Udemy - Healthcare AI Engineering - 100 Labs HL7 FHIR and Kubern...
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Healthcare AI Engineering: 100 Labs | HL7 FHIR & Kubernetes https://WebToolTip.com Published 8/2026 Created by Dar Al Taqniya MP4 | Video: h264, 1280x720 | Audio: AAC, 44.1 KHz, 2 Ch Level: All Levels | Genre: eLearning | Language: English | Duration: 112 Lectures ( 19h 49m ) | Size: 987.6 MB From isolated coding to production-grade Healthcare AI, FHIR, Telemedicine & Kubernetes engineering. What you'll learn ⚡ Architect enterprise-grade HL7 FHIR healthcare platforms from the ground up u
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Healthcare AI Engineering: 100 Labs | HL7 FHIR & Kubernetes
https://WebToolTip.com
Published 8/2026
Created by Dar Al Taqniya
MP4 | Video: h264, 1280x720 | Audio: AAC, 44.1 KHz, 2 Ch
Level: All Levels | Genre: eLearning | Language: English | Duration: 112 Lectures ( 19h 49m ) | Size: 987.6 MB
From isolated coding to production-grade Healthcare AI, FHIR, Telemedicine & Kubernetes engineering.
What you'll learn
⚡ Architect enterprise-grade HL7 FHIR healthcare platforms from the ground up using entirely open-source technologies.
⚡ Deploy secure, encrypted telemedicine infrastructure with WebRTC, TURN/STUN, TLS, OAuth2, JWT, and API gateways.
⚡ Design real-time healthcare data pipelines using Kafka, PostgreSQL, InfluxDB, Grafana, and Python.
⚡ Build AI-powered medical inference services using FastAPI, PyTorch, ONNX Runtime, and containerized microservices.
⚡ Implement production-level security including Keycloak, Vault, SMART on FHIR, Cilium, Trivy, immutable audit logging, and disaster recovery.
⚡ Master healthcare observability through Prometheus, Grafana, Loki, OpenTelemetry, distributed tracing, and SRE practices.
⚡ Engineer resilient IoT healthcare systems using MQTT, ESP32, Kubernetes Edge (K3s), secure OTA updates, and offline synchronization.
⚡ Automate Kubernetes deployments using GitOps, ArgoCD, Helm, cert-manager, ExternalDNS, and production CI/CD principles.
⚡ Validate healthcare systems against interoperability, security, compliance, resilience, and performance requirements used by modern enterprises.
⚡ Complete a production-scale Autonomous Tele-Diagnostic Mesh integrating Healthcare AI, Telemedicine, Edge Computing, Kubernetes, Security, and FHIR interoperabi
Requirements
❗ Students should have
❗ 1. Basic computer literacy
❗ 2. Basic understanding of networking concepts is helpful but not required
❗ 3. Basic familiarity with Linux command line is recommended
❗ 4. Curiosity to build production systems
❗ Software
❗ 1. Ubuntu Linux 24.04 LTS (recommended)
❗ 2. Python 3.12+
❗ 3. Docker Engine
❗ 4. Kubernetes (kubeadm or K3s during later labs)
❗ 5. Visual Studio Code
❗ Minimum Hardware Requirement
❗ 1. Quad-Core CPU
❗ 2. 16 GB RAM
❗ 3. 100 GB free SSD storage