B.Tech in Artificial Intelligence

B.Tech. in Artificial Intelligence at Global College of Social Science and Technology (GCST)

The Bachelor of Technology in Artificial Intelligence (B.Tech. in AI) at Global College of Social Science and Technology (GCST) is a four-year undergraduate program affiliated with Purbanchal University. GCST, previously known as the College of Development Studies (CDS), is located in Mid-Baneshwor, Kathmandu.

The program combines programming, mathematics, computer systems, data science, and artificial intelligence subjects with laboratory work, semester projects, an internship, electives, and a professional project. Students progress from introductory computing and mathematical courses to subjects such as machine learning, pattern recognition, natural language processing, reinforcement learning, and cloud computing. The curriculum follows an eight-semester structure under the Faculty of Science and Technology of Purbanchal University.

Quick Highlights

Course Overview

The B.Tech. in Artificial Intelligence develops knowledge across computing, mathematics, data analysis, intelligent systems, and software-related subjects. The first year introduces programming, digital logic, calculus, artificial intelligence, communication, professional ethics, probability, statistics, and linear algebra.

Later semesters cover database systems, algorithms, computer networks, AI programming tools, data science, machine learning, embedded systems, pattern recognition, data mining, computer vision, deep learning, natural language processing, reinforcement learning, and cloud computing.

The program also includes continuing project work. Project I begins in the second semester, followed by projects in subsequent semesters, an internship in the seventh semester, and a professional project in the final semester.

Who Is This Course For?

The program may suit students who are interested in:

• Programming and software-related problem-solving

• Mathematics, probability, statistics, and analytical methods

• Artificial intelligence and intelligent systems

• Data science and data analysis

• Computer systems, networks, and embedded systems

• Laboratory activities and semester-based project work

• Research, technical reporting, and presentations

Students should be prepared for a curriculum that combines theoretical study with programming, laboratories, assignments, group projects, fieldwork, and continuous assessment.

Eligibility for Admission

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

They must meet one of the following academic requirements:

• A minimum D+ grade in each subject of 10+2 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.

Students who have passed Grade 11 and are waiting for the Grade 12 supplementary examination may apply. They must submit all required academic documents at the time of admission.

Students who have appeared in the final examination and are waiting for their results and certificates may also apply for the entrance examination. Their required documents must be submitted during admission.

Applicants holding foreign academic certificates must submit an equivalence certificate and documentation showing subject-wise grades with CGPA or the total percentage issued by the concerned authority.

Entrance Examination

Applicants must pass the entrance examination conducted by Purbanchal University. Admission eligibility depends on meeting the academic requirements and passing the university entrance examination.

Duration and Academic Structure

Duration: Four academic years

Semesters: Eight

Medium: English

English is used for instruction and examinations in all subjects. The curriculum is arranged semester-wise, with each semester containing theory, tutorial, laboratory, project, internship, or fieldwork components according to the nature of the courses.

B.Tech. in AI Curriculum

First Year

Semester I

The first semester carries 18 credits and introduces the foundations of programming, computing, mathematics, communication, and professional responsibility.

Subjects include:

• Introduction to Programming

• Digital Logic

• Calculus

• Introduction to Artificial Intelligence

• Technical Report Writing and Presentation

• Society and Professional Ethics

Semester II

The second semester carries 17 credits and begins the program’s continuing project component.

Subjects include:

• Object Oriented Programming

• Artificial Intelligence and Intelligent Systems

• Microprocessor and Assembly Language

• Probability and Statistics

• Linear Algebra

• Project I

The first-year curriculum establishes a base in programming, digital systems, mathematics, artificial intelligence concepts, technical communication, and project work.

Second Year

Semester III

The third semester carries 17 credits.

Subjects include:

• Database Management System

• Data Structure and Algorithm

• Computer Organization

• Operating System

• Differential Equations

• Project II

Semester IV

The fourth semester also carries 17 credits.

Subjects include:

• Numerical Methods

• Computer Networks

• Design and Analysis of Algorithms

• Programming for AI (Tools, Techniques and Libraries)

• Introduction to Data Science

• Project III

During the second year, students study databases, computing architecture, operating systems, networks, numerical methods, algorithm design, data science, and programming tools used in artificial intelligence coursework.

Third Year

Semester V

The fifth semester carries 17 credits.

Subjects include:

• Machine Learning

• Optimization Techniques

• Embedded Systems

• Pattern Recognition and Image Processing

• Data Warehousing and Mining

• Project IV

Semester VI

The sixth semester carries 17 credits.

Subjects include:

• Object Oriented Software Engineering

• Computer Vision

• Deep Learning

• Speech and Natural Language Processing

• Research Methods

• Project V

The third year concentrates on major artificial intelligence study areas while continuing semester-based project work. Research Methods also prepares students for structured academic and technical inquiry.

Fourth Year

Semester VII

The seventh semester carries 11 credits.

Subjects include:

• Internship

• Reinforcement Learning

• Cloud Computing

• Project VI

The internship is assigned three credits and includes practical and fieldwork components.

Semester VIII

The eighth semester carries 12 credits.

Subjects include:

• IoT for Smart City

• Elective I

• Elective II

• Professional Project

The final semester allows students to select two elective subjects and complete a professional project.

Elective Subjects

The curriculum groups elective options into four areas.

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 and Simulation

• Pervasive Computing

Data Science

• Fundamentals of Big Data Analytics

• Data Analysis and Visualization

• Business Intelligence

• Social Media Analytics

Students take Elective I and Elective II during the eighth semester.

Project-Based Learning

Project work begins in the second semester and continues through the remaining semesters. Students are expected to apply concepts and principles from their coursework while completing practical assignments.

The project structure is intended to develop abilities related to:

• Goal setting

• Planning

• Research

• Teamwork

• Practical application

• Assessment

• Report writing

• Presentation

Students may work in groups of up to three under the guidance of a group adviser. Each group selects a project and defines its aims and objectives. The curriculum progresses from Project I to Project VI before the Professional Project in the eighth semester.

Internship

The internship appears in the seventh semester and carries three credits. It consists of practical and fieldwork activities. It is studied alongside Reinforcement Learning, Cloud Computing, and Project VI.

Teaching and Learning at GCST

GCST follows a participatory and practical teaching approach. Learning activities include classroom discussions, case-based assignments, collaborative work, workshops, seminars, and student presentations.

The college has classrooms equipped with projectors and whiteboards, a library containing books, journals, research materials, and digital resources, and a computer laboratory with internet access and software for academic work. Mentoring support is available for assignments, research, and project planning.

These institutional resources complement the B.Tech. in AI curriculum, which requires regular programming, laboratory work, reporting, research, presentations, and semester projects.

Attendance Requirement

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 illness or another compelling reason, missed academic work must be completed satisfactorily. Responsibility for completing missed work rests with the student, with support from the concerned teachers.

Assessment System

The program uses continuous assessment throughout each semester. Assessment may cover:

• Class and tutorial participation

• Assignments

• Laboratory work

• Class tests

• Quizzes

• Practical examinations

• End-semester examinations

Students are informed at the beginning of each course about the assessment methods and the weight assigned to different activities.

Theory and Practical Assessment

For combined theory and laboratory or practical courses:

• Internal assessment: 20%

• Practical assessment: 20%

• Final examination: 60%

For theory-only courses:

• Internal assessment: 20%

• Final examination: 80%

For laboratory or practical courses:

• Continuous internal evaluation: 60%

• University-evaluated final viva: 40%

End-semester examinations are set and evaluated by examiners.

Grading System

A student receiving an Incomplete grade for unmet coursework requirements may complete the requirement within six weeks from the end of the semester. When the requirement is not completed within that period, the grade is converted to Fail.

Students must maintain a cumulative grade point average of at least 2.0 throughout the study period. A student who does not maintain the required CGPA may be required to withdraw from the program.

Skills Students May Develop

Through coursework, laboratories, projects, presentations, and the internship, students may develop abilities in:

• Programming and object-oriented software development

• Database and computer system fundamentals

• Data structures and algorithm design

• Probability, statistics, calculus, and linear algebra

• Data analysis and data science

• Artificial intelligence and intelligent systems

• Machine learning and pattern recognition

• Image, speech, and natural language processing

• Research methods and technical reporting

• Project planning, teamwork, and presentations

The level of skill developed will depend on academic participation, practical work, project quality, individual study, and performance across the program.

Further Study Options

After completing the B.Tech. in Artificial Intelligence, graduates may pursue programs such as:

• Master of Technology in Artificial Intelligence

• Master of Science in Artificial Intelligence

• Master of Computer Applications

• Master of Information Technology

• Master of Science in Computer Science

• Master of Science in Computer Information Systems

• Master of Business Administration

Admission to any graduate program remains subject to the eligibility and selection requirements of the concerned university or institution.

Seats and Scholarship Support

The B.Tech. in AI program at GCST has 48 seats.

GCST offers some scholarship support based on merit and financial need. Support may include scholarships for academically performing students and assistance for students from remote or marginalized backgrounds or those experiencing financial hardship.

Course Planning Considerations

Prospective students should consider the program’s science-stream eligibility, Purbanchal University entrance requirement, four-year duration, English-medium instruction, and minimum attendance requirement.

The course includes mathematics, programming, laboratory activities, continuous assessment, semester projects, an internship, electives, and a professional project. Students considering the program should assess their interest in these areas and their readiness for sustained theoretical and practical study.

Frequently Asked Questions

What is the full name of B.Tech. in AI?

The full course name is Bachelor of Technology in Artificial Intelligence.

Which university is the program affiliated with?

The B.Tech. in AI at GCST is affiliated with Purbanchal University.

How long is the B.Tech. in AI program?

The program runs for four academic years across eight semesters.

Where is GCST located?

Global College of Social Science and Technology is located in Mid-Baneshwor, Kathmandu, Nepal.

How many seats are available?

The B.Tech. in AI program has 48 seats.

Is an entrance examination required?

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

What is the minimum attendance requirement?

Students must maintain at least 80% attendance in lectures, tests, and tutorial classes to qualify for final examinations.

Does the course include project work?

Yes. Project work begins in the second semester and continues across later semesters. The curriculum also includes an internship and a final professional project.

What is the medium of instruction?

English is the medium of instruction and examination for all subjects in the program.

What CGPA must students maintain?

Students must maintain a CGPA of at least 2.0 throughout the study period.