Curriculum Overview
The curriculum of the Computer Engineering program at Government Polytechnic Tanakpur is meticulously structured to provide a comprehensive education that bridges theory and practice. The program spans four years, divided into eight semesters, with each semester containing a mix of core courses, departmental electives, science electives, and laboratory sessions.
| Semester | Course Code | Course Title | Credit (L-T-P-C) | Pre-requisites |
|---|---|---|---|---|
| 1 | CE101 | Engineering Mathematics I | 3-1-0-4 | None |
| 1 | CE102 | Physics for Computer Engineering | 3-1-0-4 | None |
| 1 | CE103 | Introduction to Programming using C | 2-0-2-3 | None |
| 1 | CE104 | Engineering Drawing and Graphics | 1-0-3-2 | None |
| 1 | CE105 | Basic Electrical Engineering | 3-1-0-4 | None |
| 1 | CE106 | Communication Skills | 2-0-0-2 | None |
| 2 | CE201 | Engineering Mathematics II | 3-1-0-4 | CE101 |
| 2 | CE202 | Chemistry for Engineering | 3-1-0-4 | None |
| 2 | CE203 | Data Structures and Algorithms | 3-1-0-4 | CE103 |
| 2 | CE204 | Electronic Devices and Circuits | 3-1-0-4 | CE105 |
| 2 | CE205 | Computer Organization and Architecture | 3-1-0-4 | CE103 |
| 2 | CE206 | English for Technical Communication | 2-0-0-2 | None |
| 3 | CE301 | Probability and Statistics | 3-1-0-4 | CE201 |
| 3 | CE302 | Digital Logic Design | 3-1-0-4 | CE204 |
| 3 | CE303 | Operating Systems | 3-1-0-4 | CE205 |
| 3 | CE304 | Database Management Systems | 3-1-0-4 | CE203 |
| 3 | CE305 | Software Engineering | 3-1-0-4 | CE203 |
| 3 | CE306 | Signals and Systems | 3-1-0-4 | CE201 |
| 4 | CE401 | Microprocessors and Microcontrollers | 3-1-0-4 | CE205 |
| 4 | CE402 | Computer Networks | 3-1-0-4 | CE303 |
| 4 | CE403 | Object-Oriented Programming using C++ | 2-0-2-3 | CE103 |
| 4 | CE404 | Embedded Systems Design | 3-1-0-4 | CE302 |
| 4 | CE405 | Human Computer Interaction | 3-1-0-4 | CE203 |
| 4 | CE406 | Discrete Mathematics | 3-1-0-4 | CE201 |
| 5 | CE501 | Artificial Intelligence and Machine Learning | 3-1-0-4 | CE303 |
| 5 | CE502 | Cybersecurity Fundamentals | 3-1-0-4 | CE402 |
| 5 | CE503 | Data Mining and Warehousing | 3-1-0-4 | CE304 |
| 5 | CE504 | Cloud Computing | 3-1-0-4 | CE402 |
| 5 | CE505 | Internet of Things (IoT) | 3-1-0-4 | CE404 |
| 5 | CE506 | Computer Graphics and Animation | 3-1-0-4 | CE203 |
| 6 | CE601 | Advanced Data Structures | 3-1-0-4 | CE203 |
| 6 | CE602 | Distributed Systems | 3-1-0-4 | CE402 |
| 6 | CE603 | Reinforcement Learning | 3-1-0-4 | CE501 |
| 6 | CE604 | Network Security | 3-1-0-4 | CE502 |
| 6 | CE605 | Mobile Application Development | 3-1-0-4 | CE403 |
| 6 | CE606 | Computer Vision | 3-1-0-4 | CE501 |
| 7 | CE701 | Capstone Project I | 2-0-6-8 | CE501, CE502 |
| 7 | CE702 | Research Methodology | 3-1-0-4 | CE301 |
| 7 | CE703 | Advanced Topics in Computer Engineering | 3-1-0-4 | CE601 |
| 7 | CE704 | Entrepreneurship and Innovation | 2-0-0-2 | None |
| 7 | CE705 | Professional Ethics and Legal Aspects | 2-0-0-2 | None |
| 7 | CE706 | Internship Preparation Workshop | 1-0-3-2 | None |
| 8 | CE801 | Capstone Project II | 2-0-6-8 | CE701 |
| 8 | CE802 | Final Year Thesis | 4-0-0-4 | CE702 |
| 8 | CE803 | Industry Internship | 4-0-0-4 | CE701 |
| 8 | CE804 | Professional Development Workshop | 2-0-0-2 | None |
| 8 | CE805 | Project Presentation and Viva Voce | 1-0-3-2 | CE801 |
Advanced departmental elective courses include:
- Artificial Intelligence and Machine Learning: Focuses on neural networks, deep learning frameworks, reinforcement learning, and natural language processing. Students gain expertise in building intelligent systems using Python and TensorFlow.
- Cybersecurity Fundamentals: Covers network security protocols, encryption techniques, threat analysis, and incident response strategies. Emphasis is placed on protecting digital assets from cyber threats.
- Data Mining and Warehousing: Teaches students how to extract valuable insights from large datasets using SQL, Python, and specialized tools like Apache Spark and Hadoop.
- Cloud Computing: Introduces cloud architecture models, service delivery mechanisms, virtualization technologies, and major platforms such as AWS, Azure, and GCP.
- Internet of Things (IoT): Explores sensor networks, communication protocols, embedded systems integration, and smart city applications. Students build IoT projects using Raspberry Pi and Arduino.
- Computer Graphics and Animation: Delves into 3D modeling techniques, rendering algorithms, animation principles, and game development using Unity or Unreal Engine.
- Advanced Data Structures: Builds upon foundational knowledge to explore advanced structures like B-trees, hash tables, and graph algorithms with real-world applications in optimization problems.
- Distributed Systems: Covers fault tolerance, consensus protocols, distributed databases, and parallel computing paradigms essential for scalable software solutions.
- Reinforcement Learning: Focuses on decision-making processes in uncertain environments using algorithms like Q-learning, policy gradients, and actor-critic methods.
- Network Security: Analyzes vulnerabilities in network infrastructures and develops countermeasures using firewalls, IDS/IPS, and secure communication protocols.
The department's philosophy on project-based learning emphasizes experiential education that integrates classroom knowledge with real-world problem-solving. Mini-projects are assigned in the second and third years to encourage early exposure to engineering challenges. These projects involve working in teams, applying theoretical concepts, and presenting solutions to faculty and peers.
The final-year thesis/capstone project is a comprehensive endeavor where students select topics aligned with their specialization interests. Faculty mentors guide students through research methodologies, experimental design, data analysis, and documentation. Projects are evaluated based on innovation, technical depth, presentation quality, and peer feedback.
Students have the flexibility to choose projects that align with current industry trends or personal interests. The selection process involves submitting proposals, undergoing faculty review, and receiving guidance throughout the development phase. This approach ensures students develop both technical proficiency and entrepreneurial mindset necessary for success in competitive fields.