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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 strong foundation in core computer science principles and advanced specializations. Tailored to meet the evolving demands of the Indian IT industry, it emphasizes theoretical knowledge combined with practical application. The curriculum integrates modern technologies and problem-solving skills, preparing students for diverse roles in India''''s rapidly growing tech sector, from software development to data science.
Who Should Apply?
This program is ideal for fresh graduates from 10+2 with a strong aptitude for mathematics and logical reasoning, seeking entry into the technology domain. It also caters to individuals passionate about programming, algorithms, and system design, aiming for careers in software engineering, data analytics, or research. Students aspiring to pursue higher education or entrepreneurship in tech will find the comprehensive curriculum beneficial.
Why Choose This Course?
Graduates of this program can expect to secure roles as Software Developers, Data Analysts, System Administrators, Web Developers, and IT Consultants in leading Indian and multinational companies. Entry-level salaries typically range from INR 4-8 LPA, with experienced professionals earning significantly more (INR 10-25+ LPA). The program fosters a strong analytical mindset, opening pathways for growth in leadership and specialized technical positions.
Student Success Practices
Foundation Stage
Master Programming Fundamentals- (Semester 1-2)
Dedicate time to consistently practice core programming concepts learned in Python. Solve at least 2-3 coding problems daily to build a strong logical base and enhance problem-solving abilities.
Tools & Resources
HackerRank, CodeChef, GeeksforGeeks, Jupyter Notebooks
Career Connection
Strong fundamentals are crucial for cracking technical interviews for entry-level software development roles and form the bedrock for advanced topics.
Build a Solid Data Structures & Algorithms (DSA) Base- (Semester 1-2)
Regularly practice DSA problems using a chosen programming language (e.g., Python/C++). Understand concepts deeply, not just memorize solutions. Participate in peer coding sessions to clarify doubts.
Tools & Resources
LeetCode, InterviewBit, Visualgo.net (for visualization)
Career Connection
DSA proficiency is a primary screening criterion for almost all software engineering and data science roles in top Indian tech companies.
Engage Actively in Academic Discussions- (Semester 1-2)
Participate in classroom discussions, ask questions, and form study groups. Collaborate with peers on assignments and projects to foster a deeper understanding and learn from diverse perspectives.
Tools & Resources
Google Meet/Zoom for study groups, University library resources
Career Connection
Develops communication skills, critical thinking, and teamwork essential for professional environments and collaborative projects.
Intermediate Stage
Develop Practical Projects & Portfolio- (Semester 3-5)
Apply theoretical knowledge by working on mini-projects using technologies like C++, databases, and web frameworks. Build a portfolio of 2-3 significant projects to showcase practical skills.
Tools & Resources
GitHub, VS Code, MySQL/PostgreSQL, Python Flask/Django
Career Connection
A strong project portfolio demonstrates practical skills to recruiters, significantly boosting internship and placement chances in India''''s competitive market.
Explore Open Source Contributions & Hackathons- (Semester 3-5)
Look for beginner-friendly open-source projects to contribute to. Participate in university-level or national hackathons to gain experience in rapid prototyping and teamwork.
Tools & Resources
GitHub Explore, Devfolio (for hackathons), Major League Hacking (MLH)
Career Connection
Provides real-world development experience, network building, and a chance to get noticed by industry professionals and potential employers.
Seek Industry Internships- (Semester 4-5)
Actively apply for summer internships in relevant fields (e.g., software development, data analysis, cybersecurity). Focus on gaining exposure to industry practices and corporate culture.
Tools & Resources
LinkedIn Jobs India, Internshala, Naukri.com, College Placement Cell
Career Connection
Internships are often a direct pipeline to full-time employment, offering invaluable industry experience and a chance to build a professional network.
Advanced Stage
Specialize and Deep Dive into Electives- (Semester 6-8)
Choose Discipline Specific Electives (DSEs) strategically based on career interests (e.g., AI/ML, Data Science, Cyber Security). Pursue certifications or advanced courses in the chosen specialization.
Tools & Resources
Coursera, edX, NPTEL, Industry-specific certifications (e.g., AWS, Azure)
Career Connection
Develops expertise in high-demand areas, making graduates highly competitive for specialized roles in the Indian tech industry.
Focus on Final Year Project/Dissertation for Impact- (Semester 7-8)
Undertake a substantial and innovative final year project that showcases advanced skills. Aim to solve a real-world problem, potentially collaborating with industry mentors.
Tools & Resources
Mentorship from faculty/industry experts, Latest research papers (e.g., IEEE Xplore, ACM Digital Library)
Career Connection
A high-impact project is a significant resume booster, demonstrating problem-solving capabilities and independent work crucial for senior roles and higher studies.
Intensive Placement Preparation & Networking- (Semester 7-8)
Start rigorous preparation for placements including aptitude tests, technical rounds, and HR interviews. Actively network with alumni and professionals through LinkedIn and career fairs.
Tools & Resources
Placement preparation platforms (e.g., PrepInsta, FacePrep), Mock interview platforms, LinkedIn
Career Connection
Optimizes chances of securing desirable placements with top companies in India, leading to a strong career start and future growth opportunities.
Program Structure and Curriculum
Eligibility:
- Passed 10+2 examination or equivalent with Mathematics as one of the subjects from a recognized Board/University. Minimum aggregate marks as per University of Delhi admission policy for the academic year.
Duration: 4 years / 8 semesters
Credits: 160 Credits
Assessment: Internal: 30%, External: 70%
Semester-wise Curriculum Table
Semester 1
| Subject Code | Subject Name | Subject Type | Credits | Key Topics |
|---|---|---|---|---|
| CSCU101 | Programming Using Python | Discipline Specific Core (DSC) | 4 | Introduction to Python, Data Types and Variables, Operators and Expressions, Control Flow Statements, Functions and Modules, Lists, Tuples, Dictionaries |
| CSCU102 | Computer System Architecture | Discipline Specific Core (DSC) | 4 | Digital Logic Circuits, Combinational Circuits, Sequential Circuits, Memory Organization, CPU Organization, Instruction Set Architecture |
| GE-1 | Generic Elective - 1 (Chosen from a pool of subjects from other disciplines) | Generic Elective (GE) | 4 | |
| AEC-1 | Environmental Science | Ability Enhancement Course (AEC) | 2 | Ecosystems and their dynamics, Natural Resources and management, Biodiversity and Conservation, Environmental Pollution, Global Environmental Issues, Environmental Ethics and Policies |
| VAC-1 | Value Addition Course - 1 (Chosen from a University pool) | Value Addition Course (VAC) | 2 | |
| SEC-1 | Skill Enhancement Course - 1 (Chosen from a University pool) | Skill Enhancement Course (SEC) | 2 |
Semester 2
| Subject Code | Subject Name | Subject Type | Credits | Key Topics |
|---|---|---|---|---|
| CSCU203 | Data Structures | Discipline Specific Core (DSC) | 4 | Arrays, Records, Pointers, Stacks and Queues, Linked Lists, Trees and Binary Trees, Graphs and Graph Traversal, Searching and Sorting Algorithms |
| CSCU204 | Discrete Mathematics | Discipline Specific Core (DSC) | 4 | Logic and Propositional Calculus, Set Theory, Relations, Functions, Counting and Combinatorics, Graph Theory Fundamentals, Trees and Spanning Trees, Boolean Algebra |
| GE-2 | Generic Elective - 2 (Chosen from a pool of subjects from other disciplines) | Generic Elective (GE) | 4 | |
| AEC-2 | Ability Enhancement Course - 2 (Choose from MIL or English) | Ability Enhancement Course (AEC) | 2 | |
| VAC-2 | Value Addition Course - 2 (Chosen from a University pool) | Value Addition Course (VAC) | 2 | |
| SEC-2 | Skill Enhancement Course - 2 (Chosen from a University pool) | Skill Enhancement Course (SEC) | 2 |
Semester 3
| Subject Code | Subject Name | Subject Type | Credits | Key Topics |
|---|---|---|---|---|
| CSCU305 | Operating Systems | Discipline Specific Core (DSC) | 4 | Introduction to Operating Systems, Process Management and CPU Scheduling, Deadlocks, Memory Management Techniques, Virtual Memory, File Systems and I/O Management |
| CSCU306 | Computer Networks | Discipline Specific Core (DSC) | 4 | Network Models (OSI, TCP/IP), Physical Layer and Data Link Layer, Network Layer Protocols, Transport Layer Protocols, Application Layer Protocols, Network Security Basics |
| CSCU307 | Object-Oriented Programming with C++ | Discipline Specific Core (DSC) | 4 | Classes and Objects, Constructors and Destructors, Inheritance and Polymorphism, Virtual Functions, Exception Handling, File I/O in C++ |
| GE-3 | Generic Elective - 3 (Chosen from a pool of subjects from other disciplines) | Generic Elective (GE) | 4 | |
| VAC-3 | Value Addition Course - 3 (Chosen from a University pool) | Value Addition Course (VAC) | 2 | |
| SEC-3 | Skill Enhancement Course - 3 (Chosen from a University pool) | Skill Enhancement Course (SEC) | 2 |
Semester 4
| Subject Code | Subject Name | Subject Type | Credits | Key Topics |
|---|---|---|---|---|
| CSCU408 | Design and Analysis of Algorithms | Discipline Specific Core (DSC) | 4 | Algorithm Analysis and Complexity, Divide and Conquer Strategy, Greedy Algorithms, Dynamic Programming, Graph Algorithms, NP-Completeness |
| CSCU409 | Database Management Systems | Discipline Specific Core (DSC) | 4 | ER Model and Relational Model, Relational Algebra and Calculus, SQL Query Language, Normalization, Transaction Management, Concurrency Control and Recovery |
| CSCU410 | Software Engineering | Discipline Specific Core (DSC) | 4 | Software Development Life Cycle, Requirements Engineering, Software Design Principles, Software Testing Techniques, Software Maintenance, Project Management Concepts |
| GE-4 | Generic Elective - 4 (Chosen from a pool of subjects from other disciplines) | Generic Elective (GE) | 4 | |
| VAC-4 | Value Addition Course - 4 (Chosen from a University pool) | Value Addition Course (VAC) | 2 | |
| SEC-4 | Skill Enhancement Course - 4 (Chosen from a University pool) | Skill Enhancement Course (SEC) | 2 |
Semester 5
| Subject Code | Subject Name | Subject Type | Credits | Key Topics |
|---|---|---|---|---|
| CSCU511 | Theory of Computation | Discipline Specific Core (DSC) | 4 | Finite Automata and Regular Expressions, Context-Free Grammars and Pushdown Automata, Turing Machines, Decidability and Undecidability, Chomsky Hierarchy, Complexity Classes P and NP |
| CSCU512 | Artificial Intelligence | Discipline Specific Core (DSC) | 4 | Introduction to AI and Intelligent Agents, Problem-Solving with Search Algorithms, Knowledge Representation and Reasoning, Machine Learning Basics, Natural Language Processing, Expert Systems |
| DSE-1 | Discipline Specific Elective - 1 (Choose one: Data Mining (CSCU513), Digital Image Processing (CSCU514), Introduction to Data Science (CSCU515), Computer Graphics (CSCU516)) | Discipline Specific Elective (DSE) | 4 | |
| DSE-2 | Discipline Specific Elective - 2 (Choose one: Operating System Case Studies (CSCU517), Digital Forensics (CSCU518), Big Data Analytics (CSCU519), Cloud Computing (CSCU520)) | Discipline Specific Elective (DSE) | 4 |
Semester 6
| Subject Code | Subject Name | Subject Type | Credits | Key Topics |
|---|---|---|---|---|
| CSCU613 | Machine Learning | Discipline Specific Core (DSC) | 4 | Supervised Learning Algorithms, Unsupervised Learning Algorithms, Regression and Classification, Clustering Techniques, Model Evaluation and Selection, Introduction to Deep Learning |
| CSCU614 | Web Technologies | Discipline Specific Core (DSC) | 4 | HTML5 and CSS3, JavaScript Fundamentals, DOM Manipulation and AJAX, XML and JSON, Server-Side Scripting (e.g., PHP/Node.js), Web Security Basics |
| DSE-3 | Discipline Specific Elective - 3 (Choose one: Internet of Things (CSCU615), Mobile Application Development (CSCU616), Embedded Systems (CSCU617), Simulation and Modeling (CSCU618)) | Discipline Specific Elective (DSE) | 4 | |
| DSE-4 | Discipline Specific Elective - 4 (Choose one: Information Security (CSCU619), Compiler Design (CSCU620), Distributed Systems (CSCU621), Bioinformatics (CSCU622)) | Discipline Specific Elective (DSE) | 4 |
Semester 7
| Subject Code | Subject Name | Subject Type | Credits | Key Topics |
|---|---|---|---|---|
| DSE-5 | Discipline Specific Elective - 5 (Choose one: Cryptography and Network Security (CSCU723), Natural Language Processing (CSCU724), Computer Vision (CSCU725), Genetic Algorithms (CSCU726)) | Discipline Specific Elective (DSE) | 4 | |
| DSE-6 | Discipline Specific Elective - 6 (Choose one: Data Analytics with R (CSCU727), Reinforcement Learning (CSCU728), Blockchain Technologies (CSCU729), Robotics (CSCU730)) | Discipline Specific Elective (DSE) | 4 | |
| DSE-7 | Discipline Specific Elective - 7 (Choose one: Quantum Computing (CSCU731), Parallel and Distributed Algorithms (CSCU732), Human Computer Interaction (CSCU733), Deep Learning (CSCU734)) | Discipline Specific Elective (DSE) | 4 |
Semester 8
| Subject Code | Subject Name | Subject Type | Credits | Key Topics |
|---|---|---|---|---|
| DSE-8 | Discipline Specific Elective - 8 (Choose one: Software Testing and Quality Assurance (CSCU835), Game Development (CSCU836), Computational Biology (CSCU837), Enterprise Resource Planning (CSCU838)) | Discipline Specific Elective (DSE) | 4 | |
| CSCU815 | Project/Dissertation | Project | 12 | Problem Identification and Literature Review, System Design and Architecture, Implementation and Coding, Testing and Debugging, Documentation and Report Writing, Presentation and Viva-Voce |
