The Ai Training Hub LLC - AI for Healthcare Professionals

Description

The AI for Healthcare Professionals Course is a specialized program that extends the skills gained in the AI Mastery Course into the healthcare domain. With the rise of Generative AI, LLMs, and Agentic AI systems, healthcare is entering a new era of innovation where predictive analytics, AI-augmented imaging, and intelligent virtual assistants are reshaping clinical workflows. In this 4-week course, participants will explore healthcare-specific use cases such as AI-powered diagnostics, patient engagement chatbots, robotic assistance in surgery, and ethical frameworks for managing sensitive medical data. By the end, learners will be equipped to deploy AI solutions tailored for clinical practice while preparing for the American Board of Artificial Intelligence in Medicine (ABAIM) certification exam.

Mode of Delivery

Virtual: Live interactive sessions via Zoom.
Hands-On Labs: Healthcare case studies using GenAI, LLMs, and agent-based tools. Led by clinician-data scientists with expertise in AI for healthcare.

Course Duration

20–40 hours

4 weeks (16 hours total).
Live Lectures: 2 hours (Hours to be decided).
Hands-On Sessions: 2 hours (Hours to be decided).

Course Fee

$1,500.00

$1,500 per participant. Early-bird registration: 10% off (for payments in full). Flexible payment plans available.

Prerequisites

Completion of the AI Mastery Course (12 Weeks).
Designed for healthcare professionals (physicians, nurses, pharmacists, allied health workers).

Detailed curriculum by phase and modules.

Phase 1: GenAI & LLM Use Cases in Healthcare (Week 1)

Module 1: Applying large language models to medical text, clinical documentation, and decision support 2 hours

Module 2: Building retrieval-augmented clinical assistants for physicians and nurses 2 hours

Phase 2: AI in Medical Imaging & Diagnostics (Week 2)

Module 3: Enhancing imaging workflows with computer vision and LLM-supported reporting 2 hours

Module 4: Case studies in radiology, pathology, and point-of-care diagnostics 2 hours

Phase 3: AI Agents in Clinical Operations (Week 3)

Module 5: Virtual health assistants for patient engagement 2 hours

Module 6: Robotic and AI-agent integration in surgery and hospital management 2 hours

Phase 4: Responsible AI in Medicine & Certification Prep (Week 4)

Module 7: Ethics, bias, and compliance in healthcare AI 2 hours

Module 8: Review and preparation for ABAIM certification exam 2 hours

Dr. Peter L. Takunju

Dr. Peter L. Takunju is a former NASA Senior Data Scientist with over 16 years of experience in AI, data science, and enterprise technology. He holds a PhD in Electrical Engineering, a Master’s in Engineering Management, and an MIT Professional Certificate in AI & Machine Learning, along with certifications in AWS Machine Learning, Azure AI, and Lean Six Sigma Black Belt. He specializes in building enterprise-grade AI solutions, including LLMs, RAG systems, agent-based architectures, computer vision, and NLP pipelines. His work focuses on transforming complex challenges into scalable, production-ready systems using Responsible AI and MLOps best practices. Hands-on labs are also delivered by industry experts from sectors such as healthcare, finance, and manufacturing, giving participants practical exposure to real-world AI applications and diverse industry perspectives.

156 Students 8 Lessons

Doctorate (PhD, MD, etc.)

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Professional Certifications & Achievements

Certificate 1

Certificate 2

Certificate 3

Certificate 4

Because this course focuses on healthcare-specific use cases, it assumes a solid foundation in AI, LLMs, RAG, and Agents provided in the AI Mastery Course.

Every module includes hands-on healthcare case studies, from clinical text mining to patient engagement AI assistants.

Yes. The course prepares participants for the ABAIM Introductory Course certification exam.

Yes. The short 4-week design respects the demanding schedules of healthcare professionals.

Reviews

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