Curriculum
The Computer Science curriculum at Bishamber Sahai Diploma Engineering College is meticulously designed to provide students with a strong foundation in both theoretical concepts and practical applications. The program spans eight semesters, offering a progressive learning experience that builds upon previously acquired knowledge while introducing advanced topics relevant to the evolving technology landscape.
Each semester includes a combination of core courses, departmental electives, science electives, and laboratory sessions that are strategically aligned with industry needs and academic excellence. The curriculum emphasizes hands-on experience through lab work, group projects, internships, and capstone projects that prepare students for real-world challenges in the field of computer science.
Course Structure Across All Eight Semesters
| Semester | Course Code | Course Title | Credit Structure (L-T-P-C) | Prerequisites |
|---|---|---|---|---|
| I | CS101 | Introduction to Programming | 3-0-0-3 | None |
| I | CS102 | Mathematics for Computer Science | 4-0-0-4 | None |
| I | CS103 | Digital Logic Design | 3-0-0-3 | None |
| I | CS104 | Computer Organization and Architecture | 3-0-0-3 | None |
| I | CS105 | Engineering Graphics and Design | 2-0-0-2 | None |
| I | CS106 | English for Technical Communication | 3-0-0-3 | None |
| II | CS201 | Data Structures and Algorithms | 4-0-0-4 | CS101, CS102 |
| II | CS202 | Object Oriented Programming | 3-0-0-3 | CS101 |
| II | CS203 | Database Management Systems | 3-0-0-3 | CS101, CS201 |
| II | CS204 | Operating Systems | 3-0-0-3 | CS104, CS202 |
| II | CS205 | Discrete Mathematics | 4-0-0-4 | CS102 |
| III | CS301 | Software Engineering | 3-0-0-3 | CS201, CS202 |
| III | CS302 | Computer Networks | 3-0-0-3 | CS104, CS204 |
| III | CS303 | Compiler Design | 3-0-0-3 | CS201, CS202 |
| III | CS304 | Artificial Intelligence | 3-0-0-3 | CS201, CS205 |
| III | CS305 | Web Technologies | 3-0-0-3 | CS202 |
| IV | CS401 | Machine Learning | 3-0-0-3 | CS201, CS205 |
| IV | CS402 | Cybersecurity | 3-0-0-3 | CS204, CS302 |
| IV | CS403 | Cloud Computing | 3-0-0-3 | CS302 |
| IV | CS404 | Data Mining and Warehousing | 3-0-0-3 | CS201, CS205 |
| IV | CS405 | Human Computer Interaction | 3-0-0-3 | CS202 |
| V | CS501 | Big Data Analytics | 3-0-0-3 | CS404 |
| V | CS502 | Internet of Things (IoT) | 3-0-0-3 | CS302 |
| V | CS503 | Mobile Computing | 3-0-0-3 | CS202 |
| V | CS504 | Embedded Systems | 3-0-0-3 | CS104 |
| V | CS505 | Blockchain Technology | 3-0-0-3 | CS201, CS302 |
| VI | CS601 | Advanced Software Engineering | 3-0-0-3 | CS301 |
| VI | CS602 | Distributed Systems | 3-0-0-3 | CS302 |
| VI | CS603 | Neural Networks and Deep Learning | 3-0-0-3 | CS401 |
| VI | CS604 | Network Security | 3-0-0-3 | CS402 |
| VI | CS605 | DevOps and Automation | 3-0-0-3 | CS301 |
| VII | CS701 | Research Methodology | 2-0-0-2 | CS201, CS205 |
| VII | CS702 | Capstone Project I | 4-0-0-4 | CS301, CS401 |
| VIII | CS801 | Capstone Project II | 4-0-0-4 | CS702 |
| VIII | CS802 | Internship | 4-0-0-4 | CS601, CS702 |
Detailed Course Descriptions for Advanced Departmental Electives
The department offers several advanced departmental elective courses that allow students to delve deeper into specialized areas of interest. These courses are designed to provide in-depth knowledge and practical skills relevant to current industry demands.
- Advanced Machine Learning: This course explores advanced topics such as reinforcement learning, generative adversarial networks, transformers, attention mechanisms, and large language models. Students engage in hands-on projects involving real-world datasets and applications.
- Cryptography and Network Security: Focused on modern cryptographic techniques and security protocols, this course covers symmetric and asymmetric encryption, digital signatures, authentication protocols, and secure network design principles.
- Big Data Analytics: Students learn to process and analyze large datasets using tools like Apache Spark, Hadoop, and NoSQL databases. The course emphasizes data warehousing, ETL processes, and predictive analytics for business intelligence.
- Cloud Computing Architecture: This elective delves into cloud service models (IaaS, PaaS, SaaS), virtualization technologies, containerization with Docker, orchestration using Kubernetes, and cloud security frameworks.
- Internet of Things (IoT) Systems Design: Students explore IoT architecture, sensor networks, wireless communication protocols, edge computing, and real-time data processing systems for smart cities and industrial automation.
- Software Testing and Quality Assurance: This course covers various testing methodologies, automated testing frameworks, quality metrics, software reliability, and compliance standards in agile development environments.
- Human-Computer Interaction (HCI) Design: Emphasizing user-centered design principles, this elective focuses on usability testing, accessibility guidelines, cognitive psychology in interface design, and emerging interaction paradigms like voice and gesture-based interfaces.
- DevOps Practices and Automation: Students learn CI/CD pipelines, infrastructure as code (IaC), container orchestration, monitoring tools, and automation frameworks for software delivery and deployment processes.
- Data Mining and Predictive Modeling: This course introduces advanced data mining techniques, association rule mining, clustering algorithms, classification methods, and time series forecasting using machine learning models.
- Quantum Computing Fundamentals: An introductory course to quantum computing concepts, qubits, quantum gates, superposition, entanglement, and applications in cryptography and optimization problems.
The philosophy of project-based learning at Bishamber Sahai Diploma Engineering College is centered around fostering innovation, collaboration, and real-world problem-solving skills. Students are encouraged to take ownership of their projects from conception to execution, with guidance from faculty mentors throughout the process.
Mini-projects are assigned in the second and third years, allowing students to apply theoretical knowledge to practical scenarios. These projects typically span 2-3 months and involve team collaboration, research, implementation, testing, and documentation. Evaluation criteria include project design, technical execution, innovation, presentation quality, and peer review feedback.
The final-year thesis/capstone project is a comprehensive endeavor that integrates all aspects of the student's learning experience. Projects are selected in consultation with faculty mentors based on student interests, available resources, and alignment with industry needs. The process includes proposal submission, literature review, design phase, implementation, testing, and final presentation before a panel of experts.