B.Tech in AI

Bachelor of Technology in Artificial Intelligence (B.Tech AI) at Kantipur International College

The Bachelor of Technology in Artificial Intelligence (B.Tech AI) at Kantipur International College (KIC) is a four-year undergraduate technology program affiliated with Purbanchal University. The program falls under the Faculty of Science and Technology and is organized across eight semesters.

It begins with programming, mathematics, digital logic, and introductory artificial intelligence before moving into databases, algorithms, operating systems, data science, Machine Learning, Deep Learning, Natural Language Processing, reinforcement learning, cloud computing, electives, internship, and project work. Project study begins in the second semester and continues throughout the remaining semesters.

Quick Highlights

B.Tech AI Program Overview

The B.Tech AI curriculum combines computing foundations with progressively specialized study in artificial intelligence.

The first year establishes the mathematical and programming base through Introduction to Programming, Digital Logic, Calculus, Probability and Statistics, Linear Algebra, Object Oriented Programming, and introductory AI subjects. Technical Report Writing and Presentation and Society and Professional Ethics are also included in the opening semester.

The second year shifts toward the core computing systems required for advanced technical study. Database Management System, Data Structure and Algorithm, Computer Organization, Operating System, Numerical Methods, Computer Networks, Design and Analysis of Algorithms, Programming for AI, and Introduction to Data Science are part of this stage.

By the third year, students move into subjects directly concerned with learning systems, optimization, image-related processing, data mining, software engineering, speech, language processing, and research.

Semester-Wise Curriculum

The third-year curriculum marks a clear transition from general computing into more specialized AI study. Semester V contains Machine Learning, Optimization Techniques, Embedded Systems, Pattern Recognition and Image Processing, and Data Warehousing and Mining. Semester VI follows with Object Oriented Software Engineering, Computer Vision, Deep Learning, Speech and Natural Language Processing, and Research Methods.

The final year combines internship, Reinforcement Learning, Cloud Computing, IoT for Smart City, electives, and project work.

Project-Based Study

Project work is built into the academic structure from Semester II onward.

Students complete:

• Project I in Semester II

• Project II in Semester III

• Project III in Semester IV

• Project IV in Semester V

• Project V in Semester VI

• Project VI in Semester VII

• Professional Project in Semester VIII

The project framework is intended to connect concepts learned in other courses with practical work. Students develop a project under guidance, with activities involving goal setting, planning, research, teamwork, implementation, assessment, report writing, and presentation. Project groups may contain up to three students.

This continuing project sequence gives the program a practical component alongside lectures, tutorials, laboratory study, and examinations.

Internship

Internship appears in Year IV, Semester I and carries three credits. It is identified as practical and field work within the curriculum.

The internship is taken alongside Reinforcement Learning, Cloud Computing, and Project VI. The final semester then moves to electives, IoT for Smart City, and a Professional Project.

Elective Areas

The final-year curriculum includes Elective I and Elective II. Available elective subjects are grouped across several areas, including:

• Computer Vision: Image and Video Processing, Surveillance Video Analytics, People Detection and Bio-metric Recognition

• Mathematics: Introduction to Statistical Learning, Optimization Methods in Machine Learning/Convex Optimization, Kernel Methods, Bayesian Data Analysis

• Computing/IoT: Smart Product Development, Predictive Analysis and IoT, Modeling & Simulation, Pervasive Computing

• Data Science: Fundamentals of Big Data Analytics, Data Analysis and Visualization, Business Intelligence, Social Media Analytics

These electives allow final-year study to extend into selected mathematical, computing, image-processing, and data-oriented topics.

Eligibility for Admission

Eligibility: Applicants must have successfully completed twelve years of schooling in the science stream.

The academic requirement is either:

• Minimum D+ grade in each 10+2 subject with a CGPA of 2.0 or above; or

• At least second division, equivalent to 45% marks, in 10+2, PCL, or an equivalent qualification in the science discipline.

Students with foreign certificates are required to submit an equivalence certificate along with subject grading, CGPA, or total percentage documentation from the concerned authority.

Entrance Examination

Applicants are required to pass the entrance examination conducted by Purbanchal University.

Students awaiting Grade 12 results may appear in the entrance examination, but the required academic documents must be submitted at the time of admission. The regulations also address students awaiting a Grade 12 supplementary examination, subject to submission of the required documents during admission.

Attendance Requirement

Students must maintain at least 80% attendance in lectures, tests, and tutorial classes to qualify to sit for the final examination of a subject.

Where absence occurs for compelling reasons, missed academic work must be completed satisfactorily.

Evaluation System

Assessment takes different forms according to the type of course.

For courses combining theory and laboratory or practical work:

• 20% internal assessment

• 20% practical assessment

• 60% final examination

For theory courses:

• 20% internal assessment

• 80% final examination

For laboratory or practical courses:

• 60% continuous internal evaluation

• 40% final viva evaluated by the university

Continuous assessment can include class or tutorial participation, assignments, laboratory work, class tests, and quizzes.

The grading system uses A+, A, B+, B, C, D, F, and I grades. Students are required to maintain a CGPA of 2.0 or above during the study period.

Academic Areas Covered

Across the eight semesters, students study several connected areas:

• Programming and object-oriented programming

• Digital logic and computer organization

• Mathematics and statistics

• Artificial intelligence and intelligent systems

• Data structures and algorithms

• Database systems

• Operating systems and computer networks

• Data science

• Optimization techniques

• Embedded systems

• Pattern recognition and image processing

• Data warehousing and mining

• Software engineering

• Speech and Natural Language Processing

• Research methods

• Reinforcement Learning

• Cloud Computing

• Project and field-based work

The sequence is structured so that mathematics, programming, and computing systems appear before the more specialized subjects in the later years.

Further Study Options

Purbanchal University's regulations identify several postgraduate study routes after completion of the program, 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 depends on the requirements of the institution and program concerned.

Career Directions

The combination of programming, software engineering, data science, learning systems, projects, and internship can support entry into technical work connected with software, AI projects, and data processing.

Possible directions include:

• Junior AI or machine-learning project roles

• Software and application development

• Data and analytics-related work

• Technical project support

• Further specialization through postgraduate study

Employment outcomes depend on technical ability, project experience, academic performance, additional skills, employer requirements, and available opportunities.

FAQ

How long is B.Tech AI at Kantipur International College?

The Bachelor of Technology in Artificial Intelligence is a four-year program structured across eight semesters.

Which university is the B.Tech AI program affiliated with?

The program at Kantipur International College is affiliated with Purbanchal University and falls under its Faculty of Science and Technology.

How many seats are available for B.Tech AI at KIC?

The stated seat capacity for the program is 48.

What is the eligibility for B.Tech AI?

Applicants must have completed twelve years of schooling in the science stream. They need a minimum D+ in each subject with CGPA 2.0 or above, or second division with at least 45% in 10+2, PCL, or an equivalent science qualification.

Is there an entrance examination for B.Tech AI?

Yes. Applicants must pass the entrance examination conducted by Purbanchal University.

Does B.Tech AI include project work?

Yes. Project work begins in Semester II and continues through the remaining semesters, ending with a Professional Project in Semester VIII.

Does the program include an internship?

Yes. Internship is included in Semester VII and carries three credits.

What is the attendance requirement?

Students need at least 80% attendance in lectures, tests, and tutorial classes to qualify for the final examination of a subject.

What CGPA must students maintain?

Students are required to maintain a CGPA of 2.0 or above throughout the study period.