7 Best Generative AI Courses for Doctors in 2026

If you are new to generative AI and want a broad, no-coding foundation, start with Generative AI for Everyone by DeepLearning.AI. If you want a personalised path built around your own clinical and administrative goals, consider Upskili, the platform that publishes this guide. If you need a formal certificate or deeper technical skills, look at the programs from Johns Hopkins, Udacity or Google Cloud depending on your role.

Quick comparison

How we chose these courses

We selected these seven courses based on what a working doctor actually needs from generative AI training. Each course had to meet most of these criteria:

• Relevance to doctors' real work: The content should connect to clinical documentation, patient communication, summarising evidence, and administrative or governance tasks.
• No unnecessary prerequisites: The list includes courses open to beginners with no coding or prior AI knowledge, as well as technical options with clearly stated prerequisites.
• Hands-on practice: We looked for courses that offer opportunities to apply generative AI to tasks, not just watch lectures.
• Clear cost: We preferred courses with transparent pricing or a free tier where the provider states it.
• Recognised certificate where it matters: For doctors planning to use the course for CPD or appraisal, a formal certificate from a known institution adds value.

The courses are ordered from the most accessible starting point to the most specialised. All details come from each provider's own page, checked on the dates given in our records. We did not take the courses ourselves.

The 7 best generative AI courses for doctors, one by one

1. Generative AI for Everyone (DeepLearning.AI)

Best for: Doctors who want a quick, no-code introduction to how generative AI works and what it can do.

This beginner course by Andrew Ng explains generative AI concepts, tools, and real-world uses without requiring coding or prior AI knowledge. It is a short, self-paced starting point for understanding the technology before applying it to clinical work.

What you'll learn:

• How generative AI works and what it can realistically do
• Common tools and their practical applications
• The impact of generative AI on business and society

Worth knowing: This is a foundational overview. It will not show you how to draft a referral letter or summarise a guideline, but it will give you the mental model to do so safely.

Cost and certificate: Check the provider's current pricing. A certificate is available with a PRO upgrade.

2. Upskili: a personalised path for your goal

Best for: Doctors who want learning built directly around their own goal: using generative AI safely in clinical and administrative work.

Upskili is not a fixed, pre-written course. You state your goal—for example, using AI to draft clearer discharge summaries or summarise research papers—and it builds a personalised, AI-powered learning path around your current skill level. It then adapts as you learn, measuring progress by demonstrated capability.

What you'll learn:

• Skills and concepts mapped to your specific goal, such as prompt crafting for clinical documentation or safe AI use in patient communication
• Concepts taught in the order you need them, based on your starting point

Worth knowing: This is a personalised path, not a standard syllabus with a fixed certificate. It is especially relevant if your learning needs do not fit a one-size-fits-all course.

Cost and certificate: Free to approximately $20, depending on AI token/credit usage. Certificate not stated.

3. Free Online Certificate in Artificial Intelligence and Career Empowerment (University of Maryland)

Best for: Early to mid-career doctors who want a free, broad overview of AI and its impact on professional roles.

Offered by the Robert H. Smith School of Business, this free online program covers an overview of Artificial Intelligence and its transformation of business functional areas. It also includes career empowerment topics like job searching and consulting, which can be useful for doctors exploring portfolio careers or leadership roles.

What you'll learn:

• A broad overview of Artificial Intelligence
• How AI transforms different business and functional areas
• Career empowerment strategies, including job searching and consulting

Worth knowing: The content is designed for a general professional audience. It will not cover clinical tasks directly, but the AI overview and career modules are transferable.

Cost and certificate: Free. You earn a free certificate in "Artificial Intelligence and Career Empowerment" from the University of Maryland.

4. Explore the business value of generative AI solutions (Microsoft Learn)

Best for: Clinical directors, service leads and doctors involved in planning or implementing AI within their department or trust.

This self-paced learning path from Microsoft Learn is aimed at business leaders. It walks through identifying high-value generative AI opportunities, assessing organisational readiness, and implementing responsible AI solutions using concepts like Microsoft Copilot and Azure AI.

What you'll learn:

• How to identify high-value generative AI opportunities
• Assessing readiness for AI implementation
• Responsible AI solution implementation

Worth knowing: This is not a clinical skills course. It is about evaluating and deploying AI solutions at an organisational level, which suits doctors in leadership or governance roles.

Cost and certificate: Check the provider's current pricing. Certificate not stated.

5. Applied Generative AI and Agentic AI (Johns Hopkins University)

Best for: Doctors who want a formal, university-backed certificate and a deeper technical understanding of generative AI.

This 16-week online program from Johns Hopkins covers a wide technical scope: LLMs, RAG, prompt engineering, fine-tuning, agentic workflows and responsible AI. It is designed for technology and data professionals and involves hands-on projects.

What you'll learn:

• Large Language Models (LLMs) and Retrieval-Augmented Generation (RAG)
• Prompt engineering and fine-tuning
• Agentic workflows and responsible AI principles

Worth knowing: This is a significant time commitment and is aimed at a technical audience. The certificate of completion and 11 CEUs are strong formal credentials for an appraisal or career progression portfolio.

Cost and certificate: Check the provider's current pricing. You earn a Certificate of Completion from Johns Hopkins University and 11 CEUs.

6. Applied Generative AI Engineering (Udacity)

Best for: Doctors in technical or informatics roles who want to build and deploy their own generative AI solutions.

This intermediate nanodegree program focuses on the practical skills of building generative AI systems. It covers model selection, prompt engineering, PEFT, RAG systems, vector databases and multimodal applications. It is aimed at developers.

What you'll learn:

• Building and deploying generative AI solutions
• Model selection and prompt engineering
• RAG systems, vector databases and multimodal applications

Worth knowing: This is a developer-focused course. A doctor without a technical background or informatics role would find it a steep climb. The subscription model means your total cost depends on your pace.

Cost and certificate: Subscription, billed monthly. You earn Program Certificates upon completion.

7. Advanced: Generative AI for Developers (Google Cloud)

Best for: Doctors working as App Developers, Machine Learning Engineers or Data Scientists who already have foundational AI knowledge.

This advanced learning path from Google Cloud contains 12 technical activities. It has a recommended prerequisite: the Introduction to Generative AI learning path. It is built specifically for technical practitioners.

What you'll learn:

• A technical Generative AI learning path with 12 activities
• Advanced concepts for developers and data scientists

Worth knowing: This is the most specialised and technical course on the list. It is not suitable as a first course in generative AI. The prerequisite path is essential.

Cost and certificate: Check the provider's current pricing. Certificate not stated.

Which course should you start with?

Your choice depends on your immediate need, your time, and whether you need a formal certificate.

• New to generative AI: Start with entry 1 (Generative AI for Everyone) for a clear, quick foundation.
• Short on time and want a free overview: Choose entry 3 (University of Maryland free certificate) for a broad, no-cost introduction.
• Need a certificate for CPD or appraisal: Look at entry 5 (Johns Hopkins) for a university-backed credential or entry 6 (Udacity) for a technical program certificate.
• Want to practise on your own clinical and administrative tasks: Entry 2 (Upskili) builds a path around your goal, and entry 4 (Microsoft Learn) helps you think about implementing AI in your service.
• In a technical or informatics role: Entry 7 (Google Cloud) is the direct path for those with the prerequisites.

A learning path for doctors

You do not need to do every course. A phased approach works better alongside a clinical workload.

Phase 1 – Foundations: Start with entry 1 (Generative AI for Everyone) or entry 3 (University of Maryland) for a broad, free or low-cost introduction. This phase builds your understanding of what generative AI is and is not.

Phase 2 – Hands-on practice with your own tasks: Apply that foundation to your daily work. Entry 2 (Upskili) builds a personalised path around your own goal, like drafting referral letters or summarising guidelines. Entry 4 (Microsoft Learn) suits you if your role includes planning AI adoption for your team or trust.

Phase 3 – Specialisation: If you want to go deeper, entry 5 (Johns Hopkins) offers a formal, university-level program. For building tools, entry 6 (Udacity) or entry 7 (Google Cloud) provide developer-level skills.

Where generative AI fits in a doctor's work

Generative AI is already finding its way into several areas of clinical and administrative work. In each case, the output is a draft that needs your professional review. AI output does not replace your clinical judgement or sign-off.

Clinical documentation: Drafting referral letters, discharge summaries and clinic notes. For example, a doctor could dictate or type bullet points from a consultation, ask an AI tool to draft a referral letter from those points, then review, correct and finalise the letter before signing it.

Patient communication: Creating plain-language explanations of diagnoses, procedures or consent information. For example, a doctor could ask AI to simplify a standard discharge instruction sheet into language a specific patient can understand, then check its accuracy and tone before sharing it.

Evidence and guideline review: Summarising new research, guidelines or long patient notes. For example, a doctor preparing for an MDT could prompt AI to summarise a new NICE guideline's key recommendations, then verify every point against the source document before relying on it.

Administrative and governance tasks: Drafting audit templates, quality improvement reports and rota plans. For example, a doctor leading an audit could ask AI to draft a data collection template and a report structure, then review and adapt both for the specific project.

How to decide where to start

Match the course to your most pressing need: a broad understanding, a formal certificate, or hands-on practice with your own tasks. Consider your available time. A five-hour foundation course or a free certificate might be the right first step before a longer commitment. If you want a path built around the exact tasks on your desk, start with your own goal on Upskili. Whatever you choose, apply what you learn to one real, low-risk task—and always review the output before it goes near a patient.