AI for Logistics and Supply: Practical No-Code Applications for the Fuel Industry Training Course

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

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

Upon completing this training, participants will be capable of:

• Designing and optimizing complex LangGraph topologies to enhance speed, reduce costs, and ensure scalability.
• Ensuring system reliability through 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 them to production; and monitoring SLAs and costs.

Course Format

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

Customization Options

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

Devstral is an open-source framework designed for building and running coding agents that can interact with codebases, developer tools, and APIs to enhance engineering productivity.

This instructor-led, live training (online or onsite) is aimed at intermediate-level to advanced-level ML engineers, developer-tooling teams, and SREs who wish to design, implement, and optimize coding agents using Devstral.

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

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

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.

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.

This instructor-led, live training in Sweden (online or onsite) is aimed at beginner-level to intermediate-level researchers and laboratory professionals who wish to process and analyze images related to histological tissues, blood cells, algae, and other biological samples.

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

• Navigate the Fiji interface and utilize ImageJ’s core functions.
• Preprocess and enhance scientific images for better analysis.
• Analyze images quantitatively, including cell counting and area measurement.
• Automate repetitive tasks using macros and plugins.
• Customize workflows for specific image analysis needs in biological research.

LangGraph serves as a framework for constructing stateful, multi-agent LLM applications through composable graphs, enabling persistent state management and precise control over execution flow.

This instructor-led training, available either online or onsite, is tailored for intermediate to advanced professionals seeking to design, implement, and manage LangGraph-based financial solutions while adhering to strict governance, observability, and compliance standards.

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

• Design LangGraph workflows specific to finance that align with regulatory and audit requirements.
• Integrate financial data standards and ontologies into graph states and associated tooling.
• Implement robust reliability, safety measures, and human-in-the-loop controls for critical processes.
• Deploy, monitor, and optimize LangGraph systems to ensure optimal performance, cost-efficiency, and SLA adherence.

Course Format

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

Customization Options

• For customized training arrangements, please contact us directly.

LangGraph serves as a framework designed for constructing LLM applications that leverage graph structures, enabling capabilities such as planning, branching, tool utilization, memory management, and controlled execution.

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

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

• Explaining fundamental LangGraph concepts (nodes, edges, state) and determining appropriate use cases.
• Developing prompt chains that support branching, tool invocation, and memory retention.
• Integrating retrieval mechanisms and external APIs into graph-based workflows.
• Testing, debugging, and evaluating LangGraph applications to ensure reliability and safety.

Course Format

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

Course Customization Options

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

LangGraph empowers the creation of stateful, multi-actor workflows driven by LLMs, offering precise control over execution paths and state persistence. In the healthcare sector, these capabilities are essential for ensuring compliance, enabling interoperability, and developing decision-support systems that seamlessly integrate with medical 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 healthcare solutions while effectively addressing regulatory, ethical, and operational challenges.

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

• Design healthcare-specific LangGraph workflows with compliance and auditability at the forefront.
• Integrate LangGraph applications with medical ontologies and standards such as FHIR, SNOMED CT, and ICD.
• Apply best practices for reliability, traceability, and explainability within sensitive environments.
• Deploy, monitor, and validate LangGraph applications in healthcare production settings.

Format of the Course

• Interactive lectures and discussions.
• Hands-on exercises utilizing real-world case studies.
• Implementation practice 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 designed for constructing stateful, multi-actor LLM applications as composable graphs featuring persistent state and precise control over execution.

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

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

• Design legal-specific LangGraph workflows that maintain auditability and compliance.
• Integrate legal ontologies and document standards into graph state and processing.
• Implement guardrails, human-in-the-loop approvals, and traceable decision paths.
• Deploy, monitor, and maintain LangGraph services in production with observability and cost controls.

Format of the Course

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

Course Customization Options

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

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

This instructor-led live training, available both online and onsite, targets intermediate-level engineers and product teams. Participants will learn to combine LangGraph’s graph logic with LLM agent loops to develop dynamic, context-aware applications, including 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 data retrieval, external APIs, and structured outputs into agent loops.
• Evaluate, monitor, and harden agent behavior to ensure reliability and safety.

Course Format

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

Course Customization Options

• To request a customized version of this training, 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 on-site) targets intermediate-level marketers, content strategists, and automation developers who aim to implement dynamic, branching email campaigns and content generation pipelines using LangGraph.

Upon completing this training, participants will be capable of:

• Designing graph-structured workflows for content and email that incorporate conditional logic.
• Integrating LLMs, APIs, and data sources to enable automated personalization.
• Managing state, memory, and context throughout multi-step campaigns.
• Evaluating, monitoring, and optimizing 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

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

Le Chat Enterprise offers a private ChatOps solution that enables organizations to utilize secure, customizable, and governed conversational AI capabilities. The platform supports RBAC, SSO, connectors, and integrations with enterprise applications.

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

Upon completing this training, participants will be able to:

• Configure Le Chat Enterprise for secure deployment.
• Implement RBAC, SSO, and compliance-driven controls.
• Connect Le Chat with enterprise applications and data repositories.
• Develop and execute governance and administration playbooks for ChatOps.

Course Format

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

Customization Options

• For tailored training options, please contact us to arrange.

Mistral is a high-performance family of large language models optimized for cost-effective production deployment at scale.

This instructor-led, live training (online or onsite) is aimed at advanced-level infrastructure engineers, cloud architects, and MLOps leads who wish to design, deploy, and optimize Mistral-based architectures for maximum throughput and minimum cost.

By the end 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.

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 offers an open-source AI platform that empowers teams to construct and embed conversational assistants within both enterprise operations and customer-facing processes.

This instructor-led training, available either online or on-site, is tailored for beginner to intermediate product managers, full-stack developers, and integration engineers looking to design, integrate, and commercialize conversational assistants using Mistral's connectors and integrations.

Upon completing this training, participants will be equipped to:

• Connect Mistral conversational models with enterprise and SaaS connectors.
• Implement retrieval-augmented generation (RAG) to ensure accurate, grounded responses.
• Develop UX patterns for both internal and external chat assistants.
• Deploy assistants into product workflows to address real-world use cases.

Course Format

• Interactive lectures and discussions.
• Practical integration exercises.
• Live lab sessions for developing conversational assistants.

Customization Options

• To arrange customized training for this course, please contact us to discuss your needs.

Mistral Medium 3 is a high-performance, multimodal large language model crafted for robust, production-grade deployment within enterprise settings.

This instructor-led training session, available online or on-site, targets intermediate to advanced AI/ML engineers, platform architects, and MLOps teams seeking to deploy, optimize, and secure Mistral Medium 3 for enterprise applications.

Upon completing this training, participants will be equipped to:

• Deploy Mistral Medium 3 via API or self-hosted solutions.
• Enhance inference performance while managing costs.
• Execute multimodal use cases using Mistral Medium 3.
• Apply security and compliance best practices tailored for enterprise environments.

Course Format

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

Customization Options

• For customized training arrangements, please reach out to us.

Mistral AI offers an open, enterprise-grade AI platform designed to facilitate the secure, compliant, and responsible deployment of AI technologies.

This instructor-led live training (available online or on-site) is designed for intermediate-level compliance officers, security architects, and legal or operations stakeholders who aim to integrate 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 equipped to:

• Deploy privacy-preserving techniques within Mistral environments.
• Apply data residency strategies to ensure regulatory compliance.
• Configure enterprise-grade controls, including RBAC, SSO, and audit logging.
• Assess vendor and deployment choices to align with compliance standards.

Course Format

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

Customization Options

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