SCHOOL OF PROFESSIONAL ADVANCEMENT

AI for HealthCare

Introduction

                                     

Artificial Intelligence is transforming healthcare by enabling intelligent diagnosis, disease prediction, medical image analysis, personalized treatment, clinical decision support, and healthcare automation. This certificate course introduces participants to the foundations of AI and its practical applications in healthcare using modern machine learning and deep learning techniques. Participants will gain hands-on experience with healthcare datasets, medical imaging, electronic health records (EHRs), generative AI, large language models (LLMs), and AI-assisted clinical decision-making while understanding ethical, legal, and regulatory considerations.

 

Unique Selling Propositions                     

 

  • Industry-relevant AI applications in healthcare.
  • Hands-on training using real healthcare datasets.
  • Medical image analysis using deep learning.
  • Introduction to Generative AI and Large Language Models for healthcare.
  • AI-assisted diagnosis and clinical decision support.
  • Exposure to healthcare data analytics.
  • Practical implementation using Python, TensorFlow, and PyTorch.
  • Capstone healthcare AI project.
  • Certificate from UMT.
  • Delivered by an AI researcher with experience in healthcare AI.

 

 

Objectives and Learning Outcomes

                                     
  • Understand AI concepts relevant to healthcare.
  • Apply machine learning algorithms to healthcare data.
  • Develop deep learning models for medical image classification.
  • Analyze Electronic Health Records (EHRs) using AI techniques.
  • Utilize Generative AI and Large Language Models in healthcare applications.
  • Understand AI ethics, privacy, fairness, and regulatory requirements.
  • Build predictive healthcare models.
  • Develop AI-powered clinical decision support systems.
  • Evaluate AI model performance using appropriate healthcare metrics.
  • Design and implement an end-to-end AI healthcare project.

 

 

Key Topics / Related Concepts

             
  • Introduction to Artificial Intelligence
  • AI in Modern Healthcare
  • Python for AI
  • Data Preprocessing for Healthcare
  • Medical Data Analytics
  • Machine Learning Fundamentals
  • Supervised and Unsupervised Learning
  • Deep Learning Fundamentals
  • Convolutional Neural Networks (CNNs)
  • Medical Image Analysis
  • Disease Detection using AI
  • Electronic Health Records (EHR) Analytics
  • Natural Language Processing in Healthcare
  • Generative AI for Healthcare
  • Large Language Models (LLMs) in Medicine
  • AI-assisted Clinical Decision Support Systems
  • Explainable AI (XAI)
  • AI Ethics and Responsible AI
  • Healthcare Data Privacy and Security
  • Model Evaluation and Validation
  • Healthcare Case Studies
  • Capstone Project

 

 

 

Activities and Learning Strategies

             
  • Interactive lectures.
  • Hands-on laboratory sessions.
  • AI programming exercises using Python.
  • Medical image analysis practicals.
  • Healthcare case studies.
  • Dataset analysis.
  • Group discussions.
  • Weekly assignments.
  • Mini-projects.
  • Final capstone healthcare AI project.

 

 

 

Venue / Facilities 

             

 

 

 

UMT Main Campus; List down required facilities

 

Required Facilities

  • Computer Laboratory
  • High-Speed Internet
  • Multimedia Projector
  • Python (Anaconda Distribution)
  • Jupyter Notebook
  • Google Colab
  • TensorFlow
  • PyTorch
  • Scikit-learn
  • OpenCV
  • VS Code
  • GPU-enabled systems (preferred)

 
  • Learning Duration: 14 weeks
  • Certificate Fee: Rs 40000
  • Session:
Register

Instructor

Dr. Muhammad Asad Arshed is an Assistant Professor at the School of Systems and Technology (SST), University of Management and Technology (UMT), Lahore. He holds a PhD in Computer Science and has extensive academic, research, and industrial experience in Web Development, Artificial Intelligence (AI), Machine Learning (ML), Deep Learning (DL), Natural Language Processing (NLP), Data Science, and Backend Development using the Python Django Framework.

Prior to joining UMT, he served as a Research Officer at the KICS, University of Engineering and Technology (UET), Lahore, where he contributed to research and development projects on emerging technologies.

Dr. Arshed is an experienced trainer who has successfully conducted numerous professional development and technical training programs under the National Vocational and Technical Training Commission (NAVTTC) and at UMT. He has also delivered specialized training on Artificial Intelligence for the Punjab Police, receiving highly positive feedback and appreciation from the department for its quality, effectiveness, and practical relevance. In addition, he has organized and delivered faculty development workshops for UMT faculty members on Artificial Intelligence, Generative AI, and modern digital technologies.

His students have actively participated in prestigious national and international technology competitions, including the Microsoft Imagine Cup, demonstrating innovation and practical problem-solving skills developed under his mentorship. He has also supervised numerous industry-oriented software development and research projects.

Dr. Arshed has authored multiple research publications in internationally recognized journals and conferences. His teaching philosophy emphasizes hands-on learning, project-based education, and industry best practices, enabling participants to acquire practical AI skills directly applicable to academia and industry.

 

 

Categories