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B-SC in Computer Science at Mahila Seva Sadan P.G. College, Prayagraj
Prayagraj, Uttar Pradesh
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About the Specialization
What is Computer Science at Mahila Seva Sadan P.G. College, Prayagraj Prayagraj?
This Computer Science program at Mahila Seva Sadan Post Graduate College focuses on building a strong foundation in core computational principles and modern programming techniques, aligning with the New Education Policy 2020 framework. It emphasizes practical skills crucial for the rapidly evolving Indian tech industry, where demand for skilled computer science graduates is consistently high across sectors like IT services, product development, and digital innovation. The program is designed to create job-ready professionals equipped with theoretical knowledge and hands-on experience.
Who Should Apply?
This program is ideal for 10+2 Science graduates with a keen interest in programming, problem-solving, and technology. It caters to aspiring software developers, data analysts, web developers, and IT support professionals looking to enter the dynamic Indian tech landscape. It''''s also suitable for individuals seeking a robust academic background before pursuing higher education like MCA or M.Sc. in Computer Science, or those aiming to build a career in technology-driven startups and established IT firms.
Why Choose This Course?
Graduates of this program can expect to secure entry-level positions in prominent Indian IT companies and startups, with typical starting salaries ranging from INR 2.5 LPA to 5 LPA, potentially increasing with experience and specialized skills. Career paths include Junior Developer, Software Tester, Web Designer, Database Administrator, and IT Support Engineer. The program lays a strong groundwork for pursuing advanced certifications in cloud computing, data science, or cybersecurity, enhancing growth trajectories in fast-growing Indian tech hubs.
Student Success Practices
Foundation Stage
Master Programming Fundamentals- (Semester 1-2)
Dedicate time to thoroughly understand C programming and data structures. Practice daily coding problems on platforms like HackerRank or GeeksforGeeks to solidify concepts and improve logical thinking.
Tools & Resources
GeeksforGeeks, HackerRank, Online C compilers, Textbooks like ''''Let Us C'''' by Yashavant Kanetkar
Career Connection
Strong fundamentals are essential for cracking initial technical interviews and excelling in subsequent advanced programming courses and industry projects.
Build a Strong Academic Network- (Semester 1-2)
Actively participate in study groups, peer-to-peer learning sessions, and college technical clubs. Collaborate on assignments and mini-projects to learn from diverse perspectives and enhance problem-solving skills.
Tools & Resources
College technical societies, WhatsApp/Telegram study groups
Career Connection
Networking with peers and seniors provides insights into career paths, internship opportunities, and collaborative project experience, crucial for teamwork in the industry.
Develop Foundational Computer Skills- (Semester 1-2)
Beyond programming, ensure proficiency in basic computer applications like MS Office (Word, Excel, PowerPoint) and operating systems. Understand file management and basic troubleshooting, which are often overlooked but vital in any professional setting.
Tools & Resources
Microsoft Office Suite, Online tutorials for MS Office basics
Career Connection
These basic skills are prerequisites for almost all entry-level jobs and help in efficient documentation and presentation during academic and professional life.
Intermediate Stage
Engage in Project-Based Learning- (Semester 3-4)
Actively seek opportunities to build small projects using technologies learned (e.g., C++, DBMS, Web Designing). Focus on solving real-world problems, even on a small scale, to apply theoretical knowledge.
Tools & Resources
GitHub for version control, VS Code/Eclipse IDE, Local server environments (XAMPP)
Career Connection
Projects are your portfolio. They demonstrate practical application of skills to potential employers and are critical for showcasing capabilities during internships and placements.
Explore Open Source Contributions- (Semester 4-5)
Start exploring open-source projects relevant to your interests. Even small contributions, bug fixes, or documentation improvements can provide valuable exposure to industry-standard coding practices and team collaboration.
Tools & Resources
GitHub, GitLab, Contribution guides of open-source projects
Career Connection
Contributing to open source builds a public profile, exposes you to real-world codebases, and can be a significant highlight on your resume for tech roles.
Attend Workshops and Tech Talks- (Semester 3-5)
Participate in college-organized workshops, seminars, and tech talks on emerging technologies like Python, AI, or Cloud Computing. These events provide insights into industry trends and new skill requirements.
Tools & Resources
College event calendars, Online tech communities, YouTube channels of tech conferences
Career Connection
Staying updated with technology trends and networking with speakers/attendees can lead to mentorship opportunities and help in identifying specialized career paths and job openings.
Advanced Stage
Focus on Advanced Specialization- (Semester 5-6)
Choose advanced topics like AI, Machine Learning, or Cyber Security as a focused area. Pursue online courses (e.g., NPTEL, Coursera) or certifications to build depth in a chosen niche.
Tools & Resources
NPTEL courses, Coursera/edX for specialized certifications, Kaggle for data science
Career Connection
Specialized skills are highly valued in the Indian job market, offering better salary prospects and roles in niche tech domains, providing a competitive edge during placements.
Intensive Placement Preparation- (Semester 6)
Begin rigorous preparation for campus placements, including aptitude tests, group discussions, technical interview rounds, and HR interviews. Practice mock interviews and brush up on core CS subjects.
Tools & Resources
IndiaBix for aptitude, LeetCode for coding, Mock interview platforms
Career Connection
Dedicated and structured preparation significantly increases the chances of securing desirable job offers from leading Indian IT companies and startups during the recruitment drives.
Undertake a Capstone Project/Internship- (Semester 6)
Work on a significant capstone project (either academic or an industry internship) that integrates knowledge from multiple subjects. Focus on delivering a tangible, functional product or solution.
Tools & Resources
Industry internship opportunities, College project guidance, Freelancing platforms (for experience)
Career Connection
A strong capstone project or a relevant internship provides invaluable real-world experience, acts as a powerful talking point in interviews, and can often lead to pre-placement offers.
Program Structure and Curriculum
Eligibility:
- No eligibility criteria specified
Duration: 3 years (6 semesters) for UG Degree; 4 years (8 semesters) for UG Degree with Research
Credits: 132 credits (for 3-year UG Degree in Science Stream as per NEP-2020) Credits
Assessment: Internal: 25%, External: 75%
Semester-wise Curriculum Table
Semester 1
Semester 2
| Subject Code | Subject Name | Subject Type | Credits | Key Topics |
|---|---|---|---|---|
| CS-T-102 | Data Structures & Algorithms | Core (Major) | 4 | Introduction to Data Structures, Arrays, Stacks, Queues, Linked Lists and their types, Trees (Binary, AVL, B-trees), Graphs and Graph Traversal, Searching and Sorting Algorithms |
| CS-P-102 | Data Structures & Algorithms Lab using C++ | Practical (Major) | 2 | Implementation of Stacks, Queues, Linked Lists, Tree traversal algorithms, Graph representation and traversal, Bubble, Selection, Insertion, Merge Sort, Linear and Binary Search |
Semester 3
| Subject Code | Subject Name | Subject Type | Credits | Key Topics |
|---|---|---|---|---|
| CS-T-201 | Object Oriented Programming using C++ | Core (Major) | 4 | OOP Concepts (Classes, Objects, Encapsulation), Constructors, Destructors, Copy Constructor, Inheritance and its types, Polymorphism (Function Overloading, Virtual Functions), Operator Overloading and Friend Functions, Templates and Exception Handling |
| CS-P-201 | Object Oriented Programming Lab using C++ | Practical (Major) | 2 | Class and object definition programs, Inheritance and runtime polymorphism, Operator overloading implementation, File I/O and template programming, Exception handling mechanisms |
| CS-T-202 | Operating System | Core (Major) | 4 | Introduction to Operating Systems, Process Management and CPU Scheduling, Deadlocks and Prevention, Memory Management (Paging, Segmentation), Virtual Memory and Demand Paging, File Systems and I/O Systems |
| CS-P-202 | Operating System Lab | Practical (Major) | 2 | Shell scripting exercises, Process creation and synchronization, CPU scheduling algorithm simulations, Memory allocation strategies, Disk scheduling algorithms |
Semester 4
| Subject Code | Subject Name | Subject Type | Credits | Key Topics |
|---|---|---|---|---|
| CS-T-203 | Database Management System | Core (Major) | 4 | Introduction to DBMS and Data Models, Entity-Relationship (ER) Model, Relational Model and Relational Algebra, Structured Query Language (SQL), Normalization and Dependency Theory, Transaction Management and Concurrency Control |
| CS-P-203 | DBMS Lab | Practical (Major) | 2 | DDL, DML, DCL commands in SQL, Table creation and data manipulation, Joining tables and subqueries, Views, Stored Procedures, and Triggers, Database design and implementation |
| CS-T-204 | Web Designing | Core (Major) | 4 | Introduction to Web Technologies, HTML5 Structure and Semantics, CSS3 Styling and Layouts, JavaScript Fundamentals and DOM Manipulation, Responsive Web Design and Bootstrap Framework, XML and AJAX basics |
| CS-P-204 | Web Designing Lab | Practical (Major) | 2 | Creating static web pages with HTML, Styling web pages with CSS, Adding interactivity with JavaScript, Implementing responsive designs, Form validation and dynamic content |
Semester 5
| Subject Code | Subject Name | Subject Type | Credits | Key Topics |
|---|---|---|---|---|
| CS-T-301 | Computer Network | Core (Major) | 4 | Introduction to Computer Networks, Network Topologies and OSI Model, TCP/IP Protocol Suite, Data Link Layer and MAC Addressing, Network Layer (IP Addressing, Routing), Transport Layer (TCP, UDP) and Application Layer Protocols |
| CS-P-301 | Computer Network Lab | Practical (Major) | 2 | Network configuration using commands, IP addressing and subnetting, Socket programming (Client-Server), Packet analysis using Wireshark, Network topology setup and testing |
| CS-T-302 | Introduction to Python Programming | Core (Major) | 4 | Python Language Fundamentals, Data Types, Operators, Control Flow, Functions, Modules, and Packages, Lists, Tuples, Dictionaries, Sets, File Input/Output Operations, Object-Oriented Programming in Python |
| CS-P-302 | Python Programming Lab | Practical (Major) | 2 | Developing basic Python scripts, Working with built-in data structures, Implementing functions and modules, File handling operations, Building small object-oriented programs |
Semester 6
| Subject Code | Subject Name | Subject Type | Credits | Key Topics |
|---|---|---|---|---|
| CS-T-303 | Software Engineering | Core (Major) | 4 | Software Development Life Cycle (SDLC), Software Requirements Engineering, Software Design Principles and Patterns, Software Testing Techniques, Software Maintenance and Configuration Management, Software Project Management and Agile Methodologies |
| CS-P-303 | Software Engineering Lab | Practical (Major) | 2 | Requirement elicitation and documentation, UML diagrams for system design, Test case generation and execution, Version control system usage (Git), Project planning and tracking tools |
| CS-T-304 | Artificial Intelligence | Core (Major) | 4 | Introduction to AI and its applications, Problem Solving Agents and Search Algorithms, Knowledge Representation and Reasoning, Introduction to Machine Learning, Expert Systems and Fuzzy Logic, Natural Language Processing basics |
| CS-P-304 | AI Lab | Practical (Major) | 2 | Implementation of search algorithms (BFS, DFS), Prolog programming for knowledge representation, Using Python libraries for ML (Scikit-learn), Developing small AI-based applications, Exploring natural language processing tools |
