Institute of Engineering (IOE) Pulchowk Campus enrolls 20 students each year in Master of Science (M.Sc) in Computer System and Knowledge Engineering.
M.Sc. in Computer Systems and Knowledge Engineering (MS CSKE) course aims to provide students with expertise in the field of computer systems and knowledge engineering, mainly from the perspective of the hardware and software developer and programmer. It emphasises the design, development and programming of computer systems, embedded systems and computer engineering. The program has particular emphasis on embedded hardware and distributed software systems.
Knowledge engineering that involves integrating knowledge into computer systems in order to solve complex problems requiring a high level of human expertise. At present, it refers to the building, maintaining and development of knowledge based systems. It has a great deal in common with software engineering, and is used in many computer system domains such as artificial intelligence, including databases, data mining, expert systems, decision support systems and information systems. Knowledge engineering is also related to mathematical logic, as well as strongly involved in cognitive science and socio-cognitive engineering where the knowledge is produced by socio-cognitive aggregates and is structured according to our understanding of how human reasoning and logic works.
Option courses, along with the individual project, enable students to tailor a particular specialization to their own careers. As well as professional, analytical and management skills, students gain technical skills and knowledge at an advanced level.
Course duration: The duration of the course is two years in semester system. The last semester is dedicated for thesis work.
Course Structure: The course consists primarily of two types of courses; the core courses deal with the fundamental and application in different course areas whereas the elective courses deal with very specific details of the course. A student is allowed to select any relevant four courses from among the elective courses besides five core courses. The consistency of elective selection will be ensured with assistance from the faculty advisor. The course is thesis based and the student has to take a project work of 4 credits and a thesis of 20 credits. The student works under the guidance of the faculty advisor.
Credit System: The curriculum is organized in the framework of the credit system. Each course has a certain number of credits, which indicates the weightage. The number of credit depends upon the course contact hours. Normally a course is designed for 4 hours of lecture per week. The tutorial on each course may include laboratory, simulation works and assignment works as determined by the department.
Instructional Methods: The courses comprise of Lecturer, Tutorials, and Laboratory works, and seminars, short projects as applicable. The concerned faculty would give the assignments. Reference materials including international publications, journals, handbooks, web sites, related software etc will be used extensively. The course contents are designed in such a way that the students should use considerable self-learning efforts. Innovative approaches and ideas would be encouraged.
Qualifying Criteria: To qualify for the Master of Science in Information and Communications Engineering, a student must satisfactorily complete a program of course work of at least 60 credits including an individual thesis of 20 credits.
To be eligible for the admission to the M.Sc in Computer System and Knowledge Engineering, a candidate must have passed Bachelors degree in computer/electronics and communication engineering, electrical and electronics engineering or its equivalent from recognized institutions.
The candidate willing to appear in the entrance examination to get enrollment into the M.Sc. program should fill and submit the Application Form online within the deadline prescribed by the Entrance Exam Board. Application forms will be available in the websites: www.ioe.edu.np/entrance or http://entrance.ioe.edu.np. The application procedures are as follows:
1. The candidate should deposit required amount as an application fee for entrance examination in Account No mentioned in the notice by submitting a specially prepared voucher often by filling applicant's name and date of birth in it. The voucher No. indicated in the voucher needs to be specified in the online application form.
2. The candidate must select the appropriate entrance stream.
3. The candidate should fill up the other required fields in the form without skipping any steps.
4. The candidate also needs to upload his/her color photograph of prescribed specification and one of the following identification documents.
If any change has to be done on the submitted information in application form, candidate has to pay extra fee to edit six or less number of normal text fields. For name, photo or ID document correction, he/she has to pay more amounts at ICTC and submit a letter of request for correction with the payment voucher
Seat/Quota distribution for M.Sc Program
Master of Science in Computer Systems and Knowledge Engineering (MSCSKE) course consists primarily of two types of courses; the core courses deal with the fundamental and application in different course areas whereas the elective courses deal with very specific details of the course.
A student is allowed to select any relevant three courses from among the elective courses besides seven core courses. The consistency of elective selection will be ensured with assistance from the faculty advisor. The course is thesis based and the student has to take a project work of 4 credits in 2nd Semester and a thesis of 16 credits in 4th Semester. The student works under the guidance of the faculty advisor. The detailed course structure is given in section 2 below
Elective courses will be offered as per the availability of resource persons. The lists of elective courses are as follows:
· Web Information system
· Human Computer Interaction
· Geographical Information system
· Management Information system
· Decision support system
· e-Government system
· Multimedia system
· Object Oriented Distributed system
· Real time system design
· Computer system Simulation
· Data Warehousing and Data Mining
· Semantic web
· Grid Computing
· Genetic algorithm and Machine Learning
· Fuzzy Expert systems and fuzzy reasoning
· Speech and Language processing
· Software reuse
· Embedded system
· Bio Informatics
· Smart Systems : Algorithms and Tools
· Advanced Data Mining : Algorithms & Applications
· Engineering Decision Analysis
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