Comprehensive Curriculum Overview
The Computer Engineering program at Government Polytechnic Bachalikhal is designed to provide students with a robust foundation in both theoretical and practical aspects of computing. The curriculum spans eight semesters, integrating core engineering principles with specialized electives tailored to meet industry demands.
Year 1 Semester-wise Course Structure
| Semester | Course Code | Course Title | Credit (L-T-P-C) | Pre-requisites |
|---|---|---|---|---|
| I | CE101 | Engineering Mathematics I | 3-1-0-4 | - |
| I | CE102 | Physics for Engineering | 3-1-0-4 | - |
| I | CE103 | Chemistry for Engineering | 3-1-0-4 | - |
| I | CE104 | English Communication Skills | 2-0-0-2 | - |
| I | CE105 | Introduction to Programming | 3-1-0-4 | - |
| I | CE106 | Digital Electronics | 3-1-0-4 | - |
| I | CE107 | Engineering Drawing | 2-0-0-2 | - |
Year 2 Semester-wise Course Structure
| Semester | Course Code | Course Title | Credit (L-T-P-C) | Pre-requisites |
|---|---|---|---|---|
| II | CE201 | Engineering Mathematics II | 3-1-0-4 | CE101 |
| II | CE202 | Electrical Circuits and Networks | 3-1-0-4 | - |
| II | CE203 | Data Structures and Algorithms | 3-1-0-4 | CE105 |
| II | CE204 | Object Oriented Programming with C++ | 3-1-0-4 | CE105 |
| II | CE205 | Computer Organization and Architecture | 3-1-0-4 | CE106 |
| II | CE206 | Electronic Devices and Circuits | 3-1-0-4 | CE102 |
| II | CE207 | Engineering Ethics and Professionalism | 2-0-0-2 | - |
Year 3 Semester-wise Course Structure
| Semester | Course Code | Course Title | Credit (L-T-P-C) | Pre-requisites |
|---|---|---|---|---|
| III | CE301 | Engineering Mathematics III | 3-1-0-4 | CE201 |
| III | CE302 | Database Management Systems | 3-1-0-4 | CE203 |
| III | CE303 | Microprocessor Architecture and Assembly Language Programming | 3-1-0-4 | CE205 |
| III | CE304 | Signals and Systems | 3-1-0-4 | CE201 |
| III | CE305 | Operating Systems | 3-1-0-4 | CE203 |
| III | CE306 | Network Fundamentals | 3-1-0-4 | CE202 |
Year 4 Semester-wise Course Structure
| Semester | Course Code | Course Title | Credit (L-T-P-C) | Pre-requisites |
|---|---|---|---|---|
| IV | CE401 | Computer Graphics and Multimedia | 3-1-0-4 | CE203 |
| IV | CE402 | Software Engineering and Project Management | 3-1-0-4 | CE203 |
| IV | CE403 | Digital Signal Processing | 3-1-0-4 | CE304 |
| IV | CE404 | Embedded Systems | 3-1-0-4 | CE205 |
| IV | CE405 | Artificial Intelligence and Machine Learning | 3-1-0-4 | CE203 |
| IV | CE406 | Cybersecurity Fundamentals | 3-1-0-4 | CE306 |
Advanced Departmental Elective Courses
The department offers a range of advanced elective courses that allow students to explore specialized areas within computer engineering. These courses are designed to provide in-depth knowledge and practical skills relevant to emerging technologies and industry demands.
Artificial Intelligence and Machine Learning
This course introduces students to the fundamentals of artificial intelligence, including search algorithms, knowledge representation, reasoning, and machine learning techniques. It covers supervised and unsupervised learning methods, neural networks, deep learning architectures, and applications in natural language processing and computer vision.
Cybersecurity and Network Security
Students learn about cryptographic systems, network security protocols, intrusion detection systems, and secure software development practices. The course emphasizes hands-on experience with security tools and techniques used to protect digital assets against cyber threats.
Embedded Systems Design
This elective focuses on designing and implementing embedded systems for various applications. Students study microcontroller architectures, real-time operating systems, sensor integration, and hardware-software co-design principles.
Internet of Things (IoT) Technologies
The course explores the architecture and implementation of IoT systems, covering wireless communication protocols, cloud computing integration, data analytics, and security considerations for connected devices.
Software Testing and Quality Assurance
This course provides students with knowledge of software testing methodologies, quality assurance processes, and automation tools. It covers functional and non-functional testing techniques, test case design, and performance evaluation methods.
High-Performance Computing
Students explore parallel processing architectures, distributed computing models, GPU programming, and optimization techniques for large-scale computational tasks. The course includes practical projects involving cluster computing and supercomputing environments.
Data Mining and Big Data Analytics
This course covers data preprocessing, pattern recognition, clustering algorithms, classification techniques, and predictive modeling. Students gain hands-on experience with big data platforms like Hadoop and Spark for analyzing large datasets.
Mobile Application Development
The course focuses on developing cross-platform mobile applications using modern frameworks and tools. Students learn about UI/UX design principles, app deployment strategies, and integration with backend services.
Cloud Computing and DevOps
This elective covers cloud service models, virtualization technologies, containerization, automation tools, and continuous integration/continuous delivery (CI/CD) pipelines. It prepares students for careers in cloud-native development and infrastructure management.
Computer Vision and Image Processing
Students study image acquisition, enhancement, segmentation, feature extraction, and recognition techniques. The course includes practical applications in robotics, medical imaging, surveillance systems, and autonomous vehicles.
Project-Based Learning Philosophy
The department places significant emphasis on project-based learning to enhance students' understanding of theoretical concepts through practical application. This approach fosters creativity, problem-solving skills, and teamwork among students.
Mini-Projects
Mini-projects are assigned during the second year of the program, allowing students to apply fundamental knowledge in real-world scenarios. These projects typically span one semester and involve working in small teams under faculty supervision. Students are expected to document their work through technical reports and present findings to peers and faculty members.
Final-Year Thesis/Capstone Project
The final-year thesis is a comprehensive project that integrates all learned skills over the four-year program. Students select a topic aligned with their interests or industry requirements, conduct extensive research, develop prototypes, and present results in a formal thesis format. Faculty mentors guide students throughout this process, ensuring academic rigor and practical relevance.
Project Selection and Mentorship
Students can choose projects based on faculty research areas or industry collaborations. The department facilitates mentorship by matching students with suitable faculty advisors who provide guidance on project scope, methodology, and evaluation criteria. Regular progress meetings ensure timely completion and quality outcomes.