LangGraph in Healthcare: Workflow Orchestration for Regulated Environments Training Course

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

This instructor-led, live training (online or onsite) is aimed at advanced-level AI platform engineers, DevOps for AI, and ML architects who wish to optimize, debug, monitor, and operate production-grade LangGraph systems.

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

• Design and optimize complex LangGraph topologies for speed, cost, and scalability.
• Engineer reliability with retries, timeouts, idempotency, and checkpoint-based recovery.
• Debug and trace graph executions, inspect state, and systematically reproduce production issues.
• Instrument graphs with logs, metrics, and traces, deploy to production, and monitor SLAs and costs.

Format of the Course

• Interactive lecture and discussion.
• Lots of exercises and practice.
• Hands-on implementation in a live-lab environment.

Course Customization Options

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

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

This instructor-led, live training (available online or onsite) is designed for intermediate-level healthcare and data professionals aiming to design, evaluate, and govern agentic AI solutions for clinical and operational scenarios.

Upon completing this training, participants will be equipped to:

• Articulate the principles and constraints of agentic AI within healthcare environments.
• Architect secure agent workflows incorporating planning, memory, and tool utilization.
• Develop retrieval-augmented agents capable of processing clinical documents and knowledge bases.
• Assess, monitor, and regulate agent behavior through guardrails and human-in-the-loop oversight mechanisms.

Course Format

• Interactive lectures coupled with facilitated discussions.
• Guided laboratory exercises and code walkthroughs within a sandbox environment.
• Scenario-based activities focusing on safety, evaluation, and governance.

Customization Options

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

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

Upon completing this training, participants will be capable of:

• Grasping the role of AI agents in healthcare and diagnostics.
• Creating AI models for medical image analysis and predictive diagnostics.
• Integrating AI with electronic health records (EHR) and clinical workflows.
• Ensuring compliance with healthcare regulations and ethical AI practices.

This instructor-led, live training in Italy (online or onsite) is aimed at intermediate-level healthcare professionals who wish to apply AI and AR/VR solutions for medical training, surgery simulations, and rehabilitation.

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

• Understand the role of AI in enhancing 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 Italy (online or onsite) is designed for intermediate-level data scientists and healthcare professionals seeking to apply AI for advanced healthcare applications via 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 Italy (online or onsite) is aimed at 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 Italy (online or onsite) is designed for healthcare professionals and researchers who wish to leverage ChatGPT to enhance patient care, streamline workflows, and improve healthcare outcomes.

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

• Understand the fundamentals of ChatGPT and its applications in healthcare.
• Utilize ChatGPT to automate healthcare processes and interactions.
• Provide accurate medical information and support to patients using ChatGPT.
• Apply ChatGPT for medical research and analysis.

This instructor-led, live training in Italy (online or onsite) is aimed at 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 guided, live training in Italy (online or in-person) targets medical AI developers and data scientists at the intermediate to advanced levels who wish to adapt models for clinical diagnosis, disease prediction, and patient outcome forecasting using structured and unstructured medical data.

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

• Adapting AI models to healthcare datasets, including EMRs, imaging data, and time-series information.
• Implementing transfer learning, domain adaptation, and model compression within medical applications.
• Navigating privacy concerns, bias mitigation, and regulatory compliance during model development.
• Deploying and overseeing fine-tuned models in practical healthcare settings.

Generative AI refers to technologies capable of creating new content, including text, images, and recommendations, by interpreting prompts and analyzing data.

This instructor-led live training, available online or on-site, is designed for healthcare professionals at beginner to intermediate levels who aim to leverage generative AI and prompt engineering to enhance efficiency, precision, and communication within medical settings.

Upon completing this training, participants will be able to:

• Grasp the core concepts of generative AI and prompt engineering.
• Utilize AI tools to streamline clinical, administrative, and research workflows.
• Ensure the ethical, secure, and compliant application of AI in healthcare.
• Refine prompts to achieve consistent and accurate outcomes.

Course Format

• Interactive lectures and discussions.
• Practical exercises and real-world case studies.
• Hands-on experimentation with AI tools.

Customization Options

• For a customized version of this course, please contact us to arrange your requirements.

LangGraph serves as a framework enabling the creation of stateful, multi-actor LLM applications through composable graphs that feature persistent state and precise execution control.

This instructor-led training session, available both online and onsite, targets intermediate to advanced professionals aiming to design, implement, and manage LangGraph-based financial solutions with robust governance, observability, and compliance standards.

Upon completion of this training, participants will gain the ability to:

• Create LangGraph workflows tailored to finance that align with regulatory and audit requirements.
• Incorporate financial data standards and ontologies into graph state and associated tooling.
• Establish reliability, safety, and human-in-the-loop controls for critical processes.
• Deploy, monitor, and optimize LangGraph systems to enhance performance, manage costs, and meet SLAs.

Course Format

• Interactive lectures and discussions.
• Extensive exercises and practice sessions.
• Practical implementation in a live-lab environment.

Customization Options

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

LangGraph serves as a framework for developing graph-structured applications powered by Large Language Models (LLMs), enabling features such as planning, branching, tool utilization, memory management, and controlled execution.

This instructor-led live training, available both online and onsite, is designed for developers at the beginner level, prompt engineers, and data professionals who aim to design and construct reliable, multi-step LLM workflows using LangGraph.

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

• Articulate core LangGraph concepts—including nodes, edges, and state—and understand when to apply them.
• Construct prompt chains that support branching, tool invocation, and memory retention.
• Integrate retrieval mechanisms and external APIs into graph-based workflows.
• Test, debug, and evaluate LangGraph applications to ensure reliability and safety.

Course Format

• Interactive lectures paired with facilitated discussions.
• Guided laboratory sessions and code walkthroughs conducted within a sandbox environment.
• Scenario-based exercises focusing on design, testing, and evaluation.

Customization Options

• For those interested in customizing this training, please reach out to us to make arrangements.

LangGraph serves as a framework designed for constructing stateful, multi-actor LLM applications through composable graphs that maintain persistent state and offer precise control over execution.

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

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

• Developing 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 environments with observability and cost management.

Course Format

• Interactive lectures and discussions.
• Extensive exercises and practice sessions.
• Hands-on implementation within a live lab environment.

Customization Options

• For customized training on this course, please contact us to arrange your session.

LangGraph serves as a framework for composing graph-structured workflows powered by large language models (LLMs), featuring support for branching, tool integration, memory management, and controllable execution.

This instructor-led live training, available online or onsite, is designed for intermediate-level engineers and product teams aiming to merge LangGraph’s graph logic with LLM agent loops to build dynamic, context-aware applications. Examples include customer support agents, decision trees, and information retrieval systems.

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

• Designing graph-based workflows that coordinate LLM agents, tools, and memory.
• Implementing conditional routing, retries, and fallback mechanisms for robust execution.
• Integrating retrieval systems, APIs, and structured outputs into agent loops.
• Evaluating, monitoring, and securing agent behavior to ensure reliability and safety.

Course Format

• Interactive lectures and facilitated discussions.
• Guided labs and code walkthroughs within a sandbox environment.
• Scenario-based design exercises and peer reviews.

Customization Options

• To request 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 instructor-led, live training (available online or onsite) is designed for intermediate-level marketers, content strategists, and automation developers seeking to implement dynamic, branching email campaigns and content generation pipelines using LangGraph.

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

• Design graph-structured content and email workflows incorporating conditional logic.
• Integrate LLMs, APIs, and data sources to enable automated personalization.
• Manage state, memory, and context across multi-step campaigns.
• Evaluate, monitor, and optimize workflow performance and delivery outcomes.

Format of the Course

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

Course Customization Options

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