Artificial Intelligence (AI) Overview Training Course

LangGraph serves as a robust framework designed for constructing stateful, multi-agent LLM applications through composable graphs, ensuring persistent state and precise control over execution flows.

This instructor-led live training, available both online and onsite, targets 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 completing this training, participants will be equipped to:

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

Course Format

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

Customization Options

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

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.
• Apply 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 laboratory environment.

Course Customization Options

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

Devstral and Mistral are open-source artificial intelligence technologies engineered for flexible deployment, custom fine-tuning, and scalable integration.

This instructor-led live training, available either online or on-site, is designed for intermediate to advanced machine learning engineers, platform teams, and research engineers who aim to self-host, fine-tune, and govern Mistral and Devstral models within production environments.

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

• Establish and configure self-hosted environments tailored for Mistral and Devstral models.
• Apply fine-tuning techniques to enhance performance in specific domains.
• Implement version control, monitoring, and lifecycle governance mechanisms.
• Ensure security, regulatory compliance, and responsible utilization of open-source models.

Course Format

• Interactive lectures and discussions.
• Practical exercises focused on self-hosting and fine-tuning.
• Live laboratory sessions for implementing governance and monitoring pipelines.

Customization Options

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

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

This instructor-led live training, available either online or on-site, targets intermediate to advanced professionals looking to design, implement, and manage LangGraph-based financial solutions with robust governance, observability, and compliance measures.

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

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

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 for this course, please contact us to arrange details.

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

This instructor-led, live training (available online or onsite) targets beginner-level developers, prompt engineers, and data practitioners who aim 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 facilitates 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, enhancing interoperability, and developing decision-support systems that align with clinical workflows.

This instructor-led training, available both online and onsite, targets intermediate to advanced professionals seeking to design, implement, and manage LangGraph-based healthcare solutions while addressing regulatory, ethical, and operational challenges.

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

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

Course Format

• Interactive lectures and discussions.
• Hands-on exercises featuring real-world case studies.
• Implementation practice in a live-lab environment.

Course Customization Options

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

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

This instructor-led, live training (online or onsite) is aimed at intermediate-level to advanced-level professionals who wish to design, implement, and operate LangGraph-based legal solutions with the necessary compliance, traceability, and governance controls.

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

• Design legal-specific LangGraph workflows that preserve 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.
• 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.

LangGraph serves as a framework for assembling graph-structured Large Language Model (LLM) workflows that enable branching, tool utilization, memory management, and controlled execution.

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

Upon completing this training, participants will be able to:

• Design graph-based workflows that effectively coordinate LLM agents, tools, and memory.
• Implement conditional routing, retries, and fallback mechanisms to ensure robust execution.
• Integrate retrieval systems, APIs, and structured outputs into agent loops.
• Evaluate, monitor, and strengthen agent behavior to guarantee 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.

Course Customization Options

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

LangGraph serves as a graph-based orchestration framework designed to facilitate conditional, multi-step workflows involving Large Language Models (LLMs) and tools, making it ideal for automating and personalizing content pipelines.

This instructor-led live training, available both online and onsite, targets intermediate-level marketers, content strategists, and automation developers. The course focuses on implementing dynamic, branching email campaigns and content generation pipelines using LangGraph.

Upon completing this training, participants will be equipped to:

• Create graph-structured workflows for content and email, incorporating conditional logic.
• Seamlessly integrate LLMs, APIs, and data sources to enable automated personalization.
• Effectively manage state, memory, and context throughout multi-step campaigns.
• Evaluate, monitor, and optimize the performance and delivery outcomes of their workflows.

Course Format

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

Course Customization Options

• For those interested in tailored training for this course, please get in touch with us to make arrangements.

Le Chat Enterprise is a secure ChatOps platform that delivers governed, customizable, and private conversational AI capabilities for organizations. It supports Role-Based Access Control (RBAC), Single Sign-On (SSO), connectors, and integrations with enterprise applications.

This instructor-led training, available online or on-site, is designed for product managers, IT leads, solution engineers, and security/compliance teams at an intermediate level. The course focuses on deploying, configuring, and governing Le Chat Enterprise within enterprise settings.

Upon completion, participants will be equipped to:

• Deploy and configure Le Chat Enterprise securely.
• Implement RBAC, SSO, and compliance-driven controls.
• Connect Le Chat with enterprise applications and data repositories.
• Develop and execute governance and administrative playbooks for ChatOps.

Training Format

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

Customization Options

• For tailored training solutions, please get in touch with us to arrange.

Mistral represents a high-performance family of large language models specifically optimized for cost-efficient deployment at scale.

This instructor-led live training, available online or on-site, targets advanced infrastructure engineers, cloud architects, and MLOps leaders looking to design, deploy, and optimize Mistral-based architectures for maximum throughput and minimal cost.

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 without compromising performance.
• Design production-ready serving topologies suitable for enterprise workloads.

Course Format

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

Customization Options

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

Mistral AI is an open AI platform that enables teams to build and integrate conversational assistants into enterprise and customer-facing workflows.

This instructor-led, live training (online or onsite) is aimed at beginner-level to intermediate-level product managers, full-stack developers, and integration engineers who wish to design, integrate, and productize conversational assistants using Mistral connectors and integrations.

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

• Integrate Mistral conversational models with enterprise and SaaS connectors.
• Implement retrieval-augmented generation (RAG) for grounded responses.
• Design UX patterns for internal and external chat assistants.
• Deploy assistants into product workflows for real-world use cases.

Format of the Course

• Interactive lecture and discussion.
• Hands-on integration exercises.
• Live-lab development of conversational assistants.

Course Customization Options

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

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 is an open and enterprise-ready AI platform that delivers features for secure, compliant, and responsible AI deployment.

This instructor-led, live training (online or onsite) is aimed at intermediate-level compliance leads, security architects, and legal/ops stakeholders who wish to implement responsible AI practices with Mistral by leveraging privacy, data residency, and enterprise control mechanisms.

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

• Implement privacy-preserving techniques in Mistral deployments.
• Apply data residency strategies to meet regulatory requirements.
• Set up enterprise-grade controls such as RBAC, SSO, and audit logs.
• Evaluate vendor and deployment options for compliance alignment.

Format of the Course

• Interactive lecture and discussion.
• Compliance-focused case studies and exercises.
• Hands-on implementation of enterprise AI controls.

Course Customization Options

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

Mistral models are open-source artificial intelligence 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.