LangGraph in Healthcare: Workflow Orchestration for Regulated Environments Training Course

LangGraph is a framework designed for creating stateful, multi-actor LLM applications as composable graphs, featuring persistent state and execution control.

This instructor-led live training, available online or onsite, targets advanced AI platform engineers, AI DevOps specialists, and ML architects looking to optimize, debug, monitor, and operate production-grade LangGraph systems.

Upon completing this training, participants will be able to:

• Design and optimize complex LangGraph topologies to enhance speed, reduce costs, and improve scalability.
• Build reliability into systems using retries, timeouts, idempotency, and checkpoint-based recovery mechanisms.
• Debug and trace graph executions, inspect states, and systematically reproduce issues encountered in production.
• Instrument graphs with logs, metrics, and traces, deploy them to production, and monitor SLAs and associated costs.

Course Format

• Interactive lectures and discussions.
• Extensive exercises and practical application.
• Hands-on implementation in a live-lab environment.

Customization Options

• For customized training requests, please contact us to arrange your session.

Agentic AI represents a methodology where artificial intelligence systems engage in planning, reasoning, and executing tool-based actions to achieve specific objectives within set boundaries.

This instructor-led training session, available either online or at your premises, is tailored for intermediate-level healthcare and data professionals seeking to design, assess, and oversee agentic AI solutions for clinical and operational scenarios.

Upon completing this training, participants will be capable of:

• Articulating the core concepts and limitations of agentic AI within healthcare environments.
• Constructing secure agent workflows that incorporate planning, memory retention, and tool utilization.
• Developing retrieval-augmented agents capable of processing clinical documents and knowledge bases.
• Assessing, monitoring, and governing agent behavior through the implementation of safety guardrails and human-in-the-loop controls.

Training Format

• Engaging lectures coupled with guided discussions.
• Hands-on labs and code walkthroughs conducted in a sandbox environment.
• Scenario-based exercises focusing on safety protocols, evaluation techniques, and governance frameworks.

Customization Options

• For tailored training requests, please reach out to us to discuss arrangements.

This instructor-led, live training in Norway (online or onsite) is designed for intermediate to advanced healthcare professionals and AI developers seeking to implement AI-driven healthcare solutions.

Upon completion of this training, participants will be equipped to:

• Grasp the significance of AI agents within healthcare and diagnostic contexts.
• Create AI models tailored for medical image analysis and predictive diagnostics.
• Seamlessly integrate AI tools with electronic health records (EHR) and clinical workflows.
• Guarantee adherence to healthcare regulations and ethical AI standards.

This instructor-led, real-time training in Norway (online or in-person) is designed for intermediate-level healthcare professionals who wish to implement AI and AR/VR solutions for medical education, surgical simulations, and rehabilitation.

By the conclusion of this training, participants will be able to:

• Understand how AI enhances AR/VR experiences in healthcare.
• Use AR/VR for surgery simulations and medical training.
• Apply AR/VR tools in patient rehabilitation and therapy.
• Explore the ethical and privacy concerns in AI-enhanced medical tools.

This instructor-led, live training in Norway (online or onsite) is aimed at intermediate-level data scientists and healthcare professionals who wish to leverage AI for advanced healthcare applications using Google Colab.

By the end of this training, participants will be able to:

• Implement AI models for healthcare using Google Colab.
• Use AI for predictive modeling in healthcare data.
• Analyze medical images with AI-driven techniques.
• Explore ethical considerations in AI-based healthcare solutions.

This instructor-led, live training in Norway (online or onsite) is designed for intermediate-level healthcare professionals and data scientists who wish to understand and apply AI technologies in healthcare environments.

By the end of this training, participants will be able to:

• Identify key healthcare challenges that AI can address.
• Analyze AI’s impact on patient care, safety, and medical research.
• Understand the relationship between AI and healthcare business models.
• Apply fundamental AI concepts to healthcare scenarios.
• Develop machine learning models for medical data analysis.

This instructor-led, live training in Norway (online or onsite) targets healthcare professionals and researchers eager to harness ChatGPT to improve patient care, optimize workflows, and enhance healthcare outcomes.

Upon completion of this training, participants will be able to:

• Grasp the fundamentals of ChatGPT and its specific applications in healthcare.
• Deploy ChatGPT to automate healthcare processes and patient interactions.
• Deliver precise medical information and support to patients via ChatGPT.
• Apply ChatGPT for medical research and analytical tasks.

This instructor-led, live training in Norway (online or onsite) targets intermediate-level healthcare professionals, biomedical engineers, and AI developers who wish to leverage Edge AI for innovative healthcare solutions.

By the end of this training, participants will be able to:

• Understand the role and benefits of Edge AI in healthcare.
• Develop and deploy AI models on edge devices for healthcare applications.
• Implement Edge AI solutions in wearable devices and diagnostic tools.
• Design and deploy patient monitoring systems using Edge AI.
• Address ethical and regulatory considerations in healthcare AI applications.

This instructor-led, live training in Norway (online or onsite) is designed for intermediate to advanced medical AI developers and data scientists who aim to fine-tune models for clinical diagnosis, disease prediction, and patient outcome forecasting using structured and unstructured medical data.

By the end of this training, participants will be able to:

• Fine-tune AI models on healthcare datasets including EMRs, imaging, and time-series data.
• Apply transfer learning, domain adaptation, and model compression in medical contexts.
• Address privacy, bias, and regulatory compliance in model development.
• Deploy and monitor fine-tuned models in real-world healthcare environments.

Generative AI is a technology that creates new content such as text, images, and recommendations based on prompts and data.

This instructor-led, live training (online or onsite) is aimed at beginner-level to intermediate-level healthcare professionals who wish to use generative AI and prompt engineering to improve efficiency, accuracy, and communication in medical contexts.

By the end of this training, participants will be able to:

• Understand the fundamentals of generative AI and prompt engineering.
• Apply AI tools to streamline clinical, administrative, and research tasks.
• Ensure ethical, safe, and compliant use of AI in healthcare.
• Optimize prompts to achieve consistent and accurate results.

Format of the Course

• Interactive lecture and discussion.
• Practical exercises and case studies.
• Hands-on experimentation with AI tools.

Course Customization Options

• To request a customized training for this course, please contact us to arrange.

LangGraph is a framework designed for constructing stateful, multi-agent LLM applications by composing graphs that maintain persistent state and allow precise control over execution flow.

This instructor-led training, available both online and on-site, is tailored for intermediate to advanced professionals aiming to design, implement, and manage LangGraph-based financial solutions with robust governance, observability, and compliance.

Upon completion of this training, participants will be equipped to:

• Design financial LangGraph workflows that align with regulatory and audit requirements.
• Integrate financial data standards and ontologies into graph state and tooling.
• Implement reliability, safety, and human-in-the-loop controls for critical processes.
• Deploy, monitor, and optimize LangGraph systems for performance, cost, and SLAs.

Course Format

• Interactive lectures and discussions.
• Extensive exercises and practical application.
• Hands-on implementation in a live-lab environment.

Course Customization Options

• To request a customized training for this course, please contact us to arrange.

LangGraph is a framework for constructing LLM applications with a graph structure, supporting planning, branching, tool use, memory, and controllable execution.

This instructor-led, live training (available online or onsite) is designed for beginner-level developers, prompt engineers, and data practitioners aiming to design and build reliable, multi-step LLM workflows using LangGraph.

By the end of this training, participants will be able to:

• Explain core LangGraph concepts (nodes, edges, state) and when to use them.
• Build prompt chains that branch, call tools, and maintain memory.
• Integrate retrieval and external APIs into graph workflows.
• Test, debug, and evaluate LangGraph apps for reliability and safety.

Format of the Course

• Interactive lecture and facilitated discussion.
• Guided labs and code walkthroughs in a sandbox environment.
• Scenario-based exercises on design, testing, and evaluation.

Course Customization Options

• To request a customized training for this course, please contact us to arrange.

LangGraph serves as a framework for constructing stateful, multi-agent LLM applications as composable graphs, featuring persistent state and precise execution control.

This instructor-led, live training (available online or onsite) targets intermediate to advanced professionals seeking to design, implement, and manage LangGraph-based legal solutions with the necessary compliance, traceability, and governance controls.

Upon completing this training, participants will be capable of:

• Designing legal-specific LangGraph workflows that ensure auditability and compliance.
• Integrating legal ontologies and document standards into graph state and processing.
• Implementing guardrails, human-in-the-loop approvals, and traceable decision paths.
• Deploying, monitoring, and maintaining LangGraph services in production with observability and cost controls.

Course Format

• Interactive lectures and discussions.
• Numerous exercises and practical activities.
• Hands-on implementation in a live-lab environment.

Customization Options

• To request customized training for this course, please contact us to arrange.

LangGraph serves as a framework designed for composing graph-structured LLM workflows that support branching, tool use, memory, and controllable execution.

This instructor-led, live training (available online or onsite) targets intermediate-level engineers and product teams who wish to combine LangGraph’s graph logic with LLM agent loops to build dynamic, context-aware applications such as customer support agents, decision trees, and information retrieval systems.

By the end of this training, participants will be able to:

• Design graph-based workflows that coordinate LLM agents, tools, and memory.
• Implement conditional routing, retries, and fallbacks for robust execution.
• Integrate retrieval, APIs, and structured outputs into agent loops.
• Evaluate, monitor, and harden agent behavior for reliability and safety.

Format of the Course

• Interactive lecture and facilitated discussion.
• Guided labs and code walkthroughs in a sandbox environment.
• Scenario-based design exercises and peer reviews.

Course Customization Options

• To request a customized training for this course, please contact us to arrange.

LangGraph serves as a graph-based orchestration framework that facilitates conditional, multi-step workflows involving LLMs and tools, making it highly suitable for automating and personalizing content pipelines.

This live training, led by an instructor and available either online or onsite, targets intermediate-level marketers, content strategists, and automation developers who aim to implement dynamic, branching email campaigns and content generation pipelines using LangGraph.

Upon completion of this training, participants will be capable of:

• Designing graph-structured content and email workflows utilizing conditional logic.
• Integrating LLMs, APIs, and data sources to enable automated personalization.
• Managing state, memory, and context across multi-step campaigns.
• Evaluating, monitoring, and optimizing workflow performance and delivery outcomes.

Course Format

• Interactive lectures paired with group discussions.
• Practical labs focused on implementing email workflows and content pipelines.
• Scenario-based exercises covering personalization, segmentation, and branching logic.

Customization Options

• For a customized training session tailored to your needs, please get in touch with us to arrange it.