BS Artificial Intelligence

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Faculty of Computing
BS Artificial Intelligence

Degree Overview

Artificial Intelligence is no longer a technology of the future; it is the defining technology of today. From algorithms that analyse medical scans to detect tumors, to systems that predict patient deterioration in intensive care units, to natural language processing tools that power clinical decision support, AI is actively reshaping every dimension of human health and wellbeing.

The Bachelor of Science in Artificial Intelligence (BSAI) at Lahore University of Biological and Applied Sciences (UBAS) is designed to produce graduates who do not merely understand AI, they build it, apply it responsibly, and lead it. This four-year, eight-semester undergraduate program provides a comprehensive and rigorous education in the mathematical foundations, computational principles, and practical implementation of artificial intelligence across its full spectrum: machine learning, deep learning, computer vision, natural language processing, knowledge representation, and intelligent systems design.

At UBAS, the BSAI program carries a distinctive identity shaped by the university’s core mission in biological and applied sciences. Our students learn AI in an environment surrounded by faculties of pharmacy, health sciences, and rehabilitation. This means AI is not studied in isolation, it is studied in context. Students build diagnostic AI models on clinical datasets, develop NLP systems for Urdu-language health communication, design computer vision tools for pathology and radiology, and explore the ethical dimensions of deploying AI in life-critical settings.

This interdisciplinary immersion makes UBAS BSAI graduates uniquely valuable to the rapidly expanding health-tech, MedTech, and digital health sectors, both in Pakistan and internationally. The program is aligned with HEC Pakistan’s approved Computing Curriculum and incorporates global best practices from leading AI programs worldwide.

Program Educational Objectives (PEOS)

The BSAI program is designed so that graduates, within three to five years of graduation, will:

PEO-1	Professional AI Expertise Work as competent AI and machine learning professionals capable of designing, building, evaluating, and deploying intelligent systems, with particular readiness for roles in health-tech, clinical decision support, MedTech, and data-driven industries.
PEO-2	AI for Healthcare Impact Apply AI methodologies to solve high-impact problems in healthcare, public health, drug discovery, clinical diagnostics, and patient management by translating cutting-edge AI research into practical, beneficial systems.
PEO-3	Responsible AI Practice Design AI systems with a deep understanding of ethical obligations, algorithmic bias, data privacy, and the regulatory requirements specific to AI in healthcare and other safety-critical domains.
PEO-4	Research and Innovation Contribute to the advancement of AI through research, experimentation, and innovation in academia, research institutions, or industry R&D environments.
PEO-5	Multidisciplinary Leadership Lead or contribute meaningfully to multidisciplinary teams combining computing, clinical, scientific, and business expertise to deliver AI-powered solutions at scale.

Program Learning Outcomes (PLOS)

Upon successful completion of the BSAI degree, graduates will demonstrate the ability to:

PLO	Graduate Outcome
PLO-1	AI Knowledge Apply knowledge of AI, machine learning, deep learning, and mathematical foundations to the design and analysis of intelligent systems
PLO-2	Problem Analysis Formulate complex real-world problems, particularly in healthcare, as AI problems and solve them using appropriate methodologies
PLO-3	Intelligent System Design Design, train, evaluate, and deploy AI models and intelligent systems that meet performance and safety requirements
PLO-4	Data Competence Collect, process, analyse, and interpret complex datasets, including clinical, biomedical, text, and image data
PLO-5	AI Tools Select and apply contemporary AI frameworks, libraries, cloud platforms, and development tools effectively
PLO-6	AI Ethics Critically assess the ethical, societal, and health implications of AI systems, including bias, fairness, transparency, and patient safety
PLO-7	Communication Communicate AI model outputs and technical findings to both technical and non-technical audiences including clinicians
PLO-8	Teamwork Function effectively in interdisciplinary AI project teams including health professionals and domain experts
PLO-9	Research Orientation Engage with AI research literature critically and contribute to original research or development projects
PLO-10	Lifelong Learning Commit to continuous learning and professional adaptation in the rapidly evolving AI landscape

Why Study BSAI At UBAS?

AI with a Healthcare Soul: Learn AI in an environment where problems are real and stakes are high, diagnosing diseases earlier, personalising treatment, managing health systems smarter
Unique Campus Ecosystem: Pakistan’s only AI program embedded within a biological and applied sciences university, natural research collaborators across pharmacy, nutrition, rehabilitation, and health sciences
Full AI Curriculum: Deep coverage of machine learning, deep learning, computer vision, NLP, neural networks, knowledge representation, and intelligent systems, not just introductory AI
Pre-Medical Friendly: Students from biology and medical sciences background have a clear pathway into AI, bridging body-knowledge with the technology transforming healthcare globally
Career-Ready: Graduating into one of the world’s most in-demand career paths, with a distinctive interdisciplinary profile purely technical graduates cannot match

Healthcare Applications — What Our Students Build

At UBAS, AI is not a generic subject. Our students explore its application in contexts that matter:

Medical Image Analysis: Training CNNs to detect tumors in MRI, CT, and X-ray scans; segmenting anatomical structures; classifying pathological tissue in histology images
Clinical Decision Support: Building ML models that predict patient risk, flag deteriorating vitals, or recommend treatment pathways based on electronic health record data
Drug Discovery & Genomics: Applying deep learning to accelerate molecular screening and identify genetic risk factors for disease
Health NLP: Developing NLP systems that extract clinical information from discharge summaries, annotate Urdu-language health records, or power chatbots for patient triage
Remote Patient Monitoring: Building AI agents that analyse SMS or wearable sensor data and alert clinicians to emerging health risks
Epidemiological Modelling: Using AI to predict disease outbreaks, model vaccination impact, and support public health decision-making

Career Opportunities

Healthcare & Life Sciences AI Medical AI Engineer Clinical Informatics Specialist Health Data Scientist Bioinformatics Analyst Pharma AI Developer Digital Health Consultant	Core AI & Machine Learning Machine Learning Engineer Deep Learning Engineer AI Research Engineer Computer Vision Engineer NLP Engineer AI Product Manager	Data & Analytics Data Scientist Business Intelligence Developer Big Data Engineer AI Analyst Predictive Analytics Specialist
Emerging AI Roles Generative AI Engineer LLM Application Developer AI Ethics Consultant Robotics Engineer Autonomous Systems Developer	Research & Academia AI Researcher MS/PhD in AI or Biomedical Informatics Research Associate University Lecturer	Entrepreneurship Health-Tech AI Startup Founder AI Consultant AI Product Strategist

Criteria For Award Of Degree

Each candidate must successfully complete required degree credit hours with a minimum CGPA of 2.0 on a 4.0 scale. This is a four-year (eight-semester) program. Minimum duration: four years.

Admissions Open Fall 2026

Learn about UBAS admission requirements and eligibility for our programs.

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