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B-SC-HONS in Computer Science at University of Delhi
Delhi, Delhi
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About the Specialization
What is Computer Science at University of Delhi Delhi?
This B.Sc. (Hons.) Computer Science program at the University of Delhi focuses on building a robust foundation in theoretical and applied computer science. It covers core computing principles, algorithms, data structures, and modern applications, preparing students for the dynamic Indian IT industry. The curriculum emphasizes problem-solving and analytical thinking, aligning with the high demand for skilled tech professionals in India''''s booming digital economy. Its comprehensive approach aims to differentiate graduates in a competitive job market.
Who Should Apply?
This program is ideal for fresh graduates from Class 12th with a strong aptitude for Mathematics and an interest in logical problem-solving and technology. It attracts aspiring software developers, data analysts, network administrators, and cybersecurity enthusiasts. Working professionals looking to acquire fundamental computer science skills or career changers transitioning into the IT industry will find the rigorous curriculum beneficial, provided they meet the prerequisite academic background.
Why Choose This Course?
Graduates of this program can expect diverse career paths in software development, IT consulting, data science, and cybersecurity within India. Entry-level salaries typically range from 4-8 LPA, with experienced professionals earning 8-20+ LPA in prominent Indian tech hubs. The program provides a strong academic base for pursuing higher education like M.Sc. Computer Science or MCA, and aligns with various professional certifications required by Indian companies, fostering significant growth trajectories.
Student Success Practices
Foundation Stage
Master Programming Fundamentals- (Semester 1-2)
Dedicate consistent time to practice core programming concepts in Python and C++, focusing on syntax, logic, and basic problem-solving. Utilize online platforms to solve daily coding challenges to solidify understanding.
Tools & Resources
HackerRank, CodeChef, GeeksforGeeks, Online Python/C++ compilers
Career Connection
Strong programming fundamentals are the bedrock for any computer science career, essential for cracking technical interviews and building efficient software solutions.
Engage Actively in Lab Sessions and Peer Learning- (Semester 1-2)
Actively participate in all lab sessions, understanding the practical application of theoretical concepts. Form study groups with peers to discuss complex topics, clarify doubts, and collaboratively work on assignments, fostering a deeper understanding.
Tools & Resources
Departmental labs, Online collaboration tools (Google Docs, Discord), Study groups
Career Connection
Effective collaboration and practical skills gained in labs are highly valued in team-oriented software development roles, while peer discussions enhance conceptual clarity for exams.
Build a Strong Mathematical Foundation- (Semester 1-2)
Focus on strengthening your mathematical skills, particularly in discrete mathematics, logic, and basic calculus. These subjects are crucial for understanding algorithms, data structures, and advanced computer science topics.
Tools & Resources
Textbooks, Khan Academy, NPTEL lectures
Career Connection
A strong math foundation is critical for analytical roles in data science, machine learning, and for developing robust algorithms, directly impacting problem-solving abilities in technical roles.
Intermediate Stage
Deep Dive into Data Structures and Algorithms (DSA)- (Semester 3-5)
Beyond classroom learning, dedicate significant effort to master advanced data structures and algorithms. Practice implementing them from scratch and solving complex problems on competitive programming platforms.
Tools & Resources
LeetCode, Interviews/GeeksforGeeks, Standard DSA textbooks (e.g., CLRS)
Career Connection
DSA proficiency is the primary filter in technical interviews for software development roles at top Indian and global tech companies. It demonstrates problem-solving capability.
Undertake Practical Projects and Internships- (Semester 3-5)
Start building small to medium-scale personal projects in areas like web development, app development, or basic machine learning. Actively seek summer internships, even short-term or unpaid ones, to gain industry exposure and apply learned skills.
Tools & Resources
GitHub, FreeCodeCamp, Coursera/Udemy, LinkedIn for internships
Career Connection
Projects create a portfolio demonstrating practical skills to recruiters. Internships offer real-world experience, networking opportunities, and often lead to pre-placement offers in Indian companies.
Explore and Specialize in Emerging Technologies- (Semester 3-5)
Beyond core curriculum, explore areas like Artificial Intelligence, Machine Learning, Cybersecurity, or Cloud Computing through online courses or workshops. Attend tech meetups and seminars to understand industry trends.
Tools & Resources
NPTEL, Google/AWS/Azure certifications, Local tech communities, Tech conferences
Career Connection
Specializing in a trending domain makes you highly marketable in the Indian tech landscape, opening doors to specific high-demand roles and future growth opportunities.
Advanced Stage
Intensive Placement Preparation- (Semester 6-8)
Focus on comprehensive placement preparation, including mock interviews (technical, HR, behavioral), aptitude tests, and resume building. Practice competitive coding daily and participate in hackathons to test skills under pressure.
Tools & Resources
Mock interview platforms, Aptitude test apps, Professional resume builders, Major hackathons like Smart India Hackathon
Career Connection
Targeted preparation is crucial for securing placements in top-tier companies. It hones interview skills and ensures readiness for the rigorous recruitment processes prevalent in India.
Network and Build Professional Connections- (Semester 6-8)
Actively network with alumni, faculty, and industry professionals through LinkedIn, college events, and professional gatherings. Seek mentorship and insights into career paths and industry requirements.
Tools & Resources
LinkedIn, Alumni association events, Industry expos/webinars
Career Connection
Networking opens doors to hidden job opportunities, valuable career guidance, and potential referrals, which are often significant in the Indian job market.
Undertake a Capstone Project/Research- (Semester 6-8)
Engage in a substantial capstone project or a research-oriented dissertation that demonstrates mastery of advanced concepts. Aim for a solution that addresses a real-world problem or contributes to existing knowledge.
Tools & Resources
Academic advisors, Research papers, Open-source libraries, University research labs
Career Connection
A strong final year project acts as a significant differentiator on your resume, showcasing your ability to independently design, develop, and deliver complex solutions to potential employers or for higher studies.
Program Structure and Curriculum
Eligibility:
- Class XII pass with Mathematics and one more subject from a list of relevant subjects, as per University of Delhi Admission Bulletin.
Duration: 4 years (8 semesters)
Credits: 176 Credits
Assessment: Internal: 30%, External: 70%
Semester-wise Curriculum Table
Semester 1
| Subject Code | Subject Name | Subject Type | Credits | Key Topics |
|---|---|---|---|---|
| CS-C1 | Programming using Python | Core | 4 | Introduction to Python, Data types and operators, Control flow, Functions and modules, Data structures (lists, tuples, dictionaries) |
| CS-C1-P | Programming using Python Lab | Core Lab | 2 | Practical implementation of Python programming, Debugging and testing, Problem-solving with Python, Data handling exercises |
| GE-1 | Generic Elective - I | Generic Elective | 4 | |
| AEC-1 | Environmental Science | Ability Enhancement Course | 2 | Environmental studies, Ecosystems, Biodiversity, Environmental pollution, Sustainable development |
| VAC-1 | Value Addition Course - I | Value Addition Course | 2 |
Semester 2
| Subject Code | Subject Name | Subject Type | Credits | Key Topics |
|---|---|---|---|---|
| CS-C2 | Data Structures | Core | 4 | Arrays and linked lists, Stacks and queues, Trees and graphs, Searching and sorting algorithms, Hashing |
| CS-C2-P | Data Structures Lab | Core Lab | 2 | Implementation of data structures, Algorithm analysis, Problem-solving with data structures, Performance comparison of algorithms |
| GE-2 | Generic Elective - II | Generic Elective | 4 | |
| AEC-2 | MIL/English Communication | Ability Enhancement Course | 2 | Communication skills, Grammar and usage, Written and oral communication, Professional communication |
| VAC-2 | Value Addition Course - II | Value Addition Course | 2 |
Semester 3
| Subject Code | Subject Name | Subject Type | Credits | Key Topics |
|---|---|---|---|---|
| CS-C3 | Object-Oriented Programming using C++ | Core | 4 | Classes and objects, Inheritance and polymorphism, Constructors and destructors, Operator overloading, Exception handling |
| CS-C3-P | Object-Oriented Programming using C++ Lab | Core Lab | 2 | Practical C++ programming, Designing OOP solutions, Testing and debugging C++ code, Developing object-oriented applications |
| CS-C4 | Computer System Architecture | Core | 4 | Digital logic circuits, Combinational and sequential circuits, Memory organization, CPU design, Input/Output organization |
| CS-C4-P | Computer System Architecture Lab | Core Lab | 2 | Logic gate implementation, Circuit design and simulation, Assembly language programming, Microprocessor basic experiments |
| GE-3 | Generic Elective - III | Generic Elective | 4 | |
| SEC-1 | Skill Enhancement Course - I | Skill Enhancement Course | 2 |
Semester 4
| Subject Code | Subject Name | Subject Type | Credits | Key Topics |
|---|---|---|---|---|
| CS-C5 | Operating Systems | Core | 4 | Process management, CPU scheduling, Memory management, File systems, Concurrency and deadlock |
| CS-C5-P | Operating Systems Lab | Core Lab | 2 | Shell programming, Process creation and management, Synchronization problems, Memory allocation algorithms |
| CS-C6 | Database Management Systems | Core | 4 | ER modeling, Relational model, SQL queries, Normalization, Transaction management |
| CS-C6-P | Database Management Systems Lab | Core Lab | 2 | SQL practice, Database design, Data manipulation, Report generation |
| GE-4 | Generic Elective - IV | Generic Elective | 4 | |
| SEC-2 | Skill Enhancement Course - II | Skill Enhancement Course | 2 |
Semester 5
| Subject Code | Subject Name | Subject Type | Credits | Key Topics |
|---|---|---|---|---|
| CS-C7 | Discrete Structures | Core | 4 | Set theory, Relations and functions, Logic and proofs, Graph theory, Combinatorics |
| CS-C7-P | Discrete Structures Lab | Core Lab | 2 | Problem-solving with discrete mathematics, Logical reasoning exercises, Graph algorithms, Combinatorial problem implementation |
| CS-C8 | Computer Networks | Core | 4 | Network models (OSI, TCP/IP), Data link layer, Network layer, Transport layer, Application layer |
| CS-C8-P | Computer Networks Lab | Core Lab | 2 | Network configuration, Socket programming, Packet analysis, Network simulation tools |
| CS-DSE-1 | Discipline Specific Elective - I | Discipline Specific Elective | 4 | |
| CS-DSE-1-P | Discipline Specific Elective - I Lab | Discipline Specific Elective Lab | 2 |
Semester 6
| Subject Code | Subject Name | Subject Type | Credits | Key Topics |
|---|---|---|---|---|
| CS-C9 | Design and Analysis of Algorithms | Core | 4 | Algorithm complexity, Divide and conquer, Dynamic programming, Greedy algorithms, NP-completeness |
| CS-C9-P | Design and Analysis of Algorithms Lab | Core Lab | 2 | Implementation of algorithms, Empirical analysis of algorithms, Solving algorithmic problems, Graph algorithms |
| CS-C10 | Software Engineering | Core | 4 | Software development life cycle, Requirements engineering, Software design, Software testing, Project management |
| CS-C10-P | Software Engineering Lab | Core Lab | 2 | UML diagramming, Software project planning, Test case generation, Using software engineering tools |
| CS-DSE-2 | Discipline Specific Elective - II | Discipline Specific Elective | 4 | |
| CS-DSE-2-P | Discipline Specific Elective - II Lab | Discipline Specific Elective Lab | 2 |
Semester 7
| Subject Code | Subject Name | Subject Type | Credits | Key Topics |
|---|---|---|---|---|
| CS-DSE-3 | Discipline Specific Elective - III | Discipline Specific Elective | 4 | |
| CS-DSE-3-P | Discipline Specific Elective - III Lab | Discipline Specific Elective Lab | 2 | |
| CS-DSE-4 | Discipline Specific Elective - IV | Discipline Specific Elective | 4 | |
| CS-DSE-4-P | Discipline Specific Elective - IV Lab | Discipline Specific Elective Lab | 2 | |
| CS-DSE-5 | Discipline Specific Elective - V | Discipline Specific Elective | 4 | |
| CS-DSE-5-P | Discipline Specific Elective - V Lab | Discipline Specific Elective Lab | 2 | |
| CS-PROJ-1 | Project Work I | Project | 4 | Problem identification, Literature review, System design, Implementation planning, Project report writing |
Semester 8
| Subject Code | Subject Name | Subject Type | Credits | Key Topics |
|---|---|---|---|---|
| CS-DSE-6 | Discipline Specific Elective - VI | Discipline Specific Elective | 4 | |
| CS-DSE-6-P | Discipline Specific Elective - VI Lab | Discipline Specific Elective Lab | 2 | |
| CS-DSE-7 | Discipline Specific Elective - VII | Discipline Specific Elective | 4 | |
| CS-DSE-7-P | Discipline Specific Elective - VII Lab | Discipline Specific Elective Lab | 2 | |
| CS-DSE-8 | Discipline Specific Elective - VIII | Discipline Specific Elective | 4 | |
| CS-DSE-8-P | Discipline Specific Elective - VIII Lab | Discipline Specific Elective Lab | 2 | |
| CS-PROJ-2 | Project Work II / Dissertation | Project | 4 | Advanced system development, Testing and validation, Performance optimization, Dissertation writing, Project defense |
