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B-SC in Computer Science at SRM Institute of Science and Technology
Chengalpattu, Tamil Nadu
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About the Specialization
What is Computer Science at SRM Institute of Science and Technology Chengalpattu?
This B.Sc Computer Science program at SRM Institute of Science and Technology focuses on building a strong foundation in computational thinking, programming, and core computer science concepts. It is designed to meet the growing demand for skilled professionals in India''''s rapidly expanding IT sector. The program emphasizes a blend of theoretical knowledge and practical application, preparing students for diverse challenges.
Who Should Apply?
This program is ideal for fresh graduates who have completed 10+2 with a science background and a keen interest in logical problem-solving and technology. It also suits individuals aspiring to enter the software development, data science, or networking fields directly after their undergraduate studies in India. No prior programming experience is strictly required, making it accessible to enthusiastic learners.
Why Choose This Course?
Graduates of this program can expect to secure roles such as Software Developer, Data Analyst, Web Developer, or System Administrator in Indian IT companies. Entry-level salaries typically range from INR 3-6 LPA, with significant growth potential up to INR 10-15 LPA with experience. The curriculum aligns with industry demands, potentially leading to professional certifications in areas like cloud computing or cybersecurity.
Student Success Practices
Foundation Stage
Master Programming Fundamentals- (Semester 1-2)
Develop a solid understanding of C/Python programming logic, data structures, and algorithms. Actively participate in coding challenges to reinforce concepts.
Tools & Resources
HackerRank, LeetCode (easy), CodeChef, GeeksforGeeks, online Python/C++ tutorials
Career Connection
Strong fundamentals are crucial for technical interviews and efficient code development in any IT role.
Cultivate Strong Math & Logic Skills- (Semester 1-2)
Pay close attention to discrete mathematics and digital logic, as these form the bedrock for advanced computer science topics. Practice problem-solving regularly.
Tools & Resources
Khan Academy, NPTEL courses on Discrete Math, Logic puzzles, textbooks
Career Connection
Essential for algorithm design, data analysis, and understanding complex systems, crucial for roles like data scientist or software architect.
Active Learning & Peer Collaboration- (Semester 1-2)
Form study groups, discuss challenging concepts with peers, and teach each other. Engage with professors during office hours for clarification.
Tools & Resources
WhatsApp/Discord study groups, SRMIST''''s academic support services
Career Connection
Enhances communication, teamwork, and problem-solving skills, highly valued in corporate environments.
Intermediate Stage
Build Real-World Projects- (Semester 3-5)
Apply theoretical knowledge from DBMS, OOP, and Web Technologies to build practical projects. Start with simple web applications, mobile apps, or database-driven systems.
Tools & Resources
GitHub for version control, VS Code, MySQL/PostgreSQL, HTML/CSS/JavaScript frameworks (React/Angular)
Career Connection
Project portfolios are critical for showcasing skills to potential employers and gain hands-on experience for internship applications.
Explore Electives and Specializations- (Semester 5)
Carefully choose electives like Data Mining, AI, or Cloud Computing based on career interests. Deep dive into chosen areas through self-study and online courses.
Tools & Resources
Coursera, Udemy, NPTEL, specific elective textbooks and documentation
Career Connection
Allows for early specialization, making students more attractive for niche roles in trending fields like AI/ML or cybersecurity.
Engage in Internships/Workshops- (Summer breaks after Semesters 4 and 5)
Actively seek summer internships or participate in industry-led workshops to gain exposure to professional environments and industry practices.
Tools & Resources
SRMIST placement cell, LinkedIn, Internshala, company career pages
Career Connection
Provides invaluable experience, networking opportunities, and often converts into pre-placement offers or enhances final placement prospects.
Advanced Stage
Focus on Capstone Project & Portfolio- (Semester 6)
Dedicate significant effort to the final year project, aiming for an innovative and impactful solution. Document it thoroughly and present it professionally.
Tools & Resources
Advanced programming languages/frameworks, project management tools (Jira, Trello), LaTeX for documentation
Career Connection
A strong project acts as a major selling point in interviews, demonstrating problem-solving ability, technical skills, and project management.
Intensive Placement Preparation- (Semester 5-6)
Practice aptitude tests, technical rounds, and HR interviews rigorously. Revise core computer science concepts, algorithms, and data structures.
Tools & Resources
Online mock tests (IndiaBix), interview preparation platforms (InterviewBit), company-specific interview experiences
Career Connection
Directly enhances chances of securing desired placements in top-tier companies.
Network and Professional Development- (Throughout the final year)
Attend industry seminars, tech talks, and career fairs. Connect with alumni and industry professionals on platforms like LinkedIn. Consider relevant professional certifications.
Tools & Resources
LinkedIn, industry events, certification bodies (e.g., AWS, Microsoft Azure)
Career Connection
Expands professional network, opens doors to opportunities beyond campus placements, and fosters continuous learning for long-term career growth.
Program Structure and Curriculum
Eligibility:
- Passed 10+2 / HSC / CBSE / ICSE or equivalent examinations with Physics, Chemistry, Mathematics or Computer Science or Biology or Biotechnology as one of the subjects.
Duration: 3 years / 6 semesters
Credits: 140 Credits
Assessment: Internal: 40%, External: 60%
Semester-wise Curriculum Table
Semester 1
| Subject Code | Subject Name | Subject Type | Credits | Key Topics |
|---|---|---|---|---|
| 21LEH101T | English | Core | 3 | Listening skills, Speaking skills, Reading skills, Writing skills, Vocabulary development |
| 21BSM101T | Mathematics - I | Core | 3 | Algebra, Differential Calculus, Integral Calculus, Differential Equations, Vector Calculus |
| 21BSC101P | Computer Lab | Core - Practical | 2 | Windows OS, MS Word, MS Excel, MS PowerPoint, Internet Basics |
| 21BSCS101T | Introduction to Programming | Core | 3 | Programming fundamentals, Variables and data types, Operators and expressions, Control flow statements, Functions |
| 21BSCS102T | Digital Computer Fundamentals | Core | 3 | Number systems, Boolean algebra, Logic gates, Combinational circuits, Sequential circuits |
| 21BSCS103L | Digital Computer Fundamentals Lab | Core - Practical | 1 | Logic gates implementation, Boolean expressions, Adders/Subtractors, Flip-flops, Counters |
Semester 2
| Subject Code | Subject Name | Subject Type | Credits | Key Topics |
|---|---|---|---|---|
| 21LEH201T | Communicative English | Core | 3 | Functional English, Spoken English, Presentation skills, Group discussions, Interview skills |
| 21BSM201T | Mathematics - II | Core | 3 | Matrices, Eigenvalues, Vector spaces, Linear transformations, Numerical Methods |
| 21BSCS201T | Data Structures | Core | 3 | Array, Linked lists, Stacks, Queues, Trees, Graphs |
| 21BSCS202L | Data Structures Lab | Core - Practical | 1 | Array operations, Linked list implementations, Stack and Queue applications, Tree traversals, Graph algorithms |
| 21BSCS203T | Python Programming | Core | 3 | Python basics, Data types, Control flow, Functions, Modules, File I/O |
| 21BSCS204L | Python Programming Lab | Core - Practical | 1 | Python scripting, Data structure implementation in Python, Object-oriented programming in Python, File handling, Web scraping basics |
| 21BSCS205T | Environmental Science and Engineering | Ability Enhancement Compulsory Course | 2 | Ecosystems, Biodiversity, Environmental pollution, Natural resources, Sustainable development |
Semester 3
| Subject Code | Subject Name | Subject Type | Credits | Key Topics |
|---|---|---|---|---|
| 21BSCS301T | Object Oriented Programming with C++ | Core | 3 | OOP concepts, Classes and objects, Inheritance, Polymorphism, Exception handling, Templates |
| 21BSCS302L | Object Oriented Programming with C++ Lab | Core - Practical | 1 | Class and object implementation, Constructor/Destructor, Function overloading, Operator overloading, Inheritance, Polymorphism |
| 21BSCS303T | Database Management Systems | Core | 3 | Database concepts, Relational model, SQL queries, Normalization, Transaction management |
| 21BSCS304L | Database Management Systems Lab | Core - Practical | 1 | DDL/DML commands, SQL queries, Joins, Views, Stored procedures, Trigger implementation |
| 21BSCS305T | Computer Organization and Architecture | Core | 3 | Processor organization, Memory hierarchy, I/O organization, Pipelining, Instruction set architecture |
| 21BSCS306T | Operating Systems | Core | 3 | OS concepts, Process management, CPU scheduling, Memory management, File systems, Deadlocks |
| 21GE301T | Universal Human Values | Generic Elective | 2 | Value education, Ethics, Harmony, Human relationships, Society and nature |
Semester 4
| Subject Code | Subject Name | Subject Type | Credits | Key Topics |
|---|---|---|---|---|
| 21BSCS401T | Java Programming | Core | 3 | Java fundamentals, OOPs in Java, Exception handling, Multithreading, AWT/Swing, JDBC |
| 21BSCS402L | Java Programming Lab | Core - Practical | 1 | Java program development, Applets, GUI applications, Database connectivity, Threading |
| 21BSCS403T | Computer Networks | Core | 3 | Network models, Physical layer, Data link layer, Network layer, Transport layer, Application layer |
| 21BSCS404T | Software Engineering | Core | 3 | Software development life cycle, Requirements engineering, Design principles, Testing, Maintenance, Project management |
| 21BSCS405T | Web Technology | Core | 3 | HTML, CSS, JavaScript, Web servers, Client-side scripting, Server-side scripting basics |
| 21BSCS406L | Web Technology Lab | Core - Practical | 1 | HTML pages, CSS styling, JavaScript interactivity, Forms, Basic PHP/Node.js for server-side |
| 21GE401T | Introduction to Indian Constitution | Generic Elective | 2 | Constitutional history, Fundamental rights, Directive principles, Union government, State government, Judiciary |
Semester 5
| Subject Code | Subject Name | Subject Type | Credits | Key Topics |
|---|---|---|---|---|
| 21BSCS501T | Data Mining | Core | 3 | Data preprocessing, Association rules, Classification, Clustering, Prediction, Data visualization |
| 21BSCS502L | Data Mining Lab | Core - Practical | 1 | Data preprocessing with tools, Association rule mining, Classification algorithms, Clustering algorithms, Data visualization tools |
| 21BSCS503T | Computer Graphics | Core | 3 | Graphics primitives, Transformations, Viewing, Clipping, Projections, Shading |
| 21BSCS504L | Computer Graphics Lab | Core - Practical | 1 | Line drawing algorithms, Circle drawing, 2D/3D transformations, Clipping, Animation basics |
| 21BSCS505T | Artificial Intelligence | Core | 3 | AI concepts, Problem solving, Search algorithms, Knowledge representation, Expert systems, Machine learning overview |
| 21BSCSDE01T | Cloud Computing | Elective (Discipline Specific Elective - DSE) | 3 | Cloud models, Virtualization, Cloud services (IaaS, PaaS, SaaS), Cloud security, Cloud deployment models |
| 21BSCSSE03P | R Programming | Skill Enhancement Course (SEC) | 2 | R basics, Data structures in R, Data manipulation, Data visualization, Statistical modeling, R packages |
Semester 6
| Subject Code | Subject Name | Subject Type | Credits | Key Topics |
|---|---|---|---|---|
| 21BSCS601T | Machine Learning | Core | 3 | Supervised learning, Unsupervised learning, Regression, Classification, Neural networks, Deep learning concepts |
| 21BSCS602L | Machine Learning Lab | Core - Practical | 1 | Implementing ML algorithms, Model training, Hyperparameter tuning, Data preprocessing for ML, Using ML libraries (Scikit-learn) |
| 21BSCS603P | Project | Project | 6 | Project proposal, System design, Implementation, Testing, Documentation, Presentation |
| 21BSCSDE02T | Big Data Analytics | Elective (Discipline Specific Elective - DSE) | 3 | Big Data concepts, Hadoop ecosystem, MapReduce, HDFS, Spark, NoSQL databases |
| 21BSCSDE03T | Internet of Things | Elective (Discipline Specific Elective - DSE) | 3 | IoT architecture, Sensors, Actuators, Communication protocols, IoT platforms, Edge computing |
