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B-TECH in Computer Science Engineering at Sharda University
Gautam Buddh Nagar, Uttar Pradesh
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About the Specialization
What is Computer Science Engineering at Sharda University Gautam Buddh Nagar?
This Computer Science Engineering program at Sharda University focuses on equipping students with core knowledge in algorithms, data structures, and software development, alongside specialized expertise in cutting-edge domains. It emphasizes practical application in emerging areas like Artificial Intelligence, Machine Learning, Data Science, and Cloud Computing, preparing graduates for India''''s rapidly growing tech industry. The program is designed to foster innovation, critical thinking, and problem-solving skills, aligning with both global technological advancements and local industry demands.
Who Should Apply?
This program is ideal for high school graduates with a strong aptitude for mathematics, logical reasoning, and a keen interest in programming, seeking entry into the dynamic tech sector. It also caters to students passionate about software development, system design, data analytics, and exploring advanced computing paradigms. Aspiring innovators, data scientists, cybersecurity professionals, and AI engineers will find the curriculum stimulating and career-focused, providing a solid foundation for their professional journey.
Why Choose This Course?
Graduates of this program can expect diverse and rewarding career paths in India, including roles such as Software Developer, Data Analyst, AI/ML Engineer, Cloud Architect, Cybersecurity Specialist, and Full Stack Developer. Entry-level salaries typically range from INR 4-8 LPA in leading IT companies and startups, with significant growth potential up to INR 15-25 LPA and beyond for experienced professionals in specialized domains. The curriculum often aligns with industry-recognized professional certifications like AWS, Azure, Google Cloud, and ethical hacking.
Student Success Practices
Foundation Stage
Master Programming Fundamentals- (Semester 1-2)
Dedicate significant time to understanding core programming concepts (C/C++, Python), practicing coding challenges daily on platforms like HackerRank, and building small logical projects. Focus on solidifying data structures and algorithms through consistent practice.
Tools & Resources
HackerRank, LeetCode, GeeksforGeeks, CodeChef, Online tutorials for C++/Python
Career Connection
Strong fundamentals are the bedrock for cracking technical interviews at top IT companies, excelling in competitive programming, and building efficient, scalable software solutions.
Develop Strong Communication & Soft Skills- (Semester 1-2)
Actively participate in class discussions, group projects, and presentations. Join university clubs like Toastmasters to refine public speaking and leadership abilities. Focus on clear written communication through well-structured reports and project documentation.
Tools & Resources
University communication labs, English speaking clubs, Online courses on presentation and interpersonal skills
Career Connection
Essential for collaborating effectively in teams, client interactions, successful project management, and excelling in managerial and leadership roles, complementing technical expertise.
Explore Diverse Engineering Fields- (Semester 1-2)
Attend workshops and introductory sessions on various engineering disciplines like electronics, mechanical, and civil engineering. Understand their interconnections with computer science through multidisciplinary projects and gain a broader technical perspective.
Tools & Resources
University department workshops, NPTEL courses on basic engineering principles, Industry expert talks and seminars
Career Connection
Provides a broader perspective for innovation, fosters interdisciplinary problem-solving, and helps in making informed decisions about future specializations or career paths that might blend computing with other fields.
Intermediate Stage
Build Practical Projects & Portfolios- (Semester 3-5)
Beyond academic assignments, initiate personal projects or contribute to open-source initiatives on platforms like GitHub. Focus on applying theoretical knowledge from Data Structures, Operating Systems, DBMS, and AI to create functional applications and prototypes.
Tools & Resources
GitHub, VS Code, Specific IDEs for different languages (e.g., Eclipse, PyCharm), Online project ideas (e.g., build a web app, a small game, a data analysis tool)
Career Connection
A strong project portfolio is crucial for showcasing practical skills to recruiters during internships and placements, providing tangible proof of your abilities and making you stand out.
Engage in Technical Competitions & Hackathons- (Semester 3-5)
Regularly participate in coding competitions (e.g., ICPC, Google Kick Start), hackathons, and technical quizzes organized by university clubs or external organizations. This enhances problem-solving under pressure and introduces new technologies.
Tools & Resources
Major hackathon platforms (Devpost, MLH), University technical clubs (e.g., CSI, ACM chapters), Online competitive programming platforms
Career Connection
Builds critical thinking, teamwork, and resilience, which are highly valued in the tech industry. Success in such events can also lead to direct interview opportunities or pre-placement offers.
Seek Early Industry Exposure through Internships- (Semester 4-5 breaks)
Actively search for summer internships (even unpaid initially) in relevant tech companies or startups. This provides invaluable hands-on experience, networking opportunities, and a realistic glimpse into the corporate work culture and expectations.
Tools & Resources
LinkedIn, Internshala, Company career pages, University career services and placement cell
Career Connection
Internships often convert into full-time offers or provide crucial work experience that makes final placements easier and more competitive. They help in clarifying career interests and building a professional network.
Advanced Stage
Specialize in Emerging Technologies & Certifications- (Semester 6-8)
Deep dive into areas like Artificial Intelligence, Machine Learning, Cloud Computing, Cybersecurity, or Data Science by taking advanced electives, pursuing online certifications, and undertaking specialized projects. Focus on practical implementation of these technologies.
Tools & Resources
Coursera, edX, Udemy for specialized courses, AWS Certifications, Azure Certifications, Google Cloud Certifications, NPTEL advanced courses for theoretical depth
Career Connection
Specialized skills and industry-recognized certifications make you highly employable in niche, high-demand roles with better compensation, aligning directly with specific industry needs and future technological trends.
Focus on Comprehensive Placement Preparation- (Semester 7-8)
Systematically prepare for campus placements by thoroughly revising all core subjects, practicing aptitude, logical reasoning, and verbal ability. Engage in multiple mock interviews to refine technical and behavioral responses. Tailor resumes and cover letters for target companies.
Tools & Resources
University placement cells, Interview preparation books and online platforms (e.g., GeeksforGeeks Interview Prep, LeetCode), Mock interview services and peer practice groups
Career Connection
Directly impacts securing desirable job offers from top recruiters during campus recruitment drives, maximizing your chances of landing a dream job upon graduation.
Cultivate Professional Networking & Mentorship- (Semester 6-8)
Attend industry seminars, conferences, and connect with alumni and professionals on platforms like LinkedIn. Seek mentorship from experienced individuals to gain deeper insights into career growth, industry trends, and strategic decision-making.
Tools & Resources
LinkedIn for professional networking, Industry events and tech conferences (virtual and in-person), University alumni network and mentorship programs
Career Connection
Networking opens doors to unforeseen job opportunities, valuable career advice, potential collaborations, and helps build a strong professional reputation that supports your career trajectory long-term.
Program Structure and Curriculum
Eligibility:
- 10+2 with minimum 50% marks in PCM (Physics, Chemistry, Mathematics) & English from a recognized board, and a valid score in SUAT/JEE Main/Other equivalent entrance examination.
Duration: 8 semesters / 4 years
Credits: 160 Credits
Assessment: Internal: 30%, External: 70%
Semester-wise Curriculum Table
Semester 1
| Subject Code | Subject Name | Subject Type | Credits | Key Topics |
|---|---|---|---|---|
| PHY101 | Engineering Physics | Core | 4 | Wave Optics, Quantum Mechanics, Solid State Physics, Lasers and Fiber Optics, Semiconductor Physics, Magnetic Materials |
| MAT101 | Engineering Mathematics - I | Core | 4 | Differential Calculus, Integral Calculus, Multivariable Calculus, Vector Calculus, Matrices and Linear Algebra |
| CSE101 | Programming for Problem Solving | Core | 4 | Introduction to C, Control Structures, Functions and Modules, Arrays and Pointers, Structures and Unions, File Handling |
| BEE101 | Basic Electrical & Electronics Engineering | Core | 4 | DC and AC Circuits, Diodes and Transistors, Operational Amplifiers, Digital Logic Gates, Transformers, Electrical Motors |
| MED101 | Engineering Graphics & Design | Core | 2 | Orthographic Projections, Isometric Views, Sectional Views, Dimensioning and Conventions, Computer Aided Drafting (CAD), Assembly Drawings |
| HSS101 | Communication Skills | Core | 2 | English Grammar and Vocabulary, Written Communication, Oral Communication, Presentation Skills, Group Discussions, Effective Listening |
| PHY151 | Engineering Physics Lab | Lab | 1 | Optical Experiments, Semiconductor Device Characteristics, Magnetic Field Measurements, Lasers, Oscillations, Electronic Circuit Analysis |
| CSE151 | Programming for Problem Solving Lab | Lab | 1 | C Programming Exercises, Control Flow Implementation, Function Usage, Array and Pointer Applications, Structure-based Programs, File I/O Operations |
| BEE151 | Basic Electrical & Electronics Engineering Lab | Lab | 1 | Circuit Laws Verification, Diode and Transistor Characteristics, Logic Gate Implementation, Rectifier Circuits, Op-Amp Applications, Transformer Testing |
Semester 2
| Subject Code | Subject Name | Subject Type | Credits | Key Topics |
|---|---|---|---|---|
| MAT201 | Engineering Mathematics - II | Core | 4 | Differential Equations, Laplace Transforms, Fourier Series, Probability and Statistics, Complex Numbers, Partial Differential Equations |
| CSE201 | Data Structures | Core | 4 | Arrays and Linked Lists, Stacks and Queues, Trees and Heaps, Graphs, Sorting Algorithms, Searching Techniques |
| CSE202 | Object Oriented Programming using C++ | Core | 4 | Classes and Objects, Inheritance, Polymorphism, Abstraction and Encapsulation, Constructors and Destructors, Exception Handling |
| ECE201 | Digital Logic Design | Core | 3 | Boolean Algebra and Logic Gates, Combinational Circuits, Sequential Circuits, Registers and Counters, Memory Elements, HDL Basics |
| EVS201 | Environmental Science & Engineering | Core | 2 | Ecosystems and Biodiversity, Environmental Pollution, Natural Resources, Waste Management, Climate Change, Environmental Policies |
| CSE251 | Data Structures Lab | Lab | 1 | Array and Linked List Operations, Stack and Queue Implementations, Tree Traversal Algorithms, Graph Algorithms Implementation, Sorting and Searching Practice, Dynamic Memory Allocation |
| CSE252 | Object Oriented Programming Lab | Lab | 1 | Class and Object Creation, Inheritance Implementation, Polymorphism Usage, Operator Overloading, File Handling in C++, Template Programming |
| ECE251 | Digital Logic Design Lab | Lab | 1 | Logic Gate Verification, Combinational Circuit Design, Sequential Circuit Implementation, Flip-Flop Applications, Counter and Register Design, Multiplexers and Demultiplexers |
Semester 3
| Subject Code | Subject Name | Subject Type | Credits | Key Topics |
|---|---|---|---|---|
| MAT301 | Discrete Mathematics | Core | 4 | Set Theory and Logic, Relations and Functions, Graph Theory, Combinatorics, Recurrence Relations, Algebraic Structures |
| CSE301 | Computer Organization & Architecture | Core | 4 | Basic Computer Structure, CPU Organization, Memory Hierarchy, Input/Output Organization, Instruction Set Architecture, Pipelining and Parallelism |
| CSE302 | Operating Systems | Core | 4 | Process Management, Memory Management, File Systems, I/O Management, Deadlocks, Concurrency and Synchronization |
| CSE303 | Design & Analysis of Algorithms | Core | 4 | Algorithm Analysis, Divide and Conquer, Greedy Algorithms, Dynamic Programming, Graph Algorithms, NP-Completeness |
| CSE304 | Software Engineering | Core | 3 | Software Development Life Cycle, Requirements Engineering, Software Design, Software Testing, Software Project Management, Software Quality Assurance |
| CSE352 | Operating Systems Lab | Lab | 1 | Linux Commands, Shell Scripting, Process Management Simulation, Memory Management Techniques, Deadlock Handling, Synchronization Problems |
| CSE353 | Design & Analysis of Algorithms Lab | Lab | 1 | Implementation of Sorting Algorithms, Graph Traversal Algorithms, Dynamic Programming Problems, Greedy Algorithm Solutions, Time Complexity Analysis, Divide and Conquer Implementations |
Semester 4
| Subject Code | Subject Name | Subject Type | Credits | Key Topics |
|---|---|---|---|---|
| CSE401 | Database Management Systems | Core | 4 | ER Model, Relational Model and Algebra, SQL Queries, Normalization, Transaction Management, Concurrency Control |
| CSE402 | Theory of Computation | Core | 4 | Finite Automata, Regular Expressions, Context-Free Grammars, Pushdown Automata, Turing Machines, Undecidability |
| CSE403 | Computer Networks | Core | 4 | OSI and TCP-IP Models, Data Link Layer, Network Layer, Transport Layer, Application Layer, Network Security Basics |
| CSE404 | Artificial Intelligence | Core | 4 | Intelligent Agents, Search Algorithms, Knowledge Representation, Machine Learning Fundamentals, Natural Language Processing, Expert Systems |
| CSE405 | Python Programming | Core | 3 | Python Fundamentals, Data Structures in Python, Functions and Modules, Object-Oriented Programming, File I/O, External Libraries (Numpy, Pandas) |
| CSE451 | Database Management Systems Lab | Lab | 1 | SQL Commands (DDL, DML), Advanced SQL Queries, Database Design, Normalization Practical, PL/SQL Programming, Database Connectivity |
| CSE453 | Computer Networks Lab | Lab | 1 | Network Device Configuration, TCP/UDP Socket Programming, Network Protocol Analysis, Routing Protocols Implementation, Client-Server Communication, Packet Tracing Tools |
| CSE455 | Python Programming Lab | Lab | 1 | Basic Python Scripting, Data Manipulation with Pandas, Data Visualization with Matplotlib, Object-Oriented Python, Web Scraping Basics, Module Creation and Usage |
Semester 5
| Subject Code | Subject Name | Subject Type | Credits | Key Topics |
|---|---|---|---|---|
| CSE501 | Compiler Design | Core | 4 | Lexical Analysis, Syntax Analysis, Semantic Analysis, Intermediate Code Generation, Code Optimization, Run-Time Environments |
| CSE502 | Machine Learning | Core | 4 | Supervised Learning, Unsupervised Learning, Regression Models, Classification Algorithms, Clustering Techniques, Model Evaluation and Validation |
| CSE503 | Web Technology | Core | 4 | HTML5 and CSS3, JavaScript Fundamentals, DOM Manipulation, Front-end Frameworks (React/Angular), Backend Development (Node.js/Python), Database Integration (MongoDB/MySQL) |
| CSEE5XX | Professional Elective – I (e.g., Cyber Security Fundamentals) | Elective | 3 | Introduction to Cryptography, Network Security Principles, Malware and Vulnerabilities, Cyber Attacks and Defense, Security Policies and Standards, Ethical Hacking Basics |
| CSP501 | Minor Project | Project | 2 | Problem Identification, Literature Review, System Design, Implementation Phase, Testing and Debugging, Project Documentation |
| CSE552 | Machine Learning Lab | Lab | 1 | Data Preprocessing using Python, Regression Model Implementation, Classification Algorithm Practice, Clustering Techniques, Model Hyperparameter Tuning, Scikit-learn and TensorFlow/Keras |
| CSE553 | Web Technology Lab | Lab | 1 | HTML/CSS Page Design, Interactive JavaScript Applications, Front-end Framework Practice, RESTful API Integration, Database Interaction via Web, Deployment of Web Applications |
Semester 6
| Subject Code | Subject Name | Subject Type | Credits | Key Topics |
|---|---|---|---|---|
| CSE601 | Cloud Computing | Core | 4 | Cloud Service Models (IaaS, PaaS, SaaS), Cloud Deployment Models, Virtualization Technologies, Cloud Security, Distributed Systems, Containerization (Docker, Kubernetes) |
| CSE602 | Cryptography & Network Security | Core | 4 | Symmetric Key Cryptography, Asymmetric Key Cryptography, Hash Functions and Digital Signatures, Firewalls and Intrusion Detection Systems, VPN and SSL/TLS, Cybersecurity Attacks and Defenses |
| CSE603 | Data Science | Core | 4 | Data Preprocessing, Exploratory Data Analysis, Statistical Methods for Data Science, Data Visualization, Predictive Modeling, Introduction to Big Data Tools |
| CSEE6XX | Professional Elective – II (e.g., Internet of Things) | Elective | 3 | IoT Architecture and Protocols, Sensors and Actuators, Communication Technologies for IoT, IoT Platforms and Cloud Integration, Data Analytics in IoT, IoT Security and Privacy |
| CSI601 | Internship / Industrial Training | Project | 2 | Real-world Problem Solving, Industry Best Practices, Teamwork and Collaboration, Professional Communication, Project Report Writing, Organizational Structure |
| CSP602 | Major Project – I | Project | 3 | Advanced Problem Definition, Detailed System Design, Module Development, Integration and Testing, Intermediate Progress Report, Presentation Skills |
| CSE651 | Cloud Computing Lab | Lab | 1 | Virtual Machine Provisioning, Cloud Storage Configuration, Serverless Computing, Container Deployment (Docker), Cloud Security Group Setup, Load Balancer Implementation |
| CSE653 | Data Science Lab | Lab | 1 | Data Cleaning and Transformation, Statistical Analysis with Python, Advanced Data Visualization, Machine Learning Model Training, Predictive Analytics Case Studies, Big Data Platform Basics |
Semester 7
| Subject Code | Subject Name | Subject Type | Credits | Key Topics |
|---|---|---|---|---|
| CSE701 | Big Data Analytics | Core | 4 | Hadoop Ecosystem, MapReduce Framework, Apache Spark, NoSQL Databases (Cassandra, MongoDB), Data Warehousing, Real-time Data Processing |
| CSE702 | Deep Learning | Core | 4 | Neural Network Architectures, Convolutional Neural Networks (CNNs), Recurrent Neural Networks (RNNs), Autoencoders and GANs, Deep Learning Frameworks (TensorFlow, PyTorch), Transfer Learning |
| CSEE7XX | Professional Elective – III (e.g., Mobile Application Development) | Elective | 3 | Android/iOS Architecture, UI/UX Design for Mobile, Data Storage and Retrieval, Networking and APIs, Push Notifications, App Deployment and Monetization |
| OEE7XX | Open Elective – I | Elective | 3 | Interdisciplinary subject chosen from other departments |
| CSP701 | Major Project – II | Project | 6 | Full System Implementation, Advanced Testing and Debugging, Performance Optimization, Deployment Strategies, Comprehensive Technical Report, Final Project Presentation and Defense |
Semester 8
| Subject Code | Subject Name | Subject Type | Credits | Key Topics |
|---|---|---|---|---|
| HSS801 | Professional Ethics & Values | Core | 2 | Ethical Theories, Professionalism and Responsibility, Cyber Ethics, Intellectual Property Rights, Workplace Ethics, Social Impact of Technology |
| CSEE8XX | Professional Elective – IV (e.g., Quantum Computing) | Elective | 3 | Quantum Bits (Qubits), Superposition and Entanglement, Quantum Gates, Quantum Algorithms (Shor''''s, Grover''''s), Quantum Cryptography, Quantum Hardware |
| OEE8XX | Open Elective – II | Elective | 3 | Interdisciplinary subject chosen from other departments |
| CSP801 | Project Work / Dissertation / Advanced Internship | Project | 8 | Research Methodology, Innovative Solution Development, Comprehensive Thesis Writing, Advanced Problem Solving, Industry Standard Deployment, Viva Voce Examination |
