Course Schedule Overview
The Bachelor of Network Engineering program spans four years, divided into eight semesters. Each semester includes a combination of core courses, departmental electives, science electives, and laboratory sessions designed to build foundational knowledge progressively.
| Semester | Course Code | Course Title | Credit Structure (L-T-P-C) | Prerequisites |
|---|---|---|---|---|
| 1 | CS101 | Introduction to Computer Science | 3-1-0-4 | - |
| 1 | MA101 | Mathematics I | 3-1-0-4 | - |
| 1 | PH101 | Physics for Computer Science | 3-1-0-4 | - |
| 1 | EC101 | Electronics Fundamentals | 3-1-0-4 | - |
| 1 | CS102 | Programming in C | 2-0-2-4 | - |
| 2 | CS201 | Data Structures and Algorithms | 3-1-0-4 | CS102 |
| 2 | MA201 | Mathematics II | 3-1-0-4 | MA101 |
| 2 | PH201 | Electromagnetic Fields and Waves | 3-1-0-4 | PH101 |
| 2 | CS202 | Object-Oriented Programming in Java | 2-0-2-4 | CS102 |
| 2 | EC201 | Digital Logic Design | 3-1-0-4 | EC101 |
| 3 | CS301 | Computer Networks I | 3-1-0-4 | CS201, EC201 |
| 3 | MA301 | Probability and Statistics | 3-1-0-4 | MA201 |
| 3 | CS302 | Operating Systems | 3-1-0-4 | CS201 |
| 3 | EC301 | Analog and Digital Communications | 3-1-0-4 | PH201, EC201 |
| 3 | CS303 | Database Management Systems | 3-1-0-4 | CS201 |
| 4 | CS401 | Computer Networks II | 3-1-0-4 | CS301 |
| 4 | MA401 | Numerical Methods | 3-1-0-4 | MA201 |
| 4 | CS402 | Software Engineering | 3-1-0-4 | CS201, CS302 |
| 4 | EC401 | Signal Processing and Control Systems | 3-1-0-4 | PH201, MA301 |
| 4 | CS403 | Web Technologies | 3-1-0-4 | CS302 |
| 5 | CS501 | Network Security and Cryptography | 3-1-0-4 | CS401 |
| 5 | CS502 | Wireless Communication Systems | 3-1-0-4 | CS401 |
| 5 | CS503 | Network Management and Monitoring | 3-1-0-4 | CS401 |
| 5 | CS504 | Cloud Computing Fundamentals | 3-1-0-4 | CS302 |
| 6 | CS601 | Advanced Network Protocols | 3-1-0-4 | CS501 |
| 6 | CS602 | IoT and Embedded Systems | 3-1-0-4 | CS502 |
| 6 | CS603 | Network Automation and DevOps | 3-1-0-4 | CS402 |
| 6 | CS604 | Artificial Intelligence in Networking | 3-1-0-4 | CS501 |
| 7 | CS701 | Mini Project I | 0-0-6-6 | CS501, CS502 |
| 7 | CS702 | Mini Project II | 0-0-6-6 | CS601, CS602 |
| 8 | CS801 | Final Year Thesis/Capstone Project | 0-0-12-12 | All previous semesters |
Advanced Departmental Electives
Advanced departmental electives are designed to deepen students' understanding of specialized areas within network engineering. Here are descriptions for some of the key courses:
Network Security and Cryptography
This course provides an in-depth exploration of cryptographic algorithms, secure communication protocols, and network defense mechanisms. Students learn how to implement and evaluate encryption standards like AES, RSA, and elliptic curve cryptography. The curriculum includes hands-on labs where students simulate real-world attacks and defend against them using industry-standard tools.
Wireless Communication Systems
This elective covers the principles of wireless transmission, including modulation techniques, multiple access schemes, and interference management. Students study 5G and future technologies, analyzing their impact on network infrastructure. Practical sessions involve building and testing wireless networks in controlled lab environments.
Network Management and Monitoring
This course focuses on tools and techniques used to monitor, manage, and optimize complex network infrastructures. Topics include performance metrics, fault detection, capacity planning, and network management protocols such as SNMP and NETCONF. Students gain experience with industry-grade monitoring platforms like Nagios and SolarWinds.
Cloud Computing Fundamentals
Students explore cloud architectures, service models (IaaS, PaaS, SaaS), and virtualization technologies. The course includes designing scalable cloud networks, integrating public and private clouds, and understanding security implications in distributed computing environments. Labs involve configuring cloud instances using AWS, Azure, and Google Cloud.
Advanced Network Protocols
This advanced elective delves into the intricacies of modern network protocols such as BGP, OSPF, and MPLS. Students analyze protocol behavior under various conditions and implement custom routing algorithms. The course emphasizes practical applications in large-scale enterprise networks and internet backbone systems.
IoT and Embedded Systems
This course explores the integration of sensors and devices into networked environments. Students learn about low-power communication protocols, edge computing, and real-time data processing. Labs focus on building IoT gateways and deploying sensor networks in smart city applications.
Network Automation and DevOps
The course introduces students to automation frameworks like Ansible, Puppet, and Chef, as well as CI/CD pipelines for network operations. Students learn how to automate network configuration, monitoring, and troubleshooting tasks. Practical exercises include deploying automated network testing suites and integrating infrastructure-as-code practices.
Artificial Intelligence in Networking
This cutting-edge course integrates AI and machine learning into network management. Students study neural networks, reinforcement learning, and predictive analytics applied to network performance optimization. Labs involve developing AI models that predict network failures or optimize bandwidth allocation.
Project-Based Learning Philosophy
The department emphasizes project-based learning as a cornerstone of the curriculum. Projects are structured to mirror real-world challenges faced by industry professionals, allowing students to apply theoretical knowledge in practical settings.
Mini-projects begin in the third year, with each student selecting a topic related to their area of interest. These projects span six weeks and culminate in a presentation and documentation. Students work under faculty supervision, receiving feedback throughout the process.
The final-year thesis is a significant undertaking that allows students to conduct independent research or develop innovative solutions for network engineering challenges. The selection process involves proposal submissions, mentor pairing, and regular progress reviews. Final presentations are held before a panel of faculty members and industry experts.