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BSC in Computer Science at SSR College of Arts, Commerce and Science
Dadra and Nagar Haveli, Dadra and Nagar Haveli and Daman and Diu
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About the Specialization
What is Computer Science at SSR College of Arts, Commerce and Science Dadra and Nagar Haveli?
This Computer Science program at SSR College of Arts, Commerce and Science focuses on foundational and advanced computing principles. Aligned with the demands of India''''s booming IT sector, it provides a robust curriculum encompassing programming, data management, and emerging technologies. The program aims to cultivate industry-ready professionals with a strong theoretical and practical understanding of computer science concepts.
Who Should Apply?
This program is ideal for fresh graduates seeking entry into the dynamic IT and software development fields. It also suits working professionals aiming to upskill in modern technologies or career changers transitioning into the digital industry. Students with a strong aptitude for problem-solving, logical thinking, and a keen interest in technological advancements will thrive in this curriculum.
Why Choose This Course?
Graduates of this program can expect diverse India-specific career paths, including Software Developer, Data Analyst, Web Developer, System Administrator, and IT Consultant. Entry-level salaries typically range from INR 3-5 LPA, growing significantly with experience and specialized skills. Opportunities abound in product-based companies, IT services firms, and innovative startups across India''''s major tech hubs.
Student Success Practices
Foundation Stage
Master Programming Fundamentals- (Semester 1-2)
Dedicate ample time to practicing C and C++ programming, focusing on logic building, data structures, and object-oriented concepts. Solve at least 3-5 coding problems daily on platforms to solidify understanding and develop problem-solving intuition.
Tools & Resources
HackerRank, LeetCode (easy problems), GeeksforGeeks, online C/C++ compilers, Visual Studio Code
Career Connection
Strong fundamentals are critical for acing technical interviews, contributing effectively to projects, and building efficient software solutions, directly impacting entry-level developer roles and overall career growth.
Develop Strong Analytical Skills- (Semester 1-2)
Engage actively in Discrete Mathematics and Linear Algebra problem-solving. Form study groups to discuss complex topics, focusing on applying theoretical concepts to practical scenarios. Challenge yourself with additional math problems beyond coursework.
Tools & Resources
NPTEL courses, Khan Academy, textbook problem sets, peer study groups, Wolfram Alpha
Career Connection
These analytical skills are essential for understanding advanced algorithms, database optimization, and the mathematical underpinnings of machine learning, crucial for roles in data science and complex software engineering.
Enhance Communication Abilities- (Semester 1-2)
Participate in college workshops on communication skills, mock interviews, and group discussions. Practice public speaking and structured technical writing through presentations and detailed project documentation. Seek feedback on your communication style.
Tools & Resources
Toastmasters-like college clubs, TED Talks for inspiration, Grammarly, presentation tools (PowerPoint, Google Slides)
Career Connection
Effective communication is vital for team collaboration, client interaction, and successful project presentations. Strong communicators are highly valued in the Indian IT industry, making candidates more desirable to employers.
Intermediate Stage
Build Practical Project Portfolio- (Semester 3-5)
Start developing small-to-medium scale projects using Python, Web Technologies (HTML, CSS, JavaScript), and Java. Focus on solving real-world problems or creating functional applications that showcase your learned skills. Document your code well on platforms like GitHub.
Tools & Resources
GitHub for version control, VS Code, Django/Flask (for Python web), Spring Boot (for Java), React/Angular (for front-end)
Career Connection
A strong project portfolio demonstrates practical skills, problem-solving abilities, and initiative, significantly enhancing your resume and increasing your chances for internships and placements in product-based and service companies.
Explore Emerging Technologies via Electives- (Semester 3-5)
Choose Discipline Specific Electives (DSE) and Skill Enhancement Courses (SEC) strategically based on your career interests, whether it is Cloud Computing, Data Science, Mobile Development, or Cybersecurity. Supplement with online courses and certifications in your chosen areas.
Tools & Resources
Coursera, Udemy, Google Cloud/AWS certifications, specific technology documentation, NPTEL online courses
Career Connection
Specializing in high-demand areas makes you competitive for niche roles and potentially higher-paying positions within India''''s rapidly evolving tech landscape. It shows a forward-thinking approach to your career.
Actively Seek Internships and Workshops- (Semester 3-5)
Apply for summer internships at startups or established companies to gain invaluable industry exposure and practical experience. Attend webinars, workshops, and hackathons to network with professionals and learn about current industry trends and practices.
Tools & Resources
Internshala, LinkedIn, college placement cell, industry events (e.g., developer conferences)
Career Connection
Internships often lead to pre-placement offers, build a strong professional network, and provide real-world insights, which are crucial for navigating the Indian job market and securing a promising first job.
Advanced Stage
Intensify Placement Preparation- (Semester 6)
Begin focused preparation for campus placements early in your final year. This includes rigorous practice for aptitude tests, technical interviews covering data structures, algorithms, operating systems, DBMS, and networking, as well as HR rounds. Conduct mock interviews regularly.
Tools & Resources
IndiaBix, LeetCode (medium/hard), InterviewBit, company-specific interview guides, placement training programs
Career Connection
Dedicated and strategic preparation ensures readiness for competitive placement drives, maximizing your chances of securing desirable job offers from top Indian and multinational companies recruiting from your campus.
Undertake a Capstone Project- (Semester 6)
Select a challenging final year project that integrates knowledge from various courses. Aim for innovation or a significant contribution to an existing problem, focusing on complete implementation, detailed documentation, and a professional presentation of your work.
Tools & Resources
Project management tools (Trello, Jira), advanced IDEs, research papers and academic journals, faculty mentorship
Career Connection
A robust capstone project showcases your expertise, problem-solving skills, and ability to deliver a complex solution from conception to completion, making a strong and lasting impression on potential employers.
Develop Professional Networking and Personal Branding- (Semester 6)
Build and maintain a strong LinkedIn profile, connecting with industry professionals, alumni, and recruiters. Actively showcase your projects, skills, and certifications. Participate in career fairs, alumni mentorship programs, and industry events to expand your network.
Tools & Resources
LinkedIn, professional meetups and webinars, college alumni network, personal website/blog
Career Connection
Networking opens doors to hidden job opportunities, valuable mentorship, and career advice, which are crucial for long-term professional development and navigating career transitions in the competitive Indian IT sector.
Program Structure and Curriculum
Eligibility:
- 10+2 (HSC) or equivalent examination with Science stream including Mathematics and English as passing subjects.
Duration: 3 years / 6 semesters
Credits: 132 Credits
Assessment: Internal: 30% (for theory) / 15% (for practical/project), External: 70% (for theory) / 35% (for practical/project)
Semester-wise Curriculum Table
Semester 1
| Subject Code | Subject Name | Subject Type | Credits | Key Topics |
|---|---|---|---|---|
| CSCS101 | Programming in C (Theory) | Core | 4 | Introduction to C Programming, Operators and Expressions, Control Flow Statements, Functions and Arrays, Pointers and Structures, File Handling in C |
| CSCS102 | Relational Database Management System (Theory) | Core | 4 | Database System Concepts, Entity-Relationship (ER) Model, Relational Data Model, Structured Query Language (SQL), Normalization Techniques, Transaction Management |
| CSCS103 | Programming in C (Practical) | Lab | 2 | C Program Implementation, Control Structures Practice, Array and String Operations, Functions and Pointers usage, Structures and Unions, File I/O Exercises |
| CSCS104 | Relational Database Management System (Practical) | Lab | 2 | SQL DDL and DML Commands, Advanced SQL Queries, Joins and Subqueries, Constraints and Views, PL/SQL Basics, Database Design Exercises |
| MACS101 | Discrete Mathematics (Theory) | Core (Mathematics) | 4 | Mathematical Logic, Set Theory and Relations, Functions and Growth of Functions, Graph Theory Fundamentals, Combinatorics and Probability, Recurrence Relations |
| MACS102 | Discrete Mathematics (Practical) | Lab (Mathematics) | 2 | Implementation of Logic Gates, Set Operations using Tools, Graph Traversal Algorithms, Combinatorial Problems, Boolean Algebra Applications |
| ENVS101 | Environmental Studies (Theory) | AEC (Ability Enhancement Course) | 2 | Natural Resources and Their Management, Ecosystems and Biodiversity, Environmental Pollution and Control, Global Environmental Issues, Environmental Ethics and Legislation, Sustainable Development |
| ENVS102 | Environmental Studies (Practical) | AEC (Ability Enhancement Course) | 2 | Environmental Field Work, Case Studies on Environmental Impact, Data Collection on Local Environment, Preparation of Environmental Reports |
Semester 2
| Subject Code | Subject Name | Subject Type | Credits | Key Topics |
|---|---|---|---|---|
| CSCS201 | Data Structures (Theory) | Core | 4 | Introduction to Data Structures, Arrays and Linked Lists, Stacks and Queues, Trees (Binary, BST, AVL), Graphs and Graph Algorithms, Sorting and Searching Techniques |
| CSCS202 | Object Oriented Programming using C++ (Theory) | Core | 4 | Introduction to OOP and C++, Classes, Objects and Constructors, Inheritance and Polymorphism, Abstraction and Encapsulation, Operator Overloading, Templates and Exception Handling |
| CSCS203 | Data Structures (Practical) | Lab | 2 | Implementation of Linked Lists, Stack and Queue Applications, Binary Tree Operations, Graph Traversal Algorithms (BFS, DFS), Sorting Algorithms (Merge, Quick, Heap), Searching Algorithms |
| CSCS204 | Object Oriented Programming using C++ (Practical) | Lab | 2 | C++ Program Development, Class and Object Creation, Inheritance and Virtual Functions, Operator Overloading Examples, File I/O in C++, Templates and STL usage |
| MACS201 | Linear Algebra (Theory) | Core (Mathematics) | 4 | Matrices and Determinants, Systems of Linear Equations, Vector Spaces and Subspaces, Linear Transformations, Eigenvalues and Eigenvectors, Orthogonality and Inner Product Spaces |
| MACS202 | Linear Algebra (Practical) | Lab (Mathematics) | 2 | Matrix Operations using Software, Solving Linear Systems, Vector Space Computations, Eigenvalue/Eigenvector Calculations |
| COMM201 | Communication Skills (Theory) | AEC (Ability Enhancement Course) | 2 | Fundamentals of Communication, Verbal and Non-Verbal Communication, Listening Skills and Barriers, Public Speaking and Presentations, Group Discussions and Meetings, Written Communication |
| COMM202 | Communication Skills (Practical) | AEC (Ability Enhancement Course) | 2 | Role-Playing and Situational Dialogues, Individual and Group Presentations, Group Discussion Practice, Resume and Cover Letter Writing, Interview Skills Simulation |
Semester 3
| Subject Code | Subject Name | Subject Type | Credits | Key Topics |
|---|---|---|---|---|
| CSCS301 | Operating System (Theory) | Core | 4 | Operating System Concepts, Process Management and Scheduling, Inter-process Communication, Deadlocks and Prevention, Memory Management Techniques, File Systems and I/O Systems |
| CSCS302 | Python Programming (Theory) | Core | 4 | Python Language Fundamentals, Data Types and Control Flow, Functions and Modules, Object-Oriented Programming in Python, File Handling and Exception Handling, Libraries (NumPy, Pandas basics) |
| CSCS303 | Operating System (Practical) | Lab | 2 | Linux Command Line Interface, Shell Scripting, Process Creation and Management, Thread Synchronization, Memory Allocation Algorithms |
| CSCS304 | Python Programming (Practical) | Lab | 2 | Python Program Development, Data Structures in Python, Function and Module Implementation, File Operations and Error Handling, OOP Concepts in Python |
| MACS301 | Calculus (Theory) | Core (Mathematics) | 4 | Differential Calculus, Integral Calculus, Sequences and Series, Functions of Several Variables, Vector Calculus Basics |
| MACS302 | Calculus (Practical) | Lab (Mathematics) | 2 | Differentiation and Integration Problems, Graphing Functions using Software, Series Expansion Computations |
| VAC301 | Value Added Course (Theory) | VAC (Value Added Course) | 2 | Introduction to Emerging Technologies, Specific Skill Development Module, Industry Relevant Concepts, Application of Basic Principles |
| VAC302 | Value Added Course (Practical) | VAC (Value Added Course) | 2 | Hands-on Practice for VAC Topic, Mini-Projects for Skill Application, Tool-Based Exercises, Problem Solving Scenarios |
Semester 4
| Subject Code | Subject Name | Subject Type | Credits | Key Topics |
|---|---|---|---|---|
| CSCS401 | Computer Networks (Theory) | Core | 4 | Introduction to Computer Networks, OSI and TCP/IP Models, Data Link Layer Protocols, Network Layer (IP, Routing), Transport Layer (TCP, UDP), Application Layer Protocols |
| CSCS402 | Web Technology (Theory) | Core | 4 | HTML5 and CSS3 Fundamentals, JavaScript for Client-Side Scripting, DOM Manipulation and Events, XML and JSON Technologies, Web Servers and Web Hosting, Introduction to Web Frameworks |
| CSCS403 | Computer Networks (Practical) | Lab | 2 | Network Configuration Exercises, Packet Sniffing using Wireshark, Socket Programming, Routing Protocol Simulation, Network Security Basics |
| CSCS404 | Web Technology (Practical) | Lab | 2 | Website Development using HTML/CSS, JavaScript Interactive Elements, DOM Manipulation Projects, Form Validation, Basic Server-Side Scripting |
| MACS401 | Differential Equations (Theory) | Core (Mathematics) | 4 | First Order Ordinary Differential Equations, Higher Order Linear ODEs, Laplace Transforms, Systems of ODEs, Partial Differential Equations Basics |
| MACS402 | Differential Equations (Practical) | Lab (Mathematics) | 2 | Solving ODEs using Software, Plotting Solutions of Differential Equations, Numerical Methods for ODEs |
| SEC401 | Skill Enhancement Course (Theory) | SEC (Skill Enhancement Course) | 2 | Specialized Skill Introduction, Advanced Software Tools, Problem-Solving Methodologies, Industry Best Practices |
| SEC402 | Skill Enhancement Course (Practical) | SEC (Skill Enhancement Course) | 2 | Hands-on Implementation of SEC Skills, Project-based Learning, Tool-specific Exercises, Real-world Application Scenarios |
Semester 5
| Subject Code | Subject Name | Subject Type | Credits | Key Topics |
|---|---|---|---|---|
| CSCS501 | Data Science with R (Theory) | Core | 4 | Introduction to Data Science, R Programming Fundamentals, Data Manipulation and Cleaning, Exploratory Data Analysis, Statistical Modeling in R, Data Visualization with R |
| CSCS502 | Java Programming (Theory) | Core | 4 | Core Java Concepts, Object-Oriented Programming in Java, Exception Handling and Multithreading, Collections Framework, GUI Programming (AWT/Swing), File I/O and JDBC Connectivity |
| CSCS503 | Data Science with R (Practical) | Lab | 2 | R Scripting for Data Analysis, Data Import and Export, Statistical Test Implementation, Creating Data Visualizations, Basic Machine Learning Models in R |
| CSCS504 | Java Programming (Practical) | Lab | 2 | Java Program Development, GUI Application Building, Database Connectivity using JDBC, Multithreaded Application Development, File Operations in Java |
| DSE-1 | Discipline Specific Elective-1 (Theory) (e.g., Cloud Computing) | Elective | 4 | Introduction to Cloud Computing, Cloud Service Models (IaaS, PaaS, SaaS), Cloud Deployment Models, Virtualization Technology, Introduction to AWS/Azure Services, Cloud Security Fundamentals |
| DSE-2 | Discipline Specific Elective-2 (Practical) (e.g., Cloud Computing) | Elective | 2 | Cloud Service Configuration, Virtual Machine Deployment, Cloud Storage Management, Networking in Cloud, Basic Cloud Monitoring |
| GE-1 | Generic Elective-1 (Theory) (e.g., Mathematics for Machine Learning) | Elective | 2 | Linear Algebra for ML, Probability and Statistics for ML, Calculus for Optimization, Vector Spaces in ML, Matrix Decompositions |
| GE-2 | Generic Elective-2 (Practical) (e.g., Mathematics for Machine Learning) | Elective | 2 | Implementation of Linear Algebra concepts, Statistical Simulations, Optimization Problems using Libraries, Data Preprocessing Techniques |
Semester 6
| Subject Code | Subject Name | Subject Type | Credits | Key Topics |
|---|---|---|---|---|
| CSCS601 | Software Engineering (Theory) | Core | 4 | Software Development Life Cycle, Requirements Engineering, Software Design Principles, Software Testing and Quality Assurance, Project Management and Risk Management, Software Maintenance |
| CSCS602 | Big Data Analytics (Theory) | Core | 4 | Introduction to Big Data, Hadoop Ecosystem (HDFS, MapReduce), Apache Spark, NoSQL Databases, Data Warehousing Concepts, Introduction to Data Mining |
| CSCS603 | Software Engineering (Practical) | Lab | 2 | UML Diagram Creation (Use Case, Class), Software Requirement Specification, Test Case Design, Project Planning Tools, Version Control System Usage |
| CSCS604 | Big Data Analytics (Practical) | Lab | 2 | Hadoop Command Line Interface, MapReduce Programming, Spark Application Development, Hive Queries, NoSQL Database Operations |
| DSE-3 | Discipline Specific Elective-3 (Theory) (e.g., Machine Learning) | Elective | 4 | Introduction to Machine Learning, Supervised Learning (Regression, Classification), Unsupervised Learning (Clustering), Neural Networks and Deep Learning Basics, Model Evaluation and Validation, Ensemble Methods |
| DSE-4 | Discipline Specific Elective-4 (Practical) (e.g., Machine Learning) | Elective | 2 | Implementing Regression Models, Classification Algorithm Development, Clustering Techniques using Python, Neural Network Implementation, Feature Engineering |
| CSCS605 | Project | Project | 4 | Problem Identification and Analysis, System Design and Architecture, Implementation and Coding, Testing and Debugging, Documentation and Report Writing, Project Presentation and Viva |
| CSCS606 | Internship / Skill Based Elective (SBE) | Internship/SBE | 2 | Practical Industry Experience, Advanced Skill Development, Corporate Environment Exposure, Specific Technology Training, Problem Solving in Real-world Contexts |
