- Fee:NPR 304,500
Offering Colleges
The Far Western University (FWU) is offering the course in Bachelors Degree in Computer Engineering. The objective of this course is to produce skilled, qualified Computer Engineers that work for software development, network design and implementation, hardware and software troubleshooting, network security policies, etc. A strong theoretical foundation with sufficient practical exposure prepares students to solve real-world problems.
The total number of available seats in the program is 48. Engineering classes are conducted in the day shift.
Fee Structure for BE Computer Engineering (2077-78 Batch)
- Open Category: 304,500
- Scholarship Category: 57,500
Salient Features
Each course is specified with lecture, tutorial, and practical hours per week. The method of instruction is a lecture, enhanced by tutorials, and/or practical depending upon the relevancy of the course. Tutorials are used to widen the concepts stated in the course. Practical and laboratory classes are used to develop necessary concepts and basic skills.
Scholarships
Far Western University offers scholarships on various bases. For scholarships please contact the university.
Eligibility
The candidates seeking admissions in BE Computer Engineering must have completed 10+2 from a recognized institution or any equivalent degree (A-level, Diploma in Engineering) with major in Physics, Chemistry, and Mathematics.
The candidates are required to have secured 'C' Grade or 45% or equivalent from a recognized board.
Admission Criteria
Candidates can apply online from the website of Far Western University at www.fwu.edu.np.
Candidates are required to submit the forms as listed below while submitting an online application:
- Citizenship
- Passport-sized photo
- Marksheet of SLC/SEE, Provisional certificate, Migration Certificate, and Character certificate
- Transcript of +2 level, Provisional certificate, Migration certificate, and Character certificate
Contact details:
Address: Mahendranagar, Kanchanpur
Contact number: 977 (99) 520729 | 977 (99) 520727
email: info@fwu.edu.npOfficial
Website: http://fwu.edu.np/
Curricular Structure
This course is divided into eight semesters. The first-year courses include fundamental common subjects. The second and third-year courses generally include specific courses of the related discipline. The fourth-year courses include professional and application-type courses.
The course structure provides subject-wise information about the lecture, tutorial, and practical hours per week, full marks and pass marks for the internal and final examination and the duration of the final examination.
Credit Hours
This is a full-time course with 141 credit hours, Each student has to choose 2 elective subjects equivalent to 6 credit hours and one minor project of 3 credit hours. A field-based major project of 6 credit hours should be taken.
Internal Assessment and Final (End Semester) ExaminationThe student’s performance in each subject is evaluated by internal and final examination. Internal Assessment40 % of the total marks is allocated for internal assessment for the theory part of all subjects. Internal assessment marks should include class attendance and performance, timely submission, and correctness of assignments, class tests, quizzes, etc.
Evaluation of the practical part of most of the subjects is done through continuous assessment. It includes lab performance, report submission, presentation, viva, etc. However, for few courses, final examinations are also conducted.70 % attendance is mandatory to qualify for the final examination. Final ExaminationExaminations of theoretical subjects are conducted as per the academic calendar of FWU. The duration of the final examination will be of 3 hours for most of the subjects.
Pass MarksEach student must obtain 45 % in both internal assessment and final examination of each subject to pass in a particular subject. Only students who have passed the internal assessment of a particular subject are allowed to appear in the final examination of that subject.
Evaluation SystemStudents are evaluated on a continuous basis throughout the semester. Evaluation is done by the faculty, a consequence of the autonomous status granted to the faculty of engineering. Project work is evaluated on the basis of the review by internal and external examiners. For successful completion of the course, students should pass all the components of all subjects in all semesters. The overall performance of each student is measured by a cumulative grade point average.Depending upon the final weightage aggregate percentage scored by a student, a division is awarded as follows:CGPA > 3.6: Distinction DivisionCGPA < 3.6 and ≥ 3.0: First DivisionCGPA < 3.0 and ≥ 2.0: Second DivisionCGPA < 2.0 and ≥ 1.0: Pass Division
Curriculum Structure
| First Year | First Semester | ||
| Course Code | Course | Credits |
| AR 111 | Engineering Drawing | 2 |
| SH 112 | Engineering Math I | 3 |
| SH 113 | Engineering Physics | 3 |
| EE 114 | Basic Electrical Engineering | 3 |
| CT 115 | Programming in C | 3 |
| ME 116 | Workshop Technology | 1 |
| Total | 15 | |
| First Year | Second Semester | ||
| Course Code | Course | Credits |
| SH 121 | Engineering Math II | 3 |
| SH 122 | Engineering Chemistry | 3 |
| ME 123 | Thermodynamics | 3 |
| CE 124 | Applied Mechanics | 3 |
| CT 125 | Object-Oriented Programming | 3 |
| CT 126 | Discrete Structure | 2 |
| Total | 17 | |
| Second Year | Third Semester | ||
| Course Code | Course | Credits |
| SH 231 | Engineering Math III | 3 |
| CT 232 | Data Structure and Algorithm | 3 |
| CT 233 | Theory of Computation | 3 |
| EE 234 | Electrical Circuit Theory Course | 3 |
| EX 235 | Digital Logic | 3 |
| EX 236 | Electromagnetics | 3 |
| Total | 18 | |
| Second Year | Fourth Semester | ||
| Course Code | Course | Credits |
| SH 241 | Applied Mathematics | 3 |
| EX 242 | Microprocessor | 3 |
| CT 243 | Algorithmic Mathematics | 3 |
| EE 244 | Electrical Machine | 3 |
| EX 245 | Electronic Device and Circuit | 3 |
| SH 246 | Communication English | 3 |
| Total | 18 | |
| Third Year | Fifth Semester | ||
| Course Code | Course | Credits |
| SH 351 | Probability and Statistic | 3 |
| EX 352 | Instrumentation | 3 |
| EX 353 | Computer Graphics | 3 |
| CT 354 | Object-Oriented Software Engineering | 3 |
| CT 355 | Computer Architecture and Design | 3 |
| CT 356 | Operating System | 3 |
| Total | 18 | |
| Third Year | Sixth Semester | ||
| Course Code | Course | Credits |
| CT 361 | Project and Organization Management | 3 |
| CT 362 | Research Methodology | 2 |
| CT 363 | Artificial Intelligence | 3 |
| CT 364 | Database Management System | 3 |
| EX 365 | Communication System | 3 |
| SH 366 | Engineering Economics | 2 |
| CT 367 | Minor Project | 3 |
| Total | 19 | |
| Fourth Year | Seventh Semester | ||
| Course Code | Course | Credits |
| CT 471 | Computer Networks | 3 |
| CT 472 | Distributed Computing | 3 |
| CT 473 | Information System | 2 |
| CT 474 | Data Mining and Data Warehousing | 3 |
| CT 475 | Simulation and Modelling | 2 |
| CT | Elective I | 3 |
| CT 476 | Project - Part A | 2 |
| Total | 18 | |
| Fourth Year | Eighth Semester | ||
| Course Code | Course | Credits |
| CT 481 | Digital Signal Analysis and Processing | 3 |
| CE 482 | Engineering Professional Practice | 2 |
| CT 483 | Information Security | 3 |
| CT 484 | Big Data | 3 |
| CT | Elective - II | 3 |
| CT 485 | Project - Part B | 4 |
| Total | 18 | |
| Elective I | ||
| Code No. | Subject | Credits |
| CT 4701 | Multimedia System | 3 |
| CT 4702 | Image Processing and Pattern Recognition | 3 |
| CT 4703 | Networking with IPV6 | 3 |
| CT 4704 | Geographical Information System | 3 |
| CT 4705 | Agile Software Development | 3 |
| CT 4706 | Embedded System | 3 |
| CT 4707 | Software Project Management | 3 |
| CT 4708 | Internet and Intranet | 3 |
| Elective II | ||
| Code No. | Subject | Credits |
| CT 4801 | Enterprise Application Design and Development | 3 |
| CT 4802 | Internet of Things | 3 |
| CT 4803 | Distributed and Object-Oriented Database | 3 |
| CT 4804 | e-Government System | 3 |
| CT 4805 | Web Technology | 3 |
| CT 4806 | Machine Learning | 3 |