AI & Machine Learning for Modern Healthcare (Flagship Certificate Program)

18 May-21 June 2026 | 7:00 PM IST | Online | Certificate

India – 7:00 PM IST | Saudi Arabia – 4:30 PM | Dubai – 5:30 PM | Singapore – 10:30 PM | Australia – 11:30 PM | New York – 9:30 AM

About the Program

This industry-aligned certificate program covers the complete journey from programming fundamentals to advanced machine learning, deep learning, and healthcare AI applications. Participants will work with real-world datasets, build models, and gain practical experience through projects, making them job-ready for AI roles in healthcare and research domains.

What You Will Learn

• Programming fundamentals using Python

• Data analysis with NumPy and Pandas

• Data visualization using Matplotlib and Seaborn

• Machine learning concepts (supervised & unsupervised learning)

• Deep learning techniques (CNN, RNN, GANs)

• Model evaluation and performance metrics

• Healthcare data processing and feature engineering

• AI applications in medical diagnosis and imaging

• Real-world healthcare AI project development

Course Features

• Live coding sessions and hands-on labs

• Real-world healthcare datasets and projects

• Lifetime access to recordings and PPTs

• Mini project and final presentation

• Career guidance and industry insights

• e-Certificate (ISO–IAF Accredited)
  

Learning Outcomes

• Develop machine learning and deep learning models

• Analyze and visualize complex datasets

• Apply AI techniques to healthcare problems

• Work with medical datasets (EHR, imaging data)

• Build and present real-world AI projects

• Prepare for careers in AI, data science, and healthcare analytics
  

Who Can Join

• Final year UG & PG students (CS, IT, AI, Data Science, Bioinformatics)

• Research scholars in AI and healthcare

• Working professionals in IT and healthcare sectors

• Faculty members and PhD aspirants

Course Fee

• Indian Participants: Rs 8000

• International Participants: $225 USD

Course Module

Module 1: Programming & Data Foundations (Week 1)

• Introduction to Algorithms & problem-solving

• Basics of complexity theory and algorithm design

• Programming fundamentals (C/Python/Java overview)

• Data structures: lists, stacks, queues, dictionaries

• Python programming fundamentals

• Data manipulation (NumPy)

• Data analysis (Pandas)

• Data visualization (Matplotlib & Seaborn)

• Statistical computing basics

Module 2: Machine Learning & Deep Learning (Week 2)

• Introduction to Machine Learning & workflows

• Supervised learning (regression, classification)

• Model evaluation and validation

• Feature engineering and selection

• Unsupervised learning (clustering, PCA)

• Ensemble learning (bagging, boosting, random forest)

• Deep learning fundamentals

• CNN, RNN, LSTM, GANs

• Transfer learning and fine-tuning

• Hands-on ML/DL implementation

Module 3: AI & Machine Learning in Healthcare (Week 3)

• Foundations of AI in healthcare

• Healthcare data types (EHR, imaging data)

• Data preprocessing and feature engineering

• Ethics, data privacy, and regulations

• Disease prediction models

• Evaluation metrics in healthcare ML

• Case studies in medical diagnosis

• Healthcare ML project walkthrough

Module 4: Practicals & Project Work (Week 4)

• Medical image analysis using CNN

• X-ray and MRI classification

• Image segmentation and object detection

• Transfer learning in medical imaging

• GAN applications in healthcare

• Mini project presentation

• Real-world healthcare AI applications

• Certification and career guidance