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B-SC-PHYSICAL-SCIENCES-COMPUTER-SCIENCE in Computer Science at Atma Ram Sanatan Dharma College
Delhi, Delhi
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About the Specialization
What is Computer Science at Atma Ram Sanatan Dharma College Delhi?
This B.Sc (Physical Sciences) Computer Science program at Atma Ram Sanatan Dharma College, affiliated with the University of Delhi, focuses on building a strong foundation in computer science principles alongside a robust scientific background. It integrates theoretical knowledge with practical skills essential for the evolving Indian IT sector. The program emphasizes problem-solving, algorithmic thinking, and modern programming paradigms, preparing students for diverse technological roles. This interdisciplinary approach sets it apart, catering to the growing demand for scientifically-literate computer professionals in India.
Who Should Apply?
This program is ideal for high school graduates with a strong aptitude for science and mathematics, aspiring to build a career in technology. It is suitable for those seeking a rigorous academic foundation before pursuing higher studies or direct entry into entry-level tech roles. Fresh graduates interested in software development, data analysis, or IT support will find this course beneficial. Students transitioning from other science streams looking to acquire core computing skills for interdisciplinary roles are also well-suited for this program.
Why Choose This Course?
Graduates of this program can expect to secure roles as junior software developers, data analysts, IT support specialists, or web developers in various Indian companies, from startups to large MNCs. Entry-level salaries typically range from INR 3 LPA to 6 LPA, with significant growth potential up to INR 10-15 LPA with experience. The scientific grounding also opens doors to research assistant positions or further studies in computational science. The curriculum aligns with foundational knowledge required for popular industry certifications in programming and databases.
Student Success Practices
Foundation Stage
Master Programming Fundamentals with Python- (Semester 1-2)
Dedicate significant time to thoroughly understand Python''''s core concepts (data types, control structures, functions) and practice extensively. Solve at least 2-3 coding problems daily on platforms like HackerRank or LeetCode to build logical thinking and problem-solving skills. Collaborate with peers on small coding projects.
Tools & Resources
Python IDLE/Jupyter Notebook, GeeksforGeeks for tutorials, HackerRank/LeetCode for practice
Career Connection
Strong Python fundamentals are crucial for entry-level developer roles, scripting, data analysis, and form the base for advanced machine learning concepts, significantly boosting placement prospects.
Build a Strong Data Structures Base- (Semester 1-2)
Focus on understanding the implementation and applications of fundamental data structures like arrays, linked lists, stacks, queues, and trees. Practice implementing these structures in Python and solving problems that require their efficient use. Participate in competitive programming challenges to enhance problem-solving speed.
Tools & Resources
Textbooks (e.g., ''''Data Structures and Algorithms in Python''''), Online courses on Coursera/Udemy, CodeChef/TopCoder for problem-solving
Career Connection
Proficiency in data structures and algorithms is a mandatory skill for technical interviews at almost all software companies, directly impacting internship and job offers.
Engage in Peer Learning and Collaborative Projects- (Semester 1-2)
Form study groups to discuss complex topics, clarify doubts, and work on small academic projects together. Present concepts to each other to solidify understanding and improve communication. Actively participate in hackathons or coding clubs within the college or university to apply skills.
Tools & Resources
GitHub for version control, Google Meet/Zoom for virtual collaboration, College coding clubs
Career Connection
Develops teamwork, communication, and problem-solving skills highly valued in the industry. Contributes to a project portfolio for placements and networking opportunities.
Intermediate Stage
Deep Dive into Database Management- (Semester 3-4)
Go beyond basic SQL queries by learning advanced concepts like normalization, indexing, transaction management, and stored procedures. Work on a project involving database design and implementation for a real-world scenario, using popular systems like MySQL or PostgreSQL.
Tools & Resources
MySQL/PostgreSQL, phpMyAdmin/pgAdmin, Online tutorials and official documentation
Career Connection
Database skills are essential for backend development, data engineering, and data analysis roles across all industries. Practical project experience makes you more employable.
Explore Operating Systems and Computer Architecture- (Semester 3-4)
Understand the core principles of how computers and operating systems work, including memory management, process scheduling, and I/O. Consider exploring Linux commands and basic shell scripting. This provides a fundamental understanding crucial for system-level programming and cybersecurity roles.
Tools & Resources
Linux operating system (Ubuntu/Fedora), Command-line interface tutorials, Textbooks on OS and Computer Architecture
Career Connection
Crucial for understanding system performance, debugging, and cybersecurity, leading to roles in system administration, embedded systems, and security analysis in various tech firms.
Undertake Mini-Projects and Internships- (Semester 3-5)
Start building small, self-initiated projects in areas of interest (e.g., a simple web application, a data analysis script, a small game). Seek out summer internships, even unpaid ones, to gain practical industry exposure and apply classroom knowledge in a professional setting. Utilize the college''''s placement cell for opportunities.
Tools & Resources
GitHub for project showcases, LinkedIn for networking and opportunities, College placement cell
Career Connection
Practical projects and internships significantly boost your resume, providing real-world experience and networking opportunities, which are critical for placements.
Advanced Stage
Specialize through Electives and Advanced Projects- (Semester 5-6)
Carefully choose Computer Science DSEs that align with your career interests (e.g., AI, Web Programming, Networks). Undertake a significant final-year project that showcases your chosen specialization, applying advanced concepts and tools. Aim for projects that solve a real-world problem or explore a novel idea.
Tools & Resources
Domain-specific libraries/frameworks (e.g., TensorFlow for AI, Django/Flask for web), Mentors from academia or industry, Research papers
Career Connection
A strong final-year project tailored to a specialization makes you highly attractive to employers in that specific domain and demonstrates advanced problem-solving skills.
Intensive Placement Preparation- (Semester 5-6)
Beyond academics, focus on developing soft skills like communication, presentation, and interview etiquette. Prepare a compelling resume and cover letter tailored to specific job descriptions. Practice mock interviews, including technical and HR rounds, with peers or mentors to refine responses.
Tools & Resources
Placement Cell workshops, Online interview preparation platforms (e.g., Pramp, InterviewBit), LinkedIn for company research
Career Connection
Comprehensive preparation is key to successfully converting internship and job offers during campus placements or off-campus recruitment drives in competitive Indian job markets.
Network and Build Professional Presence- (Semester 5-6)
Attend industry seminars, webinars, and conferences related to your specialization. Connect with alumni and professionals on platforms like LinkedIn. Create a professional online portfolio or personal website to showcase your projects and skills. Consider pursuing relevant professional certifications to stand out.
Tools & Resources
LinkedIn, GitHub, Personal website platforms (e.g., GitHub Pages, Portfoliobox), NPTEL/Coursera for certifications
Career Connection
Networking opens doors to hidden job opportunities, mentorship, and keeps you informed about industry demands, accelerating career growth in the dynamic Indian tech landscape.
Program Structure and Curriculum
Eligibility:
- Passed 10+2 (or equivalent) examination with a minimum aggregate of 45% marks. Candidate must have appeared in CUET (UG) with a combination of one Language from List A, Physics from List B1, Mathematics from List B1, and Chemistry/Computer Science/Informatics Practices from List B1/B2.
Duration: 3 years (6 semesters)
Credits: 132 (as per DU''''s UGCF 2022 guidelines for 3-year multidisciplinary programs) Credits
Assessment: Internal: 30%, External: 70%
Semester-wise Curriculum Table
Semester 1
| Subject Code | Subject Name | Subject Type | Credits | Key Topics |
|---|---|---|---|---|
| DSC-1A | Programming Using Python | Discipline Specific Core (Computer Science) | 4 | Introduction to Python and IDLE, Data Types, Operators, Expressions, Control Flow (Conditional and Iterative), Functions, Modules, Packages, Strings, Lists, Tuples, Dictionaries, File Handling and Exceptions |
Semester 2
| Subject Code | Subject Name | Subject Type | Credits | Key Topics |
|---|---|---|---|---|
| DSC-1B | Data Structures | Discipline Specific Core (Computer Science) | 4 | Arrays and Pointers, Stacks and Queues, Linked Lists (Singly, Doubly, Circular), Trees (Binary, BST, AVL, B-Trees), Graphs (Representation, Traversal), Sorting, Searching, Hashing Techniques |
Semester 3
| Subject Code | Subject Name | Subject Type | Credits | Key Topics |
|---|---|---|---|---|
| DSC-1C | Computer System Architecture | Discipline Specific Core (Computer Science) | 4 | Digital Logic Circuits, Combinational and Sequential Circuits, Register Transfer and Microoperations, Basic Computer Organization and Design, Central Processing Unit (CPU) Design, Input-Output Organization, Memory Hierarchy |
Semester 4
| Subject Code | Subject Name | Subject Type | Credits | Key Topics |
|---|---|---|---|---|
| DSC-1D | Database Management Systems | Discipline Specific Core (Computer Science) | 4 | Introduction to DBMS and Data Models, Entity-Relationship (ER) Model, Relational Model and Algebra, Structured Query Language (SQL), Normalization and Dependency Theory, Transaction Management, Concurrency Control |
Semester 5
| Subject Code | Subject Name | Subject Type | Credits | Key Topics |
|---|---|---|---|---|
| DSE-CS-Pool | Computer Science Discipline Specific Elective (DSE-1) | Elective (Computer Science) | 4 | Students choose one DSE from a university-defined pool. Examples include Operating Systems, Introduction to Web Programming, Android Programming, Software Engineering, Introduction to Data Science, Artificial Intelligence, Computer Networks, Computer Graphics., Specific topics depend on chosen elective, e.g., ''''Process Management, Memory Management, File Systems'''' for Operating Systems. |
| SEC-CS-Pool | Computer Science Skill Enhancement Course (SEC-1) | Skill Enhancement Course (Elective) | 3 | Students choose SECs from a university-defined pool. Examples related to CS include Python Programming, R Programming, HTML and CSS, Data Analysis using Spreadsheets, Unix/Linux Programming, Mobile Application Development, Cyber Security., Specific topics depend on chosen SEC, e.g., ''''Bash scripting, File permissions, Process management'''' for Unix/Linux Programming. |
Semester 6
| Subject Code | Subject Name | Subject Type | Credits | Key Topics |
|---|---|---|---|---|
| DSE-CS-Pool | Computer Science Discipline Specific Elective (DSE-2) | Elective (Computer Science) | 4 | Students choose another DSE from the remaining university-defined pool not taken in Semester 5. Exact choice varies by student interest and college offering., Specific topics depend on chosen elective, e.g., ''''Threats, Vulnerabilities, Cryptography, Network Security'''' for a Cyber Security DSE. |
| SEC-CS-Pool | Computer Science Skill Enhancement Course (SEC-2) | Skill Enhancement Course (Elective) | 3 | Students choose additional SECs from the university-defined pool. Exact choice varies by student interest and college offering., Specific topics depend on chosen SEC, e.g., ''''User interface design, Event handling, Data storage'''' for Mobile Application Development. |
| VAC-CS-Pool | Computer Science Value Addition Course (VAC-1) | Value Addition Course (Elective, CS-related) | 2 | Students choose VACs from a university-defined pool. Examples related to CS include Digital Empowerment, Design Thinking., Specific topics depend on chosen VAC, e.g., ''''Digital literacy, Online safety, Government services'''' for Digital Empowerment. |
