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BSC-HONS in Computer Science at Delhi College of Arts and Commerce
Delhi, Delhi
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About the Specialization
What is Computer Science at Delhi College of Arts and Commerce Delhi?
This BSc Hons Computer Science program at Delhi College of Arts and Commerce, under the University of Delhi, focuses on building a strong foundation in core computer science concepts. It covers programming, data structures, algorithms, AI, and web technologies, equipping students with essential skills for India''''s rapidly evolving tech landscape. The curriculum emphasizes both theoretical knowledge and practical application, preparing graduates for diverse roles in software development and IT.
Who Should Apply?
This program is ideal for fresh graduates who have completed Class 12th with a strong aptitude for mathematics and problem-solving, aspiring to build a career in technology. It also suits individuals passionate about programming, software development, and understanding the intricate workings of computer systems. Students with a keen interest in logical reasoning and innovation will find this specialization particularly rewarding.
Why Choose This Course?
Graduates of this program can expect to pursue robust career paths in India as Software Developers, Data Analysts, Web Developers, and IT Consultants. Entry-level salaries typically range from INR 3-6 LPA, growing significantly with experience to INR 8-15 LPA and beyond in top-tier companies. The comprehensive curriculum aligns with industry demands, offering strong growth trajectories in Indian IT and product-based companies, and preparing for professional certifications.
Student Success Practices
Foundation Stage
Master Programming Fundamentals- (Semester 1-2)
Dedicate time to consistently practice Python and C++ programming. Understand data types, control flow, functions, and object-oriented concepts thoroughly. Solve daily coding challenges to improve problem-solving abilities.
Tools & Resources
GeeksforGeeks, HackerRank, CodeChef, Online IDEs
Career Connection
Strong programming fundamentals are the bedrock for any computer science career, crucial for cracking technical interviews and excelling in software development roles.
Build a Strong Mathematical & Logical Base- (Semester 1-2)
Focus on understanding Discrete Mathematics concepts and their application to computer science. Regularly solve logic puzzles and quantitative aptitude questions to enhance analytical skills, critical for algorithms and problem-solving.
Tools & Resources
NPTEL videos (Discrete Maths), Aptitude books, Brilliant.org
Career Connection
A solid mathematical foundation is essential for advanced computer science topics like algorithms, AI, and data science, boosting performance in competitive exams and research.
Engage in Peer Learning & Collaborative Projects- (Semester 1-2)
Form study groups to discuss complex topics and work on small programming projects together. Participate in college technical clubs to collaborate and learn from seniors, fostering teamwork and practical application.
Tools & Resources
GitHub, Discord/WhatsApp groups, College tech societies
Career Connection
Teamwork and communication are vital soft skills for the industry. Collaborative projects build practical experience and create a professional network, aiding in future job roles.
Intermediate Stage
Apply Concepts with Hands-on Projects- (Semester 3-5)
Beyond coursework, develop personal projects in areas like web development (HTML, CSS, JavaScript), database applications, or small AI models. Focus on building tangible applications to solidify theoretical understanding.
Tools & Resources
VS Code, GitHub, MongoDB Atlas (for databases), TensorFlow/Keras for AI
Career Connection
Portfolio projects are key differentiators in Indian placements, showcasing practical skills and initiative to recruiters, leading to better internship and job opportunities.
Seek Internships & Industry Exposure- (Semester 4-6)
Actively look for summer internships or part-time roles in startups or small IT firms. Even unpaid internships offer invaluable industry exposure, understanding of workflows, and networking opportunities.
Tools & Resources
Internshala, LinkedIn, College placement cell notices
Career Connection
Internships provide real-world experience, often leading to pre-placement offers (PPOs) and significantly boosting employability upon graduation in the Indian job market.
Participate in Coding Competitions & Hackathons- (Semester 3-5)
Regularly participate in online coding contests and college-level hackathons. This sharpens problem-solving under pressure, enhances algorithmic thinking, and exposes you to innovative solutions.
Tools & Resources
LeetCode, TopCoder, Kaggle, Major hackathon platforms
Career Connection
Success in competitive programming and hackathons catches the eye of top tech companies in India, often serving as a direct pathway to interviews and coveted positions.
Advanced Stage
Specialize and Build a Niche Skillset- (Semester 6-8)
Identify a domain of interest (e.g., AI/ML, Cybersecurity, Cloud, Data Science) and take elective courses, online certifications, and advanced projects in that area. Deepen expertise for specialized roles.
Tools & Resources
Coursera/edX (specific certifications), NPTEL advanced courses, Domain-specific forums
Career Connection
Specialization makes you a more valuable candidate for niche roles in high-demand areas within Indian tech companies, commanding higher salaries and faster career progression.
Intensive Placement Preparation- (Semester 7-8)
Focus on rigorous practice of data structures and algorithms, mock interviews (technical and HR), resume building, and aptitude tests. Network with alumni for insights and referrals.
Tools & Resources
GeeksforGeeks placement prep, InterviewBit, LinkedIn for networking, College alumni network
Career Connection
Thorough preparation is paramount for securing placements in leading Indian and multinational companies. This stage directly impacts job offers and starting compensation.
Undertake a Capstone Project/Research- (Semester 7-8)
Dedicate significant effort to a final year project or a research dissertation. Choose a challenging problem, develop an innovative solution, and document it professionally. This showcases comprehensive skills.
Tools & Resources
Jupyter Notebook, Overleaf (for thesis writing), Research papers, Faculty mentors
Career Connection
A strong capstone project demonstrates problem-solving ability, independent work, and technical depth, making you highly attractive to employers for R&D or advanced development roles in India.
Program Structure and Curriculum
Eligibility:
- Class 12th examination pass from a recognized board with Mathematics as one of the subjects. Admission through CUET (UG).
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 |
|---|---|---|---|---|
| DSC-1 | Programming using Python | Core | 4 | Introduction to Python, Data Types and Operators, Control Flow, Functions and Modules, File Handling and Exception Handling, Object-Oriented Programming in Python |
| DSC-2 | Data Structures | Core | 4 | Arrays and Linked Lists, Stacks and Queues, Trees (Binary, BST, AVL), Graphs and Graph Traversal, Searching and Sorting Algorithms |
| DSC-3 | Computer System Architecture | Core | 4 | Digital Logic Circuits, Combinational and Sequential Circuits, Basic Computer Organization, Instruction Set Architecture, Memory Hierarchy and I/O Organization |
| GE-1 | Generic Elective - 1 (from other discipline) | Elective | 4 | Selected topics from disciplines like Economics, Mathematics, Statistics, etc. |
| AEC-1 | Ability Enhancement Compulsory Course - 1 | Compulsory | 2 | Environmental Science, Language (e.g., Hindi, English) |
| VAC-1 | Value Addition Course - 1 | Compulsory | 2 | Ethics and Values, Constitutional Values and Fundamental Duties |
Semester 2
| Subject Code | Subject Name | Subject Type | Credits | Key Topics |
|---|---|---|---|---|
| DSC-4 | Discrete Mathematics | Core | 4 | Sets, Relations, Functions, Logic and Propositional Calculus, Combinatorics, Graphs and Trees, Algebraic Structures |
| DSC-5 | Object-Oriented Programming with C++ | Core | 4 | Introduction to OOP, Classes and Objects, Inheritance and Polymorphism, Constructors and Destructors, File I/O and Exception Handling |
| DSC-6 | Operating Systems | Core | 4 | Introduction to Operating Systems, Process Management, CPU Scheduling, Memory Management, File Systems and I/O Systems |
| GE-2 | Generic Elective - 2 (from other discipline) | Elective | 4 | Selected topics from disciplines like Economics, Mathematics, Statistics, etc. |
| AEC-2 | Ability Enhancement Compulsory Course - 2 | Compulsory | 2 | Language (e.g., Hindi, English), Communication Skills |
| VAC-2 | Value Addition Course - 2 | Compulsory | 2 | Digital Fluency, Emotional Intelligence |
Semester 3
| Subject Code | Subject Name | Subject Type | Credits | Key Topics |
|---|---|---|---|---|
| DSC-7 | Database Management Systems | Core | 4 | Introduction to DBMS, ER Model, Relational Model and Algebra, SQL and Query Optimization, Normalization, Transaction Management |
| DSC-8 | Computer Networks | Core | 4 | Network Topologies, OSI and TCP/IP Models, Data Link Layer, Network Layer (IP, Routing), Transport Layer (TCP, UDP), Application Layer Protocols |
| DSC-9 | Software Engineering | Core | 4 | Software Development Life Cycle (SDLC), Requirements Engineering, Software Design Principles, Software Testing, Software Project Management |
| SEC-1 | Skill Enhancement Course - 1 | Elective | 2 | Web Design (HTML, CSS, JavaScript), Android Programming, R Programming for Data Science |
| GE-3 | Generic Elective - 3 (from other discipline) | Elective | 4 | Selected topics from disciplines like Economics, Mathematics, Statistics, etc. |
| VAC-3 | Value Addition Course - 3 | Compulsory | 2 | Financial Literacy, Art of Being Happy |
Semester 4
| Subject Code | Subject Name | Subject Type | Credits | Key Topics |
|---|---|---|---|---|
| DSC-10 | Design and Analysis of Algorithms | Core | 4 | Algorithmic Paradigms (Divide and Conquer, Greedy), Dynamic Programming, Graph Algorithms, Complexity Analysis (Time and Space), NP-Completeness |
| DSC-11 | Artificial Intelligence | Core | 4 | Introduction to AI, Problem Solving Agents (Search Algorithms), Knowledge Representation and Reasoning, Machine Learning Basics, Natural Language Processing Fundamentals |
| DSC-12 | Web Technologies | Core | 4 | Client-Server Architecture, HTML5 and CSS3, JavaScript and DOM, Backend Development (e.g., Node.js, PHP), Database Integration (SQL/NoSQL) |
| SEC-2 | Skill Enhancement Course - 2 | Elective | 2 | Cloud Computing Fundamentals, Data Visualization, Cyber Security Essentials |
| GE-4 | Generic Elective - 4 (from other discipline) | Elective | 4 | Selected topics from disciplines like Economics, Mathematics, Statistics, etc. |
| VAC-4 | Value Addition Course - 4 | Compulsory | 2 | Swachh Bharat, Gandhian Ethics |
Semester 5
| Subject Code | Subject Name | Subject Type | Credits | Key Topics |
|---|---|---|---|---|
| DSC-13 | Theory of Computation | Core | 4 | Finite Automata, Regular Expressions and Languages, Context-Free Grammars, Pushdown Automata, Turing Machines and Undecidability |
| DSC-14 | Machine Learning | Core | 4 | Introduction to ML, Supervised Learning (Regression, Classification), Unsupervised Learning (Clustering), Neural Networks Basics, Model Evaluation and Validation |
| DSE-1 | Discipline Specific Elective - 1 | Elective | 4 | E.g., Computer Graphics, Data Mining, Advanced Algorithms |
| DSE-2 | Discipline Specific Elective - 2 | Elective | 4 | E.g., Parallel and Distributed Computing, Image Processing, Introduction to IoT |
Semester 6
| Subject Code | Subject Name | Subject Type | Credits | Key Topics |
|---|---|---|---|---|
| DSC-15 | Compiler Design | Core | 4 | Phases of Compiler, Lexical Analysis, Syntax Analysis (Parsing), Intermediate Code Generation, Code Optimization and Generation |
| DSC-16 | Computer Graphics | Core | 4 | Graphics Primitives, 2D and 3D Transformations, Viewing and Clipping, Projection, Shading and Illumination Models |
| DSE-3 | Discipline Specific Elective - 3 | Elective | 4 | E.g., Data Science, Big Data Analytics, Advanced Operating Systems |
| DSE-4 | Discipline Specific Elective - 4 | Elective | 4 | E.g., Natural Language Processing, Reinforcement Learning, Distributed Systems |
Semester 7
| Subject Code | Subject Name | Subject Type | Credits | Key Topics |
|---|---|---|---|---|
| DSE-5 | Discipline Specific Elective - 5 | Elective | 4 | E.g., Deep Learning, Cyber Forensics, Quantum Computing |
| DSE-6 | Discipline Specific Elective - 6 | Elective | 4 | E.g., Mobile Computing, Blockchain Technology, Ethical Hacking |
| OE-1 | Open Elective - 1 | Elective | 4 | Selected topics from any other discipline/department as per availability |
| RP-1 | Research Project / Internship | Project | 8 | Problem Identification, Literature Review, Methodology Design, Implementation and Testing, Report Writing and Presentation |
Semester 8
| Subject Code | Subject Name | Subject Type | Credits | Key Topics |
|---|---|---|---|---|
| DSE-7 | Discipline Specific Elective - 7 | Elective | 4 | E.g., Game Programming, Advanced Database Management, Bioinformatics |
| DSE-8 | Discipline Specific Elective - 8 | Elective | 4 | E.g., Cloud Security, Human-Computer Interaction, Robotics |
| OE-2 | Open Elective - 2 | Elective | 4 | Selected topics from any other discipline/department as per availability |
| DP-1 | Dissertation / Capstone Project | Project | 8 | Advanced System Design, Complex Problem Solving, Independent Research, Project Management, Final Thesis/Report |
