Offering Colleges (1)
Master of Technology in Artificial Intelligence (MTech in AI) program of Kathmandu University is a 2 years (4 semesters) full-time study program that will run in Pachkhal, KU.
Masters in Artificial Intelligence program of Kathmandu University aims to convey the body of skills, information, and practices connected with advanced computation, data science, and artificial intelligence (AI), which will help to open up new opportunities both locally and globally.
In particular, Masters in Artificial Intelligence program covers neural networks, fuzzy systems, and the use of evolutionary computation to create machines. The curriculum of this program mainly includes machine learning, neural network, big data analytics, information retrieval, fuzzy system, and evolutionary computation.
Masters in Artificial Intelligence will provide opportunities for experimental testing of what you have learned in order to tackle practical life issues related to various areas such as trade, economics, security, industrial control, and engineering.
Salient Features
This program will help to fulfill the demand of graduates in Artificial Intelligence in the global and local markets. This program will also assist the digital Nepal framework developed by the Government of Nepal.
The total tuition fees for the program of two years is NRs. 3,95,000.
Eligibility
Candidates with score of at least 50% in aggregate or CGPA 2.0 out of 4.0 grading system from any recognized institution, and
- Undergraduate in Engineering / Technology / Architecture / Computer Application (with honors), or
- Total of at least 16 years of education with science background, or
- M.Sc. in Physics, Chemistry, Mathematics, Statistics or any other related field.
Admission Criteria
The admission is open for Nepalese as well as foreign students.
Admission Test/ Interview: A written admission test of 1.5 hours would be conducted focusing on core computer subjects. The test would comprise both objective and subjective questions and would weigh 70% of marks. Only those securing a minimum of 40 marks in the written test would be selected for the interview. Successful candidates passing both the written test and the interview would be selected for admission on the basis of merit list.
Fees and Payment Information: Total course fee for the two year (4 semesters) study period is NRs 395,000/- (ordinary Nepalese student fee, which excludes NRs 10,000/- caution money and NRs 1000/- per year medical insurance) for ordinary Nepalese students. The fee for sponsored candidate is 1.5 times the ordinary fee.
Fee for SAARC country international candidate is 1.5 times the regular fee and for other country is 2.0 times the regular fee. Extension of period of study may subject to requirement of payment of additional fees for the extended study period.
Fee to be paid at the time of admission for ordinary Nepalese student is NRs. 136,000/- that includes first installment of first semester fee. Rest of the fee shall be paid in two installments per semester.
Admission Test Syllabus for ME Computer Engineering/ MTech IT/ MTech in AI
- Programming Basic structured programming concepts (Data Types, Operators), Object Oriented Programming Concepts (Objects, Class, Inheritance, Polymorphism)
- Data Structure and Algorithms Stack, Queue, Lists, Hash table, Sorting and Searching algorithms
- Database Management Systems Relational Database Concepts, ER Diagram, Normalization, Transaction
- Software Engineering Software Process Models, Planning & Scheduling, Testing
- Artificial Intelligence Problem Solving through Search, Logics, Current Trends in AI
- Computer Networks Basics of Computer Networks, TCP/IP, Physical Layer, Network Layer, Data Link Layer, Concepts of IP Addressing
Note: All six subjects carry equal weightage.
Curricular Structure
Artificial Intelligence Cluster Core (AICC)
| Number | Subject Name | Credit |
| 500 | Artificial Intelligence | 2+1 |
| 501 | Machine Learning | 2+1 |
| 502 | Data Analytics | 2+1 |
| 503 | Computational Intelligence | 2+1 |
| 504 | Deep Neural Networks | 2+1 |
| 505 | Intelligent System | 3 |
Artificial Intelligence Application Cluster (AIAC)
| Number | Subject Name | Credit |
| 530 | Big Data Analytics(Bio, Health, WSN, Social Network, | 3 |
| 531 | Deep Learning | 2+1 |
| 532 | Internet of Things (Internet of Vehicle, Internet of Health, Internet of people) | 3 |
| 533 | Evolutionary Computation | 2+1 |
| 534 | Computer Vision | 2+1 |
| 535 | Image Processing | 2_1 |
| 536 | Natural Image Processing | 2+1 |
| 537 | Recommendation System | 2+1 |
| 538 | Intelligent Information Retrieval | 2+1 |
| 539 | Knowledge Representation and Reasoning | 3 |
| 550 | Expert System Design | 2+1 |
| 551 | Robotic Design | 2+1 |
| 552 | Human Computer Interaction | 3 |
| 553 | Software Design | 2+1 |
| 554 | Problem Solving Agents | 3 |
| 555 | Predictive Modeling | 2+1 |
| 556 | Quantum Computiing | 2+1 |
Artificial Intelligence Mathematical Analysis (AIMA)
| Number | Subject Name | Credit |
| 500 | Computational Statistics and Probability | 3 |
| 501 | Statistical Methods for AI applications | 3 |
| 502 | Probabilistic Graphical Models | 3 |
| 503 | Fuzzy Systems | 3 |
| 504 | Discrete Multivariate Modeling | 3 |
| 505 | Computational Numerical Methods | 3 |
| 506 | Optimization Techniques | 3 |
Artificial Intelligence Research Work (AIRW)
| Number | Subject Name | Credit |
| 530 | Research Techniques for Computer Science | 3 |
| 531 | Topics in Data Science | 3 |
| 532 | AI and Society | 3 |
| 533 | Topics in AI | 3 |
| 534 | Seminar | 3 |
| 535 | Thesis | 15 |
Artificial Intelligence Guided Course ( AIGC)
| Number | Subject Name | Credit |
| 651 | Guided Course | 3 |