Building Secure and Responsible LLM Applications Training Course

LangGraph serves as a framework designed for constructing stateful, multi-actor 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 advanced AI platform engineers, AI DevOps specialists, and ML architects seeking to optimize, debug, monitor, and manage production-grade LangGraph systems.

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

• Designing and optimizing complex LangGraph topologies to enhance speed, reduce costs, and ensure scalability.
• Engineering reliability through the implementation of retries, timeouts, idempotency, and checkpoint-based recovery mechanisms.
• Debugging and tracing graph executions, inspecting states, and systematically reproducing production issues.
• Instrumenting graphs with logs, metrics, and traces; deploying to production environments; and monitoring SLAs and costs.

Course Format

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

Customization Options

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

Devstral is an open-source framework engineered to build and operate coding agents capable of interacting with codebases, developer utilities, and APIs to boost engineering productivity.

This instructor-led, live training (available online or onsite) targets intermediate to advanced ML engineers, developer-tooling teams, and SREs who aim to design, implement, and optimize coding agents using Devstral.

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

• Set up and configure Devstral for coding agent development.
• Design agentic workflows for exploring and modifying codebases.
• Integrate coding agents with developer tools and APIs.
• Implement best practices for secure and efficient agent deployment.

Course Format

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

Customization Options

• To request a customized version of this course, please contact us to arrange.

Devstral and Mistral models are open-source AI technologies designed for flexible deployment, fine-tuning, and scalable integration.

This instructor-led, live training (online or onsite) is aimed at intermediate–level to advanced–level ML engineers, platform teams, and research engineers who wish to self-host, fine-tune, and govern Mistral and Devstral models in production environments.

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

• Set up and configure self-hosted environments for Mistral and Devstral models.
• Apply fine-tuning techniques for domain-specific performance.
• Implement versioning, monitoring, and lifecycle governance.
• Ensure security, compliance, and responsible usage of open-source models.

Format of the Course

• Interactive lecture and discussion.
• Hands-on exercises in self-hosting and fine-tuning.
• Live-lab implementation of governance and monitoring pipelines.

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 through composable graphs, featuring persistent state and execution control.

This instructor-led live training, available online or onsite, is designed for intermediate to advanced professionals seeking to design, implement, and manage LangGraph-based financial solutions with appropriate governance, observability, and compliance measures.

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

• Creating finance-specific LangGraph workflows that align with regulatory and audit requirements.
• Integrating financial data standards and ontologies into graph states and tooling.
• Establishing reliability, safety, 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 application.
• Hands-on implementation within a live laboratory environment.

Customization Options

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

LangGraph is a framework designed for constructing graph-structured LLM applications that facilitate planning, branching, tool integration, memory management, and controllable execution.

This instructor-led, live training, available either online or onsite, targets beginner-level developers, prompt engineers, and data practitioners seeking to design and implement reliable, multi-step LLM workflows using LangGraph.

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

• Explain core LangGraph concepts (nodes, edges, state) and determine when to apply them.
• Construct prompt chains that incorporate branching, tool calls, 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 and facilitated discussions.
• Guided labs and code walkthroughs conducted in 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 make arrangements.

LangGraph empowers the creation of stateful, multi-actor workflows driven by Large Language Models (LLMs), offering precise control over execution paths and state management. In the healthcare sector, these capabilities are essential for ensuring compliance, enabling interoperability, and developing decision-support systems that seamlessly align with clinical workflows.

This instructor-led live training, available online or onsite, is designed for intermediate to advanced professionals seeking to design, implement, and manage LangGraph-based solutions for healthcare while navigating regulatory, ethical, and operational complexities.

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

• Design LangGraph workflows tailored to healthcare needs, prioritizing compliance and auditability.
• Integrate LangGraph applications with established medical ontologies and standards, including FHIR, SNOMED CT, and ICD.
• Apply best practices for reliability, traceability, and explainability within sensitive operational environments.
• Deploy, monitor, and validate LangGraph applications in real-world healthcare production settings.

Course Format

• Interactive lectures and discussions.
• Hands-on exercises utilizing real-world case studies.
• Practical implementation in a live laboratory environment.

Customization Options

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

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

This instructor-led live training, available online or onsite, targets intermediate to advanced professionals seeking 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:

• Developing legal-specific LangGraph workflows that ensure auditability and regulatory compliance.
• Incorporating legal ontologies and document standards into graph states and processing mechanisms.
• Establishing guardrails, human-in-the-loop approval processes, 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 application.
• Hands-on implementation within a live laboratory environment.

Customization Options

• For customized training requests, please reach out to us to arrange your specific needs.

LangGraph serves as a framework designed for composing graph-structured workflows involving Large Language Models (LLMs). It facilitates branching, tool utilization, memory management, and controllable execution flows.

This instructor-led, live training session, available both online and onsite, targets intermediate-level engineers and product teams aiming to merge LangGraph’s graph logic with LLM agent loops. The goal is to develop dynamic, context-aware applications, such as customer support agents, decision trees, and information retrieval systems.

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

• Design graph-based workflows that effectively coordinate LLM agents, tools, and memory.
• Implement conditional routing, retry mechanisms, and fallback strategies to ensure robust execution.
• Integrate retrieval processes, APIs, and structured outputs into agent loops.
• Evaluate, monitor, and reinforce agent behavior to ensure reliability and safety.

Course Format

• Interactive lectures coupled with facilitated discussions.
• Guided laboratory exercises and code walkthroughs conducted within a sandbox environment.
• Scenario-based design exercises and peer review sessions.

Course Customization Options

• For customized training arrangements, please contact us directly.

LangGraph is a graph-based orchestration framework designed to facilitate conditional, multi-step workflows involving LLMs and tools, making it highly suitable for automating and personalizing content pipelines.

This instructor-led, live training—available both online and onsite—is tailored for intermediate-level marketers, content strategists, and automation developers looking to implement dynamic, branching email campaigns and content generation pipelines using LangGraph.

Upon completing 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.

Course Format

• 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 session for this course, please contact us to arrange.

Le Chat Enterprise is a confidential ChatOps platform that delivers secure, customizable, and governed conversational AI capabilities for organizations, supporting RBAC, SSO, connectors, and enterprise application integrations.

This instructor-led, live training (available online or onsite) targets intermediate-level product managers, IT leads, solution engineers, and security/compliance teams who want to deploy, configure, and govern Le Chat Enterprise within enterprise settings.

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

• Set up and configure Le Chat Enterprise for secure deployments.
• Enable RBAC, SSO, and compliance-driven controls.
• Integrate Le Chat with enterprise applications and data stores.
• Design and implement governance and admin playbooks for ChatOps.

Format of the Course

• Interactive lecture and discussion.
• Extensive 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.

Mistral represents a high-performance family of large language models, specifically engineered for cost-effective production deployment at scale.

This instructor-led live training, available online or on-site, is designed for advanced infrastructure engineers, cloud architects, and MLOps leaders who aim to design, deploy, and optimize Mistral-based architectures to achieve maximum throughput with minimal costs.

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

• Implement scalable deployment patterns for Mistral Medium 3.
• Apply batching, quantization, and efficient serving strategies.
• Optimize inference costs while maintaining performance.
• Design production-ready serving topologies for enterprise workloads.

Course Format

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

Customization Options

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

Mistral AI operates as an open-source AI platform, empowering teams to construct and incorporate conversational assistants into both enterprise operations and customer-facing processes.

This instructor-led, live training session, available either online or onsite, targets beginner to intermediate-level product managers, full-stack developers, and integration engineers seeking to design, integrate, and commercialize conversational assistants utilizing Mistral connectors and integrations.

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

• Connect Mistral conversational models with enterprise and SaaS connectors.
• Execute retrieval-augmented generation (RAG) to ensure accurate, grounded responses.
• Create user experience (UX) patterns suitable for both internal and external chat assistants.
• Deploy assistants within product workflows to address practical, real-world scenarios.

Course Format

• Interactive lectures and discussions.
• Practical, hands-on integration exercises.
• Live laboratory development of conversational assistants.

Customization Options

• To arrange customized training for this course, please reach out to us.

Mistral Medium 3 is a high-performance, multimodal large language model designed for production-grade deployment across enterprise environments.

This instructor-led, live training (online or onsite) is aimed at intermediate-level to advanced-level AI/ML engineers, platform architects, and MLOps teams who wish to deploy, optimize, and secure Mistral Medium 3 for enterprise use cases.

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

• Deploy Mistral Medium 3 using API and self-hosted options.
• Optimize inference performance and costs.
• Implement multimodal use cases with Mistral Medium 3.
• Apply security and compliance best practices for enterprise environments.

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.

Mistral AI serves as an open, enterprise-ready AI platform designed to facilitate secure, compliant, and responsible AI deployment through its robust feature set.

This instructor-led training, available online or onsite, targets intermediate-level compliance leads, security architects, and legal/ops stakeholders who aim to implement responsible AI practices using Mistral. The course focuses on leveraging privacy safeguards, data residency controls, and enterprise management mechanisms.

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

• Deploying privacy-preserving techniques within Mistral environments.
• Applying data residency strategies to ensure regulatory compliance.
• Configuring enterprise-grade controls, including RBAC, SSO, and audit logging.
• Evaluating vendor and deployment options to align with compliance standards.

Course Format

• Interactive lectures and discussions.
• Case studies and exercises focused on compliance.
• Hands-on implementation of enterprise AI controls.

Customization Options

• For customized training arrangements, please contact us.

Mistral models are open-source AI technologies that now extend into multimodal workflows, supporting both language and vision tasks for enterprise and research applications.

This instructor-led, live training (online or onsite) is aimed at intermediate-level ML researchers, applied engineers, and product teams who wish to build multimodal applications with Mistral models, including OCR and document understanding pipelines.

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

• Set up and configure Mistral models for multimodal tasks.
• Implement OCR workflows and integrate them with NLP pipelines.
• Design document understanding applications for enterprise use cases.
• Develop vision-text search and assistive UI functionalities.

Format of the Course

• Interactive lecture and discussion.
• Hands-on coding exercises.
• Live-lab implementation of multimodal pipelines.

Course Customization Options

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