The Bachelor of Technology in Artificial Intelligence at National Institute of Engineering and Technology (NIET), Kupondole, Lalitpur, is a four-year undergraduate program affiliated with Purbanchal University. The official program title is Bachelor of Technology in Artificial Intelligence, commonly written as B.Tech in AI.
The curriculum combines programming, mathematics, computer systems, data science and specialised artificial intelligence subjects. Project work begins in the second semester and continues throughout the remaining semesters. The final year includes an internship, two electives and a professional project.
NIET offers 48 seats in the program. The institute, formerly known as the College of Biomedical Engineering and Applied Sciences, conducts the course in Kupondole, Lalitpur.
| Field | Details |
|---|---|
| Course | Bachelor of Technology in Artificial Intelligence |
| Common title | B.Tech in AI |
| Institution | National Institute of Engineering and Technology |
| Location | Kupondole, Lalitpur |
| Affiliation | Purbanchal University |
| Faculty | Faculty of Science and Technology |
| Level | Bachelor’s degree |
| Duration | Four academic years |
| Academic structure | Eight semesters |
| Seats | 48 |
| Medium | English |
| Entrance examination | Conducted by Purbanchal University |
| Attendance requirement | At least 80% |
The B.Tech in Artificial Intelligence curriculum begins with programming, digital logic, calculus, technical communication and introductory AI. Later semesters cover data structures, algorithms, operating systems, databases, computer networks and computer organisation.
The specialised part of the curriculum includes Machine Learning, Pattern Recognition and Image Processing, Computer Vision, Deep Learning, Speech and Natural Language Processing, Reinforcement Learning and artificial intelligence programming tools.
Mathematics remains part of the course across several semesters. Students study Calculus, Linear Algebra, Probability and Statistics, Differential Equations, Numerical Methods and Optimization Techniques. These subjects support the mathematical and statistical work required in later AI courses.
The program also includes embedded systems, microprocessors, cloud computing and smart-city systems. This gives students exposure to software, computing infrastructure and connected systems alongside the central AI subjects.
The program may suit students who are prepared to study programming and mathematics throughout a four-year degree. It requires regular work in lectures, tutorials, laboratories, assignments and semester projects.
Students considering the course should be comfortable with subjects such as:
Mathematics and statistics
Computer programming
Logical and analytical problem-solving
Technical report writing
Laboratory and project work
Group assignments and presentations
Research methods
Software and computer systems
The curriculum does not begin only with specialised AI subjects. The first two years establish the programming, mathematical and computing foundation required for Machine Learning, Computer Vision, Deep Learning and related courses in the later semesters.
NIET’s stated admission requirement is the completion of 10+2 or an equivalent qualification with Physics, Chemistry and Mathematics. Applicants are required to have at least 50% aggregate marks.
Purbanchal University’s regulations for the Bachelor of Technology in Artificial Intelligence set the following academic eligibility:
Successful completion of twelve years of schooling in the science stream
A minimum D+ grade in every subject with a CGPA of 2.0 or above; or
At least second division, equivalent to 45%, in 10+2, PCL or an equivalent qualification in the science discipline
Successful completion of the entrance examination conducted by Purbanchal University
Applicants seeking admission at NIET are subject to the institute’s 50% aggregate requirement along with the university’s entrance and academic rules.
Students who have completed Grade 11 and are waiting for the Grade 12 supplementary examination may apply. They must submit all required academic documents when completing admission.
Students who have appeared in the final examination and are awaiting their results or certificates may also sit for the entrance examination. Their pending documents must be submitted during admission.
Applicants holding foreign academic certificates must submit an equivalence certificate issued by the concerned authority. They must also provide records showing individual subject grades, CGPA or total percentage.
Admission to the B.Tech in Artificial Intelligence program requires applicants to meet the academic eligibility criteria and pass the entrance examination conducted by Purbanchal University.
The main admission stages are:
Completion of 10+2 or an equivalent science qualification
Submission of the entrance application
Participation in the Purbanchal University entrance examination
Fulfilment of NIET’s academic admission requirement
Submission of academic certificates and other required documents
Completion of admission within the applicable institutional schedule
The entrance requirement applies even when an applicant has already met the minimum academic grades or marks.
The B.Tech in Artificial Intelligence extends over four academic years and is divided into eight semesters. English is the medium of instruction and examination for all subjects.
The first semester carries 18 credits. The second to sixth semesters each carry 17 credits. The seventh semester carries 11 credits, while the eighth semester carries 12 credits.
| Semester | Courses | Credits |
|---|---|---|
| First | Introduction to Programming; Digital Logic; Calculus; Introduction to Artificial Intelligence; Technical Report Writing and Presentation; Society and Professional Ethics | 18 |
| Second | Object Oriented Programming; Artificial Intelligence and Intelligent Systems; Microprocessor and Assembly Language; Probability and Statistics; Linear Algebra; Project I | 17 |
| Third | Database Management System; Data Structure and Algorithm; Computer Organization; Operating System; Differential Equations; Project II | 17 |
| Fourth | Numerical Methods; Computer Networks; Design and Analysis of Algorithms; Programming for AI: Tools, Techniques and Libraries; Introduction to Data Science; Project III | 17 |
| Fifth | Machine Learning; Optimization Techniques; Embedded Systems; Pattern Recognition and Image Processing; Data Warehousing and Mining; Project IV | 17 |
| Sixth | Object Oriented Software Engineering; Computer Vision; Deep Learning; Speech and Natural Language Processing; Research Methods; Project V | 17 |
| Seventh | Internship; Reinforcement Learning; Cloud Computing; Project VI | 11 |
| Eighth | IoT for Smart City; Elective I; Elective II; Professional Project | 12 |
The curriculum moves from foundational programming and mathematics to specialised subjects in the third and fourth years. Database systems, data structures, operating systems and computer networks are studied before the program moves into Machine Learning, Computer Vision, Deep Learning and Reinforcement Learning.
Project work begins with Project I in the second semester and continues through Project VI in the seventh semester. The eighth semester contains a separate Professional Project.
Students apply concepts from their other courses to a defined practical assignment. Project work covers:
Setting project aims and objectives
Planning and research
Technical implementation
Teamwork
Assessment
Report preparation
Presentation
Students may work in groups of up to three under the guidance of a group adviser. Each group identifies a project and sets its objectives before beginning the planned work.
The sequence allows project complexity to develop alongside the curriculum. Earlier projects accompany introductory programming and computing subjects, while later projects run alongside specialised courses such as Machine Learning, Computer Vision, Deep Learning and Reinforcement Learning.
The seventh semester includes a three-credit internship involving practical and fieldwork. It is studied alongside Reinforcement Learning, Cloud Computing and Project VI.
The internship gives students a separate practical component before the final semester. The program then concludes with two electives, IoT for Smart City and the Professional Project.
Students take two electives in the eighth semester. The elective list is organised across Computer Vision, Mathematics, Computing/IoT and Data Science.
Image and Video Processing
Surveillance Video Analytics
People Detection and Bio-metric Recognition
Introduction to Statistical Learning
Optimization Methods in Machine Learning/Convex Optimization
Kernel Methods
Bayesian Data Analysis
Smart Product Development
Predictive Analysis and IoT
Modeling and Simulation
Pervasive Computing
Fundamentals of Big Data Analytics
Data Analysis and Visualization
Business Intelligence
Social Media Analytics
The elective subjects allow students to extend their study in a selected technical area during the final semester.
Students are assessed throughout each semester. Continuous assessment may include participation in classes or tutorials, assignments, laboratory work, class tests and quizzes.
The distribution of marks depends on the type of course.
| Course category | Internal or practical assessment | Final assessment |
|---|---|---|
| Combined theory and laboratory course | 20% internal and 20% practical | 60% final examination |
| Theory course | 20% internal | 80% final examination |
| Laboratory or practical course | 60% continuous internal evaluation | 40% final university viva |
End-semester examinations are set and evaluated by examiners. Students are informed at the beginning of each course about the assessment methods and the weight assigned to different activities.
The program uses letter grades based on marks obtained through the applicable internal, practical and final assessments.
| Marks | Letter grade | Grade value |
|---|---|---|
| 90 and above | A+ | 4.00 |
| 80 to below 90 | A | 3.75 |
| 70 to below 80 | B+ | 3.50 |
| 60 to below 70 | B | 3.00 |
| 50 to below 60 | C | 2.50 |
| 40 to below 50 | D | 1.75 |
| Below 40 | F | 0.00 |
| Not qualified or absent | I | Incomplete |
An incomplete grade may be issued when a student has not submitted required work such as a term paper, report, home assignment or laboratory assignment. The outstanding requirement must be completed within six weeks from the end of the semester. Otherwise, the incomplete grade is converted into a fail grade.
A student must maintain a cumulative grade point average of at least 2.0 throughout the program. Failure to maintain the required CGPA may result in withdrawal from the course.
Students must maintain at least 80% attendance in lectures, tests and tutorial classes to qualify for the final examination in a subject.
When absence results from unavoidable circumstances, the missed academic work must be completed. Responsibility for completing that work rests with the student, with support from the concerned teachers.
The subjects, laboratories and projects provide structured practice in:
Programming and software development
Data structures and algorithm design
Database and operating-system concepts
Mathematical and statistical analysis
AI programming tools and libraries
Data science methods
Pattern recognition and image processing
Machine Learning
Computer Vision
Deep Learning
Speech and natural language processing
Embedded and connected systems
Research planning and technical reporting
Project design, teamwork and presentation
These areas arise directly across the semester curriculum rather than through a single isolated subject.
After completing the program, graduates may continue to postgraduate study in areas identified within the university regulations, including:
Master of Technology in Artificial Intelligence
Master of Science in Artificial Intelligence
Master of Computer Application
Master of Information Technology
Master of Science in Computer Science
Master of Science in Computer Information Systems
Master of Business Administration
Admission to any postgraduate program remains subject to the requirements of the concerned university or institution.
NIET offers merit-based and need-based scholarships. Merit-based support considers academic performance, while need-based support considers the applicant’s financial circumstances.
Scholarship allocation, amount and continuation conditions depend on the applicable criteria followed by the institute.
Alongside B.Tech in Artificial Intelligence, NIET offers:
These programs are also conducted under Purbanchal University.
The program takes four academic years and is divided into eight semesters.
NIET offers 48 seats in the B.Tech in Artificial Intelligence program.
Applicants must have completed 10+2 or an equivalent qualification in the science stream. NIET requires Physics, Chemistry and Mathematics with at least 50% aggregate marks. Applicants must also meet Purbanchal University’s eligibility and entrance requirements.
Yes. Applicants must pass the entrance examination conducted by Purbanchal University.
Students awaiting their final results or certificates may apply for the entrance examination. All required documents must be submitted during admission.
Yes. Project work begins in the second semester and continues through the seventh semester. The final semester includes a Professional Project.
Yes. A three-credit internship involving practical and fieldwork is included in the seventh semester.
English is the medium of instruction and examination.
Students must maintain at least 80% attendance in lectures, tests and tutorial classes to qualify for the final examination in a subject.
Students must maintain a CGPA of at least 2.0 throughout the program.
