Doctors and healthcare · courses checked October 2026

Best AI Courses for Doctors and Healthcare Professionals in India (2026-27)

The quick answerFor a practising doctor who does not code, Stanford’s AI in Healthcare specialisation on Coursera is the best-value start, and some of its courses carry CME credit from Stanford Medicine. For an Indian institute certificate, IIT Delhi’s Executive Programme for AI in Healthcare is the main option, though it ends with a coding test. Johns Hopkins and Harvard Medical School offer shorter, pricier programmes aimed at clinical and hospital leaders. If you run a hospital, clinic network or pharma team and want staff trained together on everyday AI, ask Skillopedia about team training.
7 courses comparedIndia and globalCoding needs flaggedPatient-data note
Illustration of an analyst at a desk working on a monitor of bar and donut charts

The shortlist

Seven AI courses for doctors, at a glance

AI is reaching Indian medicine through radiology and pathology software, clinical documentation, triage tools and, increasingly, general assistants that doctors use for summaries and patient leaflets. Doctors need enough understanding to judge these tools: what data trained them, how they were evaluated and where they fail. We checked every course below on its own official page in October 2026, and we flag which ones require programming.

Not medical or legal advice. This page compares training courses. It does not recommend any AI tool for diagnosis or treatment, and nothing here is clinical, regulatory or legal advice. Clinical use of AI must follow your institution’s policies, your medical council’s rules and applicable law. The order of the list reflects usefulness to a typical Indian clinician, not a score; Skillopedia, which publishes this list on its own site, is not one of the seven.

Comparison table

Format, time, fee and coding needs side by side

CourseFormatTime neededFee as listedCoding needed?
Stanford: AI in HealthcareSelf-paced, 5 coursesAbout 60 hours in totalNot shown; financial aid availableNo
IIT Delhi CEP: AI in HealthcareLive weekend online plus 2-day campus6 months₹1,50,000Yes: final Python or MATLAB test
Johns Hopkins: AI and Agentic AI in HealthcareOnline with live sessions10 weeks at 6 to 8 hrs/week₹1,80,000 + GSTNo
Harvard Medical School: AI in Health CareOnline with live faculty sessions8 weeks at 4 to 6 hrs/weekUS$3,150No
University of Delhi: AI in Health SciencesLive online, weekends15 weeksNot shown on the current pageSome lab work
MIT xPRO: AI in HealthcareOnline10 weeksUS$2,700Not stated
DeepLearning.AI: AI for MedicineSelf-pacedSeveral weeks per courseNot shown; financial aid availableYes: intermediate Python

Fees as shown on each official or delivery-partner page in October 2026. Coursera prices in local currency at checkout.

The seven courses

What each course teaches clinicians, and what it costs

The courses fall into three groups. Literacy courses teach doctors to evaluate and work alongside AI. Leadership programmes teach how to bring AI into a hospital or service. Technical courses teach you to build models. Most clinicians need the first; heads of department and medical directors may want the second.

Best value · CME on some courses

1. Stanford Online: AI in Healthcare Specialization

Stanford Online, on Coursera

A five-course series from Stanford that starts with how healthcare and clinical data work, moves through machine learning concepts, and spends a full course on how to evaluate AI applications. It does not require coding, and Stanford University School of Medicine is accredited to provide continuing medical education, with CME details given on individual course pages.

What you learn: the sources and biases of clinical data; fundamentals of machine learning for healthcare; how to evaluate an AI application before trusting it; and deployment and ethics, with a capstone.

Who it is for: doctors, nurses and allied health professionals, and also technologists who want to understand clinical settings.

Pros
  • Low cost with financial aid
  • Evaluation of AI tools is a full course
  • CME accreditation from Stanford Medicine for eligible courses
Cons
  • US healthcare examples
  • Acceptance of US CME by Indian councils is not stated
  • Longer than the headline duration suggests
Format
Online, self-paced; five courses
Duration
About 60 hours across the five courses
Fee
Not shown; included in Coursera Plus; financial aid available
Certificate
Stanford Online certificate via Coursera
CME
Stanford Medicine is ACCME-accredited; see each course page for credits
Level
Beginner

Source: Coursera specialisation page, checked October 2026. Fees and dates change; confirm on the provider’s page before you apply.

Indian institute · 6 months

2. IIT Delhi: Executive Programme for AI in Healthcare

Continuing Education Programme (CEP), IIT Delhi, delivered with Digivarsity

The most substantial Indian programme we found. It runs live online on weekends for six months, includes a two-day campus immersion at IIT Delhi with a twelve-hour hands-on workshop, and finishes with a faculty-guided capstone. It is technical: the final assessment includes a proctored coding test in Python or MATLAB.

What you learn: machine learning and deep learning foundations; healthcare data types such as EMR, imaging and genomics, with data ethics; AI decision support, generative AI and deployment; and public health analytics.

Who it is for: clinicians, researchers and health-technology professionals willing to learn some programming.

Pros
  • IIT Delhi certificate
  • Campus immersion and hands-on workshop
  • Indian context, including DISHA in the data module
Cons
  • Coding test in the final assessment
  • Next batch date not shown on the official partner page
  • Page gives both 6 months and 1 year
Format
Live online on weekends, plus a 2-day campus immersion
Duration
6 months (the page also mentions 1 year)
Fee
₹1,50,000 one-time programme fee as listed
Certificate
e-Certificate of Successful Completion from CEP, IIT Delhi
Eligibility
Graduates in a relevant field; no prior technical background required
Next batch
Not shown; the page offers “Notify Me”

Source: Digivarsity programme page (IIT Delhi CEP), checked October 2026. Fees and dates change; confirm on the provider’s page before you apply.

Global university · 10 weeks

3. Johns Hopkins University: AI and Agentic AI in Healthcare

Johns Hopkins University, delivered with Great Learning

A ten-week online programme with live masterclasses by Johns Hopkins faculty and weekly mentored sessions. It is up to date on large language models and agentic AI, priced in rupees, and needs no coding, which makes it the most accessible global-university option for Indian clinicians and hospital managers.

What you learn: foundations of AI for healthcare; AI for clinical decision support; AI for population health and disease management; and business strategy for AI in healthcare.

Who it is for: clinicians moving into leadership, hospital administrators, and pharma and health-technology professionals.

Pros
  • No coding required
  • Rupee fee with EMI options
  • Current content on LLMs and agents
Cons
  • Expensive for ten weeks
  • Weekly support is largely from mentors, not faculty
  • Start date to be announced
Format
Online, with live masterclasses and mentored sessions
Duration
10 weeks at 6 to 8 hours a week
Fee
₹1,80,000 + GST; EMI from ₹5,465 a month
Certificate
Certificate of Completion from Johns Hopkins University
Credits
6 CEUs (continuing education units, not CME)
Deadline
Applications close 31 October 2026

Source: Johns Hopkins programme page, checked October 2026. Fees and dates change; confirm on the provider’s page before you apply.

Leadership · 8 weeks

4. Harvard Medical School: AI in Health Care: From Strategies to Implementation

Harvard Medical School Executive Education

An eight-week online programme for people who decide whether and how AI is adopted: medical directors, department heads and health-system leaders. It focuses on judging AI projects, not building them, with weekly office hours and live faculty sessions.

What you learn: a framework for the AI development pipeline; transparency, reproducibility and generalisability; bias and potential harm; and implementation strategy, ending with a capstone pitch.

Who it is for: senior clinicians and managers in hospitals, health systems and life sciences who will approve or lead AI initiatives.

Pros
  • Harvard Medical School faculty
  • Strategy and risk, not code
  • Live sessions and office hours
Cons
  • Priced in US dollars
  • No CME or academic credit stated
  • Strategic rather than clinical
Format
Online, with live faculty sessions
Duration
8 weeks at 4 to 6 hours a week
Fee
US$3,150
Certificate
Digital certificate from Harvard Medical School Executive Education
Credit
The page says it does not grant academic credit
Next intake
10 December 2026 to 18 February 2027

Source: Harvard Medical School programme page, checked October 2026. Fees and dates change; confirm on the provider’s page before you apply.

Low cost · Indian university

5. University of Delhi: Certificate Course on Applications of Artificial Intelligence in Health Sciences

Research Council, University of Delhi

A fifteen-week weekend course from the University of Delhi with hands-on labs. It leans towards research and data work, including medical imaging and bioinformatics, so it suits doctors in academic medicine more than those looking only for productivity skills.

What you learn: evaluating machine learning models with ROC, AUC and calibration; medical imaging workflows, including DICOM, PACS and annotation tools; and bioinformatics and multi-omics with survival analysis.

Who it is for: MBBS, nursing and pharmacy graduates, life-science researchers and technologists, according to the university’s brochure.

Pros
  • University of Delhi certificate
  • Hands-on labs
  • Likely the lowest-cost paid option here
Cons
  • The second batch began in September 2026; next intake not yet listed
  • Fee not shown on the current page
  • Research and bioinformatics emphasis
Format
Live online on Saturdays and Sundays
Duration
15 weeks; 8 modules
Fee
Not shown on the current page; an earlier poster listed a registration fee of ₹10,000
Certificate
University of Delhi
Seats
50 per batch
Next intake
Watch the course site

Source: University of Delhi course site, checked October 2026. Fees and dates change; confirm on the provider’s page before you apply.

Frequent intakes · 10 weeks

6. MIT xPRO: Artificial Intelligence in Healthcare: Fundamentals and Applications

MIT xPRO

A ten-week online course from MIT’s professional education arm with several intakes a year. The official page says little about modules, so check the brochure before paying; its strength is the MIT name and a regular schedule that fits around clinical rotas.

What you learn: how AI is changing patient care, clinical roles and medical processes, according to the course page.

Who it is for: healthcare professionals and managers who want an MIT certificate and a structured ten-week course.

Pros
  • MIT certificate
  • Intakes roughly every quarter
  • Fixed, predictable length
Cons
  • Little syllabus detail on the official page
  • Priced in US dollars
  • Prerequisites not stated
Format
Online
Duration
10 weeks
Fee
US$2,700
Certificate
Course certificate of completion
Start dates
11 November 2026; 3 February, 14 April and 22 June 2027
Level
Not stated

Source: MIT Professional Education page, checked October 2026. Fees and dates change; confirm on the provider’s page before you apply.

Technical · for doctors who code

7. DeepLearning.AI: AI for Medicine Specialization

DeepLearning.AI, on Coursera

A hands-on technical series in which you build and evaluate medical AI models yourself. It suits the growing number of doctors who code or want to work with data-science teams on equal terms. It is not a literacy course.

What you learn: classifying chest X-rays with deep learning; measuring performance with sensitivity, specificity and ROC curves; and segmenting brain MRI images, in the first course of the series.

Who it is for: clinicians and researchers with intermediate Python and some knowledge of neural networks. No medical background is required for technologists.

Pros
  • Real model-building practice
  • Teaches evaluation metrics properly
  • Self-paced
Cons
  • Requires intermediate Python and deep-learning basics
  • No CME
  • Too technical for most clinicians
Format
Online, self-paced
Duration
Listed as about 2 weeks at 10 hours a week for the first course
Fee
Not shown; financial aid available
Certificate
Shareable certificate (paid option)
Level
Intermediate
Prerequisites
Python and convolutional neural networks

Source: Coursera course page, checked October 2026. Fees and dates change; confirm on the provider’s page before you apply.

Worth watching: the National Board of Examinations in Medical Sciences (NBEMS) ran a free six-month online programme on AI in medical education from January 2026 for its trainees, alumni and faculty, with a completion certificate for those meeting attendance and assessment rules; we found no second cohort announced yet. IIT Madras ran an NPTEL+ course, AI for clinicians, in April and May 2026 at a nominal fee, now closed. IIHMR Bangalore’s Generative AI for Doctors executive certificate last listed a May 2026 start. Check these institutions for new dates.

Illustration of a hybrid training session with remote participants on a video wall and colleagues in the room

Where Skillopedia fits

For hospital and healthcare teams, not individual doctors

Skillopedia does not teach clinical AI and does not run courses for individual doctors. We are a training firm (Skillopedia LLP, Mumbai, est. 2017) that has worked with 335+ organisations across 13 sectors, and we run live, in-company programmes on everyday generative AI for organisations, including hospital groups, diagnostics chains and pharma companies.

That work sits outside clinical decision-making: administrative writing, policy and SOP drafting, training material, patient-communication drafts reviewed by clinicians, operations reporting and meeting summaries, using approved tools such as ChatGPT, Microsoft Copilot or Claude, with a firm rule that patient-identifiable data stays out unless the tool is approved for it. The usual starting point is our Generative AI for Productivity programme; patient-services teams may also want AI training for customer service. Participants rate our programmes 4.8/5 on average (300+ surveyed).

How to choose

Literacy, leadership or building models: which do you need?

Most practising doctors need AI literacy: enough to read a vendor’s validation claims, spot a biased dataset and use a general assistant safely for non-clinical writing. Stanford’s specialisation covers this at low cost; Johns Hopkins covers it with more structure and live sessions.

Medical directors and department heads deciding what a hospital buys should look at Harvard Medical School or Johns Hopkins, both of which focus on strategy, governance and implementation.

Doctors who want to build should choose IIT Delhi for an Indian credential with campus time, or DeepLearning.AI for self-paced technical practice. Academic clinicians interested in imaging and omics may prefer the University of Delhi course.

Leading a hospital or health business? Our list of AI courses for leaders covers strategy programmes across sectors.

Illustration of a business leader presenting a rising bar chart to a seated audience

Questions to ask any provider

  • Does the course need coding, and how much?
  • Are CME or CPD credits offered, and from which body?
  • Does it teach how to evaluate an AI tool’s evidence?
  • Who teaches the live sessions: faculty or mentors?

Red flags

  • Claims that AI will replace clinical judgement
  • Exercises using real patient records in public tools
  • No discussion of bias, validation or consent
  • Certificates marketed as a medical qualification

For hospital leaders training staff

  • Which AI tools are approved, and for which data?
  • Who reviews AI-drafted patient communication?
  • How will non-clinical staff be trained?
  • What will we check after 90 days?

A learning path

A 12-week path for a busy clinician

Short, regular sessions fit around clinical duties better than long blocks. This sequence builds judgement first and tool use second.

Week 1Know the rulesRead your hospital’s AI policy and ICMR’s 2023 ethical guidelines for AI in healthcare.
Weeks 2 to 5FoundationsComplete the first two Stanford courses on healthcare and clinical data.
Weeks 6 to 8EvaluationTake the course on evaluating AI applications and apply it to one tool your department uses.
Weeks 9 to 11Safe everyday useUse an approved assistant for non-clinical writing, with no patient identifiers.
Week 12SharePresent what you learned and the questions to ask vendors at a departmental meeting.

What good looks like

What an AI course for doctors should cover

Evaluation, not just enthusiasm. Sensitivity and specificity, calibration, external validation and the difference between a retrospective study and real-world performance.

Bias and generalisability. Models trained on one population can perform worse on another. Indian clinicians should ask whether a tool was validated on Indian patients.

Patient data and consent. India’s Digital Personal Data Protection Act, 2023 applies to digital personal data, including patient records. The DPDP Rules were notified in November 2025, with most obligations on organisations phased in over the following 18 months. In practice: no patient-identifiable information in public AI tools, and only approved systems for clinical data.

Ethics and accountability. ICMR’s Ethical Guidelines for Application of Artificial Intelligence in Biomedical Research and Healthcare (2023) set out principles on accountability, consent and ethics review. A good course should reference them or their equivalent.

Everyday, non-clinical use. Summaries, letters, teaching material and patient leaflets drafted with AI still need clinical review for accuracy and tone.

Not medical or legal advice. Skillopedia is a training firm. Whether a particular AI tool or use of patient data is appropriate is a matter for your institution’s ethics committee, data protection officer, medical council rules and legal advisers. See ICMR’s AI guidelines for the national ethical framework.
Two colleagues reviewing analysis on screen in a workshop
Representative photo: two colleagues checking an analysis on screen.
Illustration of two colleagues reviewing a long document with highlighted lines and an approval tick

Measuring it

How a hospital can tell whether AI training worked

Course providers do not publish outcome data that a medical director should rely on. Measure your own teams, and keep clinical outcomes out of the claim until you have proper evidence.

What to measureHowWhen
Policy knowledgeShort quiz on which tools and data are allowedWeeks 0 and 4
Administrative timeTime spent on letters, summaries and reports before and afterWeeks 0 and 8
Review qualityAudit a sample of AI-drafted documents for errors caught before useMonthly
Data incidentsTrack any patient data entered into unapproved toolsOngoing
Vendor questionsCheck that AI purchases include validation and bias questionsEach purchase

For hospitals, clinic networks and pharma

Training your healthcare teams together?

Tell us the teams, numbers and approved AI tools. We reply within one working day, and after a short call you receive a written proposal covering:

  • sessions for administrators, nursing and clinical leads, and support teams
  • labs on your own SOPs and documents, with patient data removed
  • a draft rule on patient data and review of AI drafts
  • a check on adoption after 30 days

Ask for a healthcare team proposal

We reply within one working day. No obligation.

Contact Us

FAQ

AI courses for doctors in India: common questions

For most practising doctors, Stanford’s AI in Healthcare specialisation on Coursera is the best-value start and needs no coding. For an Indian institute certificate, IIT Delhi’s Executive Programme for AI in Healthcare is the main option, but it includes a coding test. Johns Hopkins and Harvard Medical School suit clinical leaders.

NBEMS ran a free online AI programme in 2026 for its trainees, alumni and faculty; watch for a new cohort. Coursera courses such as Stanford’s offer financial aid. Many other courses are paid.

Not for AI literacy or leadership courses such as Stanford, Johns Hopkins and Harvard Medical School. IIT Delhi’s programme includes a Python or MATLAB test, and DeepLearning.AI’s series requires intermediate Python.

Some do. Stanford University School of Medicine is accredited to provide CME, and credits are listed on individual course pages. Whether an Indian state medical council accepts a given credit is not stated on the course pages, so check with your council.

When we checked, IIT Delhi’s CEP programme was taking expressions of interest for its next batch. IIT Madras’s NPTEL+ AI for clinicians had closed. We found no open AIIMS certificate course on AI.

From eight weeks (Harvard Medical School) and ten weeks (Johns Hopkins, MIT xPRO) to fifteen weeks (University of Delhi), six months (IIT Delhi) or about 60 hours at your own pace (Stanford).

For non-clinical writing, if your institution allows it and no patient-identifiable data is entered. Clinical use needs approved, validated tools and must follow your institution’s policy. This page is not medical or legal advice.

The DPDP Act, 2023 applies to digital personal data, including patient records, with Rules notified in November 2025 and most organisational duties phased in over 18 months. How it applies to your practice is a question for your legal advisers.

ICMR published Ethical Guidelines for Application of Artificial Intelligence in Biomedical Research and Healthcare in 2023. They cover principles such as accountability, consent and ethics review for developers, clinicians and ethics committees.

It shows you have studied the subject, which helps in roles involving digital health, research or procurement. It is not a medical qualification, and the skills you can demonstrate matter more.

Yes. Stanford, Johns Hopkins and the University of Delhi course are open to a range of healthcare professionals. Check each course’s eligibility before applying.

No. Skillopedia runs live in-company programmes on everyday generative AI for organisations, including hospital groups and pharma companies, focused on non-clinical work. It does not teach clinical AI.

Set a policy on approved tools and patient data, start with non-clinical tasks, train by role, name champions in each department and review after 30 and 90 days. Our guide to identifying AI use cases helps you pick safe first tasks.

Next step

Help your healthcare teams use AI safely

Tell us about your organisation, the teams involved and the AI tools you have approved. We reply within one working day with a few questions, then send a written proposal with a fixed fee.

  • Labs on your own SOPs and documents, with patient data removed
  • A patient-data and review rule your leadership can sign
  • A 30-day adoption check

Ask for a healthcare team proposal

Reply within one working day.

Contact Us