer coding sessions
Career Connection
Strong programming fundamentals are the bedrock for almost all software development roles, essential for cracking technical interviews and building efficient applications, thus enhancing placement opportunities.
Build Strong Data Structures & Algorithms (DSA) Base- (Semester 1-2)
Understand the implementation and time/space complexity of fundamental data structures (arrays, linked lists, trees, graphs) and algorithms (sorting, searching). Work through textbook problems and visualize concepts for clarity.
Tools & Resources
VisuAlgo, InterviewBit, books like ''''Cracking the Coding Interview'''', YouTube tutorials on DSA
Career Connection
DSA is crucial for competitive programming, excelling in technical interviews at product-based companies, and developing optimized software solutions, leading to better career prospects.
Engage in Peer Learning & Collaborative Projects- (Semester 1-2)
Form study groups with classmates to discuss difficult topics, solve problems together, and collaborate on small academic projects. This approach enhances understanding, sharpens problem-solving skills, and builds essential teamwork abilities.
Tools & Resources
GitHub (for version control), Discord/WhatsApp groups, college labs, shared online whiteboards
Career Connection
Teamwork and collaboration are highly valued in the industry. Early exposure to group projects simulates real-world development environments, making graduates more job-ready.
Intermediate Stage
Gain Practical Exposure through Internships- (Semester 3-5)
Actively seek out and apply for internships (paid or unpaid) during summer or semester breaks. Focus on gaining hands-on experience in areas like web development, database management, or software testing to apply classroom knowledge.
Tools & Resources
LinkedIn, Internshala, company career pages, college placement cell
Career Connection
Internships provide invaluable real-world experience, help build a professional network, and often lead to pre-placement offers, significantly boosting career prospects and practical skill development.
Develop Specialised Skills via Electives & Certifications- (Semester 3-5)
Choose elective courses strategically based on emerging industry trends (AI, Machine Learning, Data Science, Cloud Computing). Supplement classroom learning with online certifications in your chosen niche to deepen expertise.
Tools & Resources
Coursera, Udemy, NPTEL, edX, industry-recognized certifications (e.g., AWS Certified Cloud Practitioner)
Career Connection
Specialization makes you more competitive in specific job markets and demonstrates proactive learning, essential for niche roles and higher salaries in the dynamic Indian tech sector.
Participate in Hackathons & Coding Competitions- (Semester 3-5)
Actively participate in intra-college, inter-college, and national hackathons or coding competitions. These events challenge problem-solving skills, foster innovation, and provide excellent networking opportunities with peers and industry experts.
Tools & Resources
Major hackathon platforms (Devpost, HackerEarth), college tech clubs, industry sponsored events
Career Connection
Winning or even participating effectively provides valuable resume points, exposure to industry problems, and a chance to impress potential employers, enhancing your employability.
Advanced Stage
Execute a Strong Final Year Project- (Semester 6)
Choose a challenging and industry-relevant project topic. Focus on creating a functional prototype with robust documentation, showcasing your acquired skills. Collaborate with faculty or industry mentors for guidance.
Tools & Resources
GitHub, project management tools (Jira, Trello), academic papers, technical documentation
Career Connection
A well-executed project is a powerful portfolio piece that demonstrates practical skills, problem-solving abilities, and domain knowledge to recruiters, significantly aiding placement.
Intensive Placement Preparation- (Semester 6)
Begin mock interviews (technical and HR), practice aptitude tests, and refine your resume and LinkedIn profile. Focus on developing strong communication and presentation skills, crucial for job interviews.
Tools & Resources
College placement cell, online aptitude test platforms, interview preparation guides, LinkedIn for professional networking
Career Connection
Thorough preparation increases the likelihood of securing good placements in reputable companies, leading to a smooth and successful transition from academics to the professional world.
Network and Build a Professional Presence- (Semester 6 and post-graduation)
Attend industry seminars, workshops, and career fairs. Connect with alumni and professionals in your target fields on platforms like LinkedIn. Showcase your projects and skills online through a portfolio or GitHub.
Tools & Resources
LinkedIn, professional conferences, university alumni network, personal portfolio website/GitHub
Career Connection
Networking opens doors to job opportunities, mentorship, and helps you stay updated with industry trends, which is crucial for long-term career growth and professional advancement.
Program Structure and Curriculum
Eligibility:
- A candidate who has passed 10+2 examination with Mathematics as one of the subjects with 50% marks in aggregate or equivalent examination shall be eligible.
Duration: 3 years / 6 semesters
Credits: 120 Credits
Assessment: Internal: 10% for theory papers (based on assignments, attendance, etc.), 0% for practical papers, External: 90% for theory papers (end-semester examination), 100% for practical papers (end-semester examination)
Semester-wise Curriculum Table
Semester 1
| Subject Code | Subject Name | Subject Type | Credits | Key Topics |
|---|---|---|---|---|
| CS-C1 | Programming Fundamentals using C/C++ | Core Theory | 4 | Introduction to C/C++, Data Types and Operators, Control Flow Statements, Functions and Arrays, Pointers and Structures, File I/O |
| CS-C2 | Computer System Architecture | Core Theory | 4 | Digital Logic Circuits, Combinational and Sequential Circuits, CPU Organization, Memory Hierarchy, I/O Organization, Instruction Sets |
| CS-C3 | Mathematical Foundation for Computer Science | Core Theory | 4 | Set Theory, Relations and Functions, Propositional Logic, Graph Theory, Combinatorics, Recurrence Relations |
| CS-C4 | Data Structures | Core Theory | 4 | Arrays and Linked Lists, Stacks and Queues, Trees (Binary, AVL, B-Trees), Graphs and Graph Traversal, Sorting and Searching Algorithms, Hashing |
| CS-C5P | Programming Lab (C/C++) | Core Practical | 2 | C/C++ Programming Exercises, Control Structures Implementation, Array and String Manipulation, Pointers and Functions, File Handling, Basic Algorithm Implementation |
| CS-C6P | Data Structures Lab | Core Practical | 2 | Implementation of Stacks and Queues, Linked List Operations, Tree Traversal Algorithms, Graph Algorithms (DFS, BFS), Sorting and Searching Algorithms Implementation, Hashing Techniques |
Semester 2
| Subject Code | Subject Name | Subject Type | Credits | Key Topics |
|---|---|---|---|---|
| CS-C7 | Object Oriented Programming using C++ | Core Theory | 4 | OOP Concepts (Classes, Objects), Inheritance and Polymorphism, Encapsulation and Abstraction, Constructors and Destructors, Virtual Functions and Templates, Exception Handling |
| CS-C8 | Operating Systems | Core Theory | 4 | OS Functions and Types, Process Management and Scheduling, Deadlocks, Memory Management, File Systems, I/O Management |
| CS-C9 | Discrete Mathematics | Core Theory | 4 | Graph Theory, Trees and Spanning Trees, Recurrence Relations, Boolean Algebra, Mathematical Logic, Combinatorics |
| CS-C10 | Database Management Systems | Core Theory | 4 | DBMS Architecture, ER Model, Relational Model and Algebra, SQL Queries, Normalization, Transaction Management |
| CS-C11P | Object Oriented Programming Lab (C++) | Core Practical | 2 | C++ Class and Object Implementation, Inheritance and Polymorphism Examples, Operator Overloading, File I/O in C++, Template Programming, Exception Handling Practices |
| CS-C12P | Database Management Systems Lab | Core Practical | 2 | SQL DDL and DML Commands, Database Design and ER Diagrams, Joins and Subqueries, Views and Stored Procedures, Normalization Examples, Transaction Control Language |
Semester 3
| Subject Code | Subject Name | Subject Type | Credits | Key Topics |
|---|---|---|---|---|
| CS-C13 | Computer Networks | Core Theory | 4 | Network Models (OSI, TCP/IP), Physical and Data Link Layer, Network Layer Protocols (IP, Routing), Transport Layer (TCP, UDP), Application Layer Protocols (HTTP, DNS), Network Security Basics |
| CS-C14 | Design and Analysis of Algorithms | Core Theory | 4 | Algorithm Analysis and Complexity, Divide and Conquer, Greedy Algorithms, Dynamic Programming, Backtracking and Branch & Bound, NP-Completeness |
| CS-C15 | Web Programming | Core Theory | 4 | HTML and CSS, JavaScript Fundamentals, DOM Manipulation, XML and JSON, Server-Side Scripting (PHP/ASP.NET/Python Basics), Web Services |
| CS-C16 | Software Engineering | Core Theory | 4 | Software Life Cycle Models, Requirements Engineering, Software Design Principles, Software Testing Techniques, Software Maintenance, Software Project Management |
| CS-C17P | Web Programming Lab | Core Practical | 2 | HTML and CSS Page Design, JavaScript Interactive Elements, DOM Manipulation Exercises, XML and JSON Parsing, Server-Side Scripting Implementations, Database Connectivity for Web |
| CS-C18P | Algorithm Design Lab | Core Practical | 2 | Implementation of Sorting Algorithms, Graph Traversal Algorithms, Greedy and Dynamic Programming Problems, Backtracking Solutions, Time Complexity Analysis of Algorithms, Data Structure-based Problem Solving |
Semester 4
| Subject Code | Subject Name | Subject Type | Credits | Key Topics |
|---|---|---|---|---|
| CS-C19 | Artificial Intelligence | Core Theory | 4 | Introduction to AI, Problem Solving by Search, Knowledge Representation, Logical Reasoning, Machine Learning Basics, Natural Language Processing Fundamentals |
| CS-C20 | Theory of Computation | Core Theory | 4 | Finite Automata, Regular Expressions, Context-Free Grammars, Pushdown Automata, Turing Machines, Decidability and Undecidability |
| CS-C21 | Computer Graphics | Core Theory | 4 | Graphics Hardware, 2D/3D Transformations, Viewing and Clipping, Projection Techniques, Raster Scan Graphics, Color Models and Illumination |
| CS-C22 | Compiler Design | Core Theory | 4 | Lexical Analysis, Syntax Analysis (Parsing), Semantic Analysis, Intermediate Code Generation, Code Optimization, Target Code Generation |
| CS-C23P | Artificial Intelligence Lab | Core Practical | 2 | Implementation of Search Algorithms, Logic Programming (Prolog/Python), Knowledge Representation Techniques, Simple Expert Systems, Machine Learning Algorithm Basics, AI Problem Solving Examples |
| CS-C24P | Computer Graphics Lab | Core Practical | 2 | Graphics Primitives using OpenGL/C/C++, 2D/3D Transformations Implementation, Line and Circle Drawing Algorithms, Polygon Filling Algorithms, Clipping Algorithms, Interactive Graphics Programming |
Semester 5
| Subject Code | Subject Name | Subject Type | Credits | Key Topics |
|---|---|---|---|---|
| CS-C25 | Data Mining | Core Theory | 4 | Introduction to Data Mining, Data Preprocessing, Data Warehousing and OLAP, Association Rule Mining, Classification Techniques, Clustering Methods |
| CS-DSE1 | Discipline Specific Elective I | Elective Theory | 4 | Student chooses one from: Distributed Systems, Advanced Java Programming, Android Programming, Big Data Analytics, Parallel Computing, Image Processing |
| CS-DSE2 | Discipline Specific Elective II | Elective Theory | 4 | Student chooses one from: Cloud Computing, Software Testing, Information Security, Soft Computing, Machine Learning, Internet of Things |
| CS-SEC1 | Skill Enhancement Course I | Elective Theory | 4 | Student chooses one from: Linux Administration, R Programming, Python Programming, Shell Programming, Web Designing, Scientific Computing |
| CS-C27P | Data Mining Lab | Core Practical | 2 | Data Preprocessing using tools, Implementation of Association Rules, Classification Algorithms (Weka), Clustering Algorithms Implementation, Data Visualization, Predictive Modeling |
Semester 6
| Subject Code | Subject Name | Subject Type | Credits | Key Topics |
|---|---|---|---|---|
| CS-DSE3 | Discipline Specific Elective III | Elective Theory | 4 | Student chooses one from: Computer Vision, Data Science, Deep Learning, Fuzzy Logic and Neural Networks, Optimization Techniques, Cryptography and Network Security |
| CS-DSE4 | Discipline Specific Elective IV | Elective Theory | 4 | Student chooses one from: Digital Forensics, Open Source Technologies, Mobile Computing, Big Data Analytics, Image Processing, Machine Learning |
| CS-SEC2 | Skill Enhancement Course II | Elective Theory | 4 | Student chooses one from: Android App Development, Front End Development (HTML, CSS, JS), Back End Development (PHP, Python, Node.js), Data Visualization, Ethical Hacking, Scientific Computing |
| CS-C28 | Project Work | Core Project | 12 | Problem Identification and Literature Survey, Requirement Analysis and Design, Implementation and Testing, Documentation and Reporting, Project Presentation, Viva-Voce |
