LangGraph in Healthcare: Workflow Orchestration for Regulated Environments Training Course

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

This instructor-led live training, available either online or on-site, is tailored for advanced AI platform engineers, DevOps professionals specializing in AI, and ML architects who aim to optimize, debug, monitor, and manage production-grade LangGraph systems.

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

• Design and optimize intricate LangGraph topologies to enhance speed, reduce costs, and ensure scalability.
• Enhance reliability through 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 practice.
• Hands-on implementation within a live lab environment.

Customization Options

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

Agentic AI represents a methodology where artificial intelligence systems are capable of planning, reasoning, and utilizing tools to achieve specific objectives within established boundaries.

This guided, live training session—available either online or in-person—is designed for mid-level healthcare and data professionals looking to design, assess, and oversee agentic AI solutions for both clinical and operational scenarios.

Upon completing this course, participants will be equipped to:

• Clarify the principles and limitations of agentic AI within healthcare environments.
• Construct secure agent workflows that incorporate planning, memory retention, and tool integration.
• Develop retrieval-augmented agents leveraging clinical records and knowledge repositories.
• Assess, monitor, and manage agent conduct using guardrails and human-supervised controls.

Training Format

• Engaging lectures complemented by guided discussions.
• Supervised hands-on labs and code demonstrations within a sandbox setting.
• Practical exercises focusing on safety, evaluation metrics, and governance frameworks.

Customization Options

• For tailored training solutions, please reach out to us to discuss your specific needs.

This instructor-led, live training in Turkey (online or on-site) is aimed at intermediate-level to advanced-level healthcare professionals and AI developers who wish to implement AI-driven healthcare solutions.

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

• Understand the role of AI agents in healthcare and diagnostics.
• Develop AI models for medical image analysis and predictive diagnostics.
• Integrate AI with electronic health records (EHR) and clinical workflows.
• Ensure compliance with healthcare regulations and ethical AI practices.

This instructor-led, live training in Turkey (online or onsite) is designed for intermediate-level healthcare professionals who aim to implement AI and AR/VR solutions for medical education, surgical simulations, and rehabilitation programs.

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

• Grasping how AI enhances AR/VR experiences within the healthcare domain.
• Utilizing AR/VR for surgical simulations and medical education.
• Implementing AR/VR tools for patient rehabilitation and therapy.
• Investigating the ethical and privacy issues associated with AI-enhanced medical instruments.

This instructor-led, live training in Turkey (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 live, instructor-led training in Turkey (online or on-site) is tailored for intermediate-level healthcare professionals and data scientists aiming to understand and deploy AI technologies in healthcare environments.

Upon completing this training, participants will be able to:

• Recognize primary healthcare challenges that AI solutions can resolve.
• Evaluate the influence of AI on patient safety, care quality, and medical research.
• Grasp the connection between AI technologies and healthcare business strategies.
• Apply core AI principles to real-world healthcare situations.
• Construct machine learning models for the analysis of medical data.

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

Upon completing this training, participants will be able to:

• Fine-tune AI models using healthcare datasets such as electronic medical records (EMRs), imaging data, and time-series information.
• Implement transfer learning, domain adaptation, and model compression strategies within medical applications.
• Tackle issues related to privacy, algorithmic bias, and regulatory compliance during model development.
• Deploy and oversee fine-tuned models in practical healthcare settings.

Generative AI refers to technology capable of producing new content, such as text, images, and recommendations, by leveraging prompts and underlying data.

This instructor-led live training, available both online and onsite, is designed for healthcare professionals at beginner to intermediate levels who aim to utilize generative AI and prompt engineering to enhance efficiency, precision, and communication within medical environments.

Upon completing this training, participants will be able to:

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

Course Format

• Engaging lectures paired with interactive discussions.
• Practical exercises and real-world case studies.
• Hands-on experimentation with various AI tools.

Customization Options

• To request a tailored version of this training, please contact us to make arrangements.

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

This instructor-led live training, available either online or onsite, targets intermediate to advanced professionals seeking to design, implement, and manage finance solutions based on LangGraph, ensuring proper governance, observability, and regulatory compliance.

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

• Designing LangGraph workflows tailored to financial regulations and audit requirements.
• Integrating financial data standards and ontologies into graph states and tools.
• Implementing reliability, safety measures, and human-in-the-loop controls for critical processes.
• Deploying, monitoring, and optimizing LangGraph systems to meet performance, cost, and SLA targets.

Course Format

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

Customization Options

• For requests regarding customized training for this course, please contact us to make arrangements.

LangGraph is a framework designed for constructing graph-structured Large Language Model (LLM) applications that support planning, branching, tool use, memory, and controllable execution.

This instructor-led, live training (available online or on-site) targets beginner-level developers, prompt engineers, and data practitioners who want to design and build reliable, multi-step LLM workflows using LangGraph.

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

• Explain core LangGraph concepts (nodes, edges, state) and understand when to apply them.
• Build prompt chains that branch, invoke tools, and maintain memory.
• Integrate retrieval mechanisms and external APIs into graph workflows.
• Test, debug, and evaluate LangGraph applications to ensure reliability and safety.

Format of the Course

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

Course Customization Options

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

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

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

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

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

Course Format

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

Customization Options for the Course

• To request customized training for this course, please get in touch with us to arrange details.

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

This instructor-led, live training (online or onsite) is aimed at 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.

Course Format

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

Customization Options

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

LangGraph is a graph-based orchestration framework that supports conditional, multi-step workflows involving LLMs and tools, making it ideal for automating and personalizing content pipelines.

This instructor-led live training (available online or onsite) targets intermediate-level marketers, content strategists, and automation developers looking to implement dynamic, branching email campaigns and content generation pipelines using LangGraph.

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

• Design graph-structured content and email workflows with conditional logic.
• Integrate LLMs, APIs, and data sources for 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 implementing email workflows and content pipelines.
• Scenario-based exercises on personalization, segmentation, and branching logic.

Course Customization Options

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