Master AI for Healthcare:
Build a strong foundation in AI, machine learning, and deep learning tailored to healthcare - even without coding experience. Explore real-world applications in diagnosis, monitoring, and treatment planning.
Application Closure Date : 31st July, 2025
Course Duration :
6 months
Course Fees :
₹ 1,20,000 + 18% GST
Schedule :
Saturdays, 6:00 PM – 7:30 PM
Sundays, 11:00 AM – 12:30 PM
Course Eligibility :
Any graduate professional working in industry and academia with area relevant to AI in healthcare
Campus Immersion :
A two-day in-person session at IIT Delhi toward the end of the programme
Build a strong foundation in AI, machine learning, and deep learning tailored to healthcare - even without coding experience. Explore real-world applications in diagnosis, monitoring, and treatment planning.
Work with diverse datasets like Electronic Medical Records (EMR), Electronic Health Records (EHR), medical imaging (PACS), genomics, and IoT-based sensor data. Learn to manage sensitive data using MIMIC-III.
Create supervised/unsupervised models, apply CNNs for imaging, and use NLP on clinical notes. Evaluate models with healthcare-specific metrics like ROC curves, precision, and recall.
Learn end-to-end deployment using cloud platforms and HIS integration. Work with standards like FHIR, HL7, and DICOM to ensure interoperability.
Apply your skills in a mentored capstone project with IIT Delhi and AIIMS faculty. Tackle real healthcare challenges and build clinically relevant AI solutions.
e-Certificate of successful completion from CEP, IIT Delhi: Earn a prestigious
e-Certificate from IIT Delhi upon completing the programme.
Core Principles of AI and Machine Learning
Develop a solid understanding of AI, machine learning, and deep learning concepts and how they
specifically apply to healthcare challenges.
Handling and Processing Healthcare Data
Learn techniques for working with diverse clinical data sources such as electronic medical records,
medical imaging, genomics, and sensor data, while adhering to healthcare data standards like FHIR,
HL7, and DICOM.
Designing Predictive Models for Healthcare
Acquire skills to create and assess machine learning models that support disease diagnosis, patient
risk assessment, and outcome prediction.
Utilizing Deep Learning and Language Processing
Gain experience in applying neural networks to interpret medical images and extract meaningful
information from clinical text using natural language processing.
Implementing AI Solutions in Clinical Environments
Understand the process of deploying AI applications through interactive dashboards and cloud
infrastructure, and integrating these into existing hospital information systems.
Analyzing Population Health Trends:
Explore AI-driven methods for forecasting epidemics, analyzing health data over time, and mapping
disease spread to inform public health strategies using advanced artificial intelligence in health
care techniques.
Foundations of AI (ML & DL) for Healthcare
|
Healthcare Data & Clinical Big Data Analysis
|
AI Models & Predictive Analytics
|
AI Applications & Healthcare Automation
|
AI Deployment & Integration
|
Public Health & Population Analytics
|
Capstone Project
|
Industry Expert Roundtable
|
Prerequisites for the Program:
1. Basics of Mathematics : including Linear Algebra, Calculus, Probability, and Statistics
(school-level understanding is sufficient).
2. Basic Programming Knowledge :preferably in MATLAB or Python.
Pre-programme Support:
✪ Webinars will be organized by the faculty 2 months before the program to help students revise or learn these concepts to help students revise or learn these concepts along with pre-program preparatory content.
✪ These webinars are optional but highly recommended, particularly for students from non-technical backgrounds.
Evaluation & Practical Learning Components
Internal Assessments: Periodic quizzes, short clinical AI tasks, mini viva sessions, and
capstone project reviews designed to reinforce your understanding throughout the program.
Final Examination: A comprehensive term-end evaluation including an MCQ exam, oral viva, and
coding test (Python/MATLAB) to assess both theoretical knowledge and practical skills.
10+ Case Studies and
Projects:
Gain practical experience through carefully
Gain practical experience through carefully designed case studies and a hands-on project focused on
real healthcare challenges. Work with clinical data like EMR data, physiological data, medical images,
and genomics while applying AI/ML techniques using tools like Python and MATLAB. These exercises are
crafted to help you translate theoretical knowledge into impactful healthcare solutions.
| Tool to Be Used | Purpose | Rationale |
|---|---|---|
| Python (Pandas, NumPy)/ MATLAB | Data Analysis & Cleaning | Industry-standard for manipulating clinical data, easy to scale and script |
| Python (Matplotlib, Seaborn), MATLAB GUI, Streamlit (Python) | Visualization & Dashboards | Interactive dashboards & GUI building with Python/ MATLAB as front-end tools |
| Python (scikit-learn), MATLAB | Machine Learning Models | Covers supervised and unsupervised learning via both code and visual modeling |
| Python (TensorFlow/Keras), MATLAB (CNN toolbox) | Deep Learning / Imaging | Real-world applications in radiology, pathology, etc. |
| Python, MATLAB | Data Preprocessing | Used for handling missing values, transformations, feature engineering |
| Python (spaCy, NLTK) | NLP & EHR Mining | For Named Entity Recognition, text mining of clinical notes |
| Streamlit (Python), MATLAB App Designer | Deployment (Simplified) | Build healthcare apps/interfaces for simulation or controlled use |
| GCP, AWS (Introductory Only) | Cloud Awareness (Conceptual) | Tool exposure without actual development — Python/MATLAB to be used offline |
| Python (FHIR client libs), MATLAB for DICOM | Standards Handling | Maintain compliance with health data exchange protocols |
| Apache Spark (PySpark) | Distributed Data Processing & Scalable Analytics | Enables fast, large-scale processing of healthcare data—ideal for handling high-volume datasets like EHR logs or sensor streams, with seamless integration into the Python ecosystem. |
| Particulars | Amount (₹) |
| Programme Fees | ₹ 1,20,000 |
| GST @ 18% | ₹ 21,600 |
| Total Fees | ₹ 1,41,600 |
All fees should be submitted in the IITD CEP account only, and the details will be shared post-selection.
The receipt will be issued by the IIT Delhi CEP Account for your records, which can be downloaded from the CEP Portal.
Easy EMI options available.
Loan and EMI Options are services offered by Teamlease Edtech. IIT Delhi is not responsible for the same.
GST @ 18% will be charged extra in addition to the fee.
| Installment | Installment Date | Amount (₹) |
| I | Due within 3 Days of offer letter. | ₹ 60,000+GST |
| II | 31st October, 2025. | ₹ 60,000+GST |
| Total fees – ₹ 1,20,000+GST [No cost EMI available] | ||
GST @ 18% will be charged extra in addition to the fee.
Candidates can withdraw within 15 days from the programme start date. A total of 80% of the total fee received will be refunded. However, the applicable tax amount paid will not be refunded on the paid amount.
Candidates withdrawing after 15 days from the start of the programme session will not be eligible for any refund.
Easy EMI options available. Loan and EMI Options are services offered by Teamlease Edtech. IIT Delhi is not responsible for the same.
If you wish to withdraw from the programme, you must email cepaccounts@admin.iitd.ac.in and cepdelhi@digivarsity.com, stating your intent to withdraw. The refund, if applicable, will be processed within 30 working days from the date of receiving the withdrawal request.
Dr. Anup
Singh
Professor
CENTRE FOR BIOMEDICAL ENGINEERING, INDIAN INSTITUTE OF TECHNOLOGY DELHI.
Prof.
Anup Singh is a leading researcher and educator in biomedical imaging, currently serving as faculty at
the Centre for Biomedical Engineering, IIT Delhi, and the Department of Biomedical Engineering, AIIMS
New Delhi. He is also an associate faculty at Yardi School of AI at IIT Delhi. With a PhD from the
Department of Mathematics and Statistics at IIT Kanpur and postdoctoral experience from the Department
of Radiology at the University of Pennsylvania, Dr. Singh brings over a decade of expertise in
advanced MRI techniques, quantitative imaging, machine learning & deep learning for medical imaging,
along with an experience in the development of MRI- compatible devices. He has authored 80+
peer-reviewed papers (including in Nature Medicine), holds 5 US/ Indian patents, and is actively
involved in translational biomedical imaging research.
Prof. Amit
Mehndiratta
Professor
CENTRE FOR BIOMEDICAL ENGINEERING, INDIAN INSTITUTE
OF TECHNOLOGY DELHI.
A physician-engineer, Dr. Amit Mehndiratta holds an MBBS
from Dr. MGR Medical University, a Master's from IIT Kharagpur, and a D.Phil. from the University of
Oxford. He currently serves as joint faculty at IIT Delhi and AIIMS New Delhi, focusing on
neuro-assistive technologies and biomedical imaging. His past affiliations include Harvard Medical
School, Massachusetts General Hospital, and the German Cancer Research Center. He has received
multiple awards, including the SERB Technology Translation Award and the Ericsson Innovation Award.
Dr. Mehndiratta leads CARE-DAT, a CoE in Assistive Technology supported by ICMR.
The two-day campus immersion offers a valuable chance to engage face-to-face with IIT Delhi faculty and peers. However, travel, accommodation, and related costs are not included in the programme fee and must be borne by the participants.
Yes. You will connect with a diverse cohort of healthcare, technology, and data science professionals through live sessions, collaborative projects, and the two-day campus immersion - building strong professional relationships in the evolving AI in healthcare space.
Participants who meet the evaluation requirements will be awarded an e-Certificate of Successful Completion from CEP, IIT Delhi. Those who fulfill the minimum attendance but not the evaluation criteria will receive a Certificate of Participation. This certification validates your skills in AI for healthcare and enhances your profile in the growing healthcare AI sector.