BTech in Artificial Intelligence (BTech in AI)

The B. Tech in AI at Global College of Social Science and Technology (GCST), affiliated with Purbanchal University, is one of Nepal’s most sought-after IT programs. Spanning over four years across eight semesters, the course combines theoretical depth with strong practical engagement, preparing students for impactful careers in AI, machine learning, and emerging technologies.

This program is more than a degree-it’s a transformative journey that builds leadership, innovation, and real-world problem-solving skills. Designed to help students thrive in the global digital economy, B. Tech in AI at GCST shapes tech-savvy, socially responsible professionals ready to lead change.

Vision 

GCST’s B. Tech in AI program is envisioned to be a national and global model for excellence in AI education, producing ethical and visionary leaders for a tech-driven world.

Mission 

• Provide practical and ethical education in AI.
• Promote critical thinking, innovation, and interdisciplinary learning
• Bridge academia with the industry and research sectors
• Cultivate responsible leadership for equitable tech advancement

Objectives

•  Deliver solid theoretical and hands-on knowledge in AI
• Offer real-world learning via projects and industry links
• Enhance decision-making and problem-solving skills
• Encourage ethical and innovative AI development
• Support entrepreneurship and global collaboration
• Promote research in AI, robotics, and automation
• Prepare graduates for success in diverse global roles

Special Benchmarks of B.Tech in AI at GCST

• Industry-responsive and globally recognised benchmarked curriculum
• Cutting-edge technology-enabled teaching and AI simulation tools
• Strong focus on experiential learning through capstone projects and industry internships
• A dynamic faculty team with academic depth and industry insights
• Exposure to tech firms through institutional partnerships for research, mentoring, and placement

Key Area of Focus

• Machine Learning
• Natural Language Processing
• Robotics & Intelligent Systems
• Business Intelligence and Automation
• Ethical AI & Responsible Innovation
• Big Data & Cloud-based AI Applications
• Deep Learning & Neural Networks