Artificial Intelligence - the most applied stuff - Data Analysis + Distributed AI + NLP Training Course

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

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

Upon completing this training, participants will be able to:

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

Course Format

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

Course Customization Options

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

Devstral serves as an open-source framework engineered for the creation and execution of coding agents capable of engaging with codebases, developer utilities, and APIs to elevate engineering efficiency.

This instructor-led, live training session (available online or onsite) targets intermediate to advanced ML engineers, developer-tooling teams, and SREs aiming to design, implement, and refine coding agents utilizing Devstral.

Upon completing this training, participants will possess the ability to:

• Establish and configure Devstral for coding agent development.
• Design agentic workflows tailored for codebase exploration and modification.
• Seamlessly 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 applications.
• Hands-on implementation within a live-lab environment.

Customization Options

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

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

This instructor-led, live training (available online or onsite) is tailored for intermediate 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.

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

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

Course Format

• Interactive lectures and discussions.
• Hands-on exercises focused on self-hosting and fine-tuning.
• Live-lab implementation of governance and monitoring pipelines.

Course Customization Options

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

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

This instructor-led, live training (available online or on-site) is designed for intermediate to advanced professionals seeking to design, implement, and operate LangGraph-based financial solutions with robust governance, observability, and compliance.

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

• Designing finance-specific LangGraph workflows that align with regulatory and audit requirements.
• Integrating financial data standards and ontologies into graph state and tooling.
• Implementing reliability, safety, and human-in-the-loop controls for critical processes.
• Deploying, monitoring, and optimizing LangGraph systems to meet performance, cost, and SLA objectives.

Course Format

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

Course Customization Options

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

LangGraph serves as a framework for developing graph-structured LLM applications, enabling capabilities such as planning, branching, tool usage, 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 construct 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 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-agent workflows driven by LLMs, offering precise control over execution paths and state persistence. In the healthcare sector, these capabilities are vital for ensuring compliance, interoperability, and the development of decision-support systems that align with clinical workflows.

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

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

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

Course Format

• Interactive lectures and discussions.
• Hands-on exercises utilizing real-world case studies.
• Implementation practice within a live laboratory environment.

Course Customization Options

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

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

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

Upon completing 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.

Course Format

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

Course Customization Options

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

LangGraph serves as a framework for composing graph-structured workflows involving Large Language Models (LLMs), enabling features such as branching, tool utilization, memory management, and controlled execution.

This instructor-led live training (available online or onsite) is designed for intermediate-level engineers and product teams looking to integrate LangGraph's graph logic with LLM agent loops to create dynamic, context-aware applications, including 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 to ensure robust execution.
• Integrating retrieval processes, APIs, and structured outputs into agent loops.
• Evaluating, monitoring, and enhancing 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 make arrangements.

LangGraph is a graph-based orchestration framework designed to facilitate conditional, multi-step workflows involving large language models (LLMs) and tools, making it an excellent choice for automating and personalizing content pipelines.

This instructor-led live training, available either online or onsite, targets intermediate-level marketers, content strategists, and automation developers who aim 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.

Course Format

• Interactive lectures accompanied by 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 customized training for this course, please contact us to make arrangements.

Le Chat Enterprise offers a secure, private ChatOps solution that delivers governed and customizable conversational AI capabilities tailored for organizational needs. It supports key enterprise features such as Role-Based Access Control (RBAC), Single Sign-On (SSO), connectors, and integration with enterprise applications.

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

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

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

Course Format

• Interactive lectures and discussions.
• Extensive hands-on exercises and practice sessions.
• Live-lab implementation for practical learning.

Customization Options

• For customized training arrangements, please contact us to discuss your specific requirements.

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 is an open AI platform that empowers 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 serves as an open, enterprise-ready AI platform offering capabilities designed to facilitate secure, compliant, and responsible AI deployment.

This instructor-led training, available online or onsite, is tailored for compliance leaders, security architects, and legal/operations stakeholders at an intermediate level who aim to embed responsible AI practices using Mistral through privacy preservation, data residency controls, and enterprise management mechanisms.

Upon completing this training, participants will be able to:

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

Course Format

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

Customization Options

• For customized training arrangements, please contact us directly.

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.