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The Intelligent Clinic: AI-Dietitian Masterclass

Categories: AI
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About Course

Before you enrol

Language
Lessons are spoken in Egyptian Arabic with English technical terms. Slides and downloadable resources are in English.
Format
Self-paced recorded lessons, plus periodic live Q&A sessions. Live sessions are recorded and added to the course.
Start
Start any time. Access opens as soon as your payment is confirmed.
Access
Lifetime access to the course for as long as it is offered on Nutripedia.
Learning time
About 40 hours of estimated total learning time, including recorded lessons, labs and exercises.
Level
No prior AI experience needed. Designed for nutrition students and practitioners; the clinical exercises assume basic nutrition knowledge.
Support
Ask questions in the course Q&A, and bring them to the live Q&A sessions.
Price & payment
EGP 1,500, paid by InstaPay, Vodafone Cash or bank transfer. Access is activated after we confirm your payment.
Refunds
No refunds once course access has been granted. Read the refund policy.

The Intelligent Clinic: AI-Dietitian Masterclass — the complete curriculum for next-generation nutritionists and smart clinical practice.

An intensive, hands-on masterclass that helps clinical dietitians, nutrition specialists and wellness consultants use AI as an always-available assistant in their practice. You will learn to speed up evidence-based research, calculate macro- and micronutrient targets accurately (with every number checked), manage complex clinical cases, automate client follow-up and produce engaging health content in far less time — while every professional decision stays with you and patient data stays protected.

Instructor

Dr. Sandy Emad — Clinical Nutrition & Obesity Management Specialist. Member of ESNO, EASHTN and EMASO. View profile

Course at a glance

  • Total duration: About 40 hours of estimated total learning time (recorded lessons, labs and exercises).
  • Format: interactive modules, live demos, case studies (fictional or de-identified) and a clinical capstone.
  • Prerequisites: no technical or coding background required — suitable for students, clinic owners and online consultants.
  • Core tools: ChatGPT (including Custom GPTs), Claude AI, Google Gemini, Perplexity AI, Google NotebookLM, Canva AI, Kling AI, Lovable, Notion and n8n.

Some tools require paid subscriptions, which participants cover themselves.

Who this course is for

  • Clinical dietitians and nutritionists: spend less time on meal planning and clinical calculations, and more on patient care and behavioural coaching.
  • Clinic and private-practice owners: modernise workflows, automate check-ins and appointment scheduling, and build simple landing pages.
  • Online nutrition coaches and consultants: scale consultations, automate client intake and CRM, and grow a professional social media presence.
  • Nutrition and health-science students and graduates: learn future-ready tools and build a strong portfolio.

Therapeutic plans for medical conditions are applied only within each participant’s professional scope and licence. The course does not qualify non-specialists to diagnose or prescribe treatment.

Course modules

  • Module 1: AI Foundations & Prompt Engineering for Healthcare (RTF, CTF, TRACE).
  • Module 2: Evidence-Based Clinical Nutrition & Meal Planning (macros, micros and clinical conditions).
  • Module 3: Clinical Research, Deep Study & Modern Clinic Tools (Perplexity, NotebookLM, Lovable).
  • Module 4: Practice Automation, CRM & Workflow Orchestration (Notion, n8n, WhatsApp).
  • Module 5: Social Media Strategy, Visual Design & Practice Growth (Canva AI, Kling AI, Nano Banana).
  • Module 6: Capstone Project & Clinical Defence.

Bonus resources & toolkits

  • Clinical Prompt Library (150+ prompts) organised under the RTF, CTF and TRACE frameworks and reviewed by the instructor.
  • 15+ condition-specific diet blueprints for chronic conditions, athletic preparation and gut health — to adapt after your own professional assessment.
  • Smart nutrition calculator prompts that pair food-composition data with conversational AI.
  • The Intelligent Clinic Notion workspace: a ready-to-duplicate client CRM, appointment tracker and measurement registry.
  • Canva AI clinical design kit: templates for Instagram carousels, infographics and client onboarding packs.
  • Certificate of completion issued by Nutripedia.

Certificate

Awarded after completing the modules, labs and capstone project. It confirms completion of this course; it is not a professional licence or an accreditation from an external body.

Privacy and responsible use

You practise with fictional or de-identified cases. Never upload identifiable patient data, photos or records to public AI tools. When you build client systems with Notion, n8n, WhatsApp and Lovable, the course covers consent and data protection. AI output is a draft: the specialist reviews it and remains responsible for it.

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Course Content

Module 1: AI Foundations & Prompt Engineering for Healthcare
Understand the strengths and limitations of today's leading AI models, master specialised prompting frameworks, and learn to detect and reduce AI "hallucinations".

  • Unit 1.1: Foundations of Artificial Intelligence in Healthcare
  • Unit 1.2: Clinical Prompt Engineering Architectures

Module 2: Evidence-Based Clinical Nutrition & Meal Planning
Use AI assistants, under professional review, to set macronutrient and micronutrient targets across complex clinical conditions.

Module 3: Clinical Research, Deep Study & Modern Clinic Tools
Synthesise the scientific literature quickly — verifying every source — and build simple digital tools for your practice.

Module 4: Practice Automation, CRM & Workflow Orchestration
Move from manual patient tracking to organised databases and automated workflows — with client consent and data protection.

Module 5: Social Media Strategy, Visual Design & Practice Growth
Build professional authority and educate prospective clients with generative design and video tools.

Module 6: Capstone Project & Clinical Defence
Bring all tools, protocols and automations together in an end-to-end project on a fictional or de-identified case.

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