AI for Postgres Training Course

LangGraph is a framework designed for constructing stateful, multi-actor LLM applications using composable graphs that maintain persistent state and provide control over execution.

This instructor-led, live training (available online or on-site) targets advanced AI platform engineers, DevOps professionals for AI, and ML architects who aim to optimize, debug, monitor, and operate production-grade LangGraph systems.

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

• Design and optimize complex LangGraph topologies for improved speed, cost efficiency, and scalability.
• Enhance reliability through mechanisms such as retries, timeouts, idempotency, and checkpoint-based recovery.
• Effectively 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.

Format of the Course

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

Course Customization Options

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

Devstral is an open-source framework designed to create and run coding agents that can interact with codebases, developer tools, and APIs, thereby enhancing engineering productivity.

This instructor-led, live training (available online or on-site) is targeted at intermediate to advanced ML engineers, developer-tooling teams, and SREs who want 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 developing coding agents.
• Create agentic workflows for exploring and modifying codebases.
• Integrate coding agents with developer tools and APIs.
• Implement best practices for secure and efficient agent deployment.

Format of the Course

• Interactive lectures and discussions.
• Extensive exercises and practice sessions.
• 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 to advanced ML engineers, platform teams, and research engineers who wish to self-host, fine-tune, and manage 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 the Mistral and Devstral models.
• Apply fine-tuning techniques to enhance performance for specific domains.
• Implement versioning, monitoring, and lifecycle management practices.
• Ensure secure, compliant, and responsible use of open-source models.

Format of the Course

• Interactive lectures and discussions.
• Practical 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 is a framework designed for constructing stateful, multi-actor LLM applications using composable graphs that maintain persistent state and offer control over execution.

This instructor-led, live training (available both online and onsite) is targeted at intermediate to advanced professionals who aim to design, implement, and manage LangGraph-based financial solutions while ensuring proper governance, observability, and compliance.

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

• Create finance-specific LangGraph workflows that comply with regulatory and audit requirements.
• Incorporate financial data standards and ontologies into the graph state and tooling.
• Implement reliability, safety, and human-in-the-loop controls for critical processes.
• Deploy, monitor, and optimize LangGraph systems to meet performance, cost, and SLA requirements.

Format of the Course

• Interactive lectures and discussions.
• Ample exercises and practice sessions.
• 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 is a framework designed to build graph-structured LLM applications that support planning, branching, tool use, memory, and controllable execution.

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

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

• Understand key LangGraph concepts (nodes, edges, state) and know when to apply them.
• Create prompt chains that can branch, call tools, and maintain memory.
• Incorporate retrieval and external APIs into graph workflows.
• Test, debug, and evaluate LangGraph applications for reliability and safety.

Format of the Course

• Interactive lectures and facilitated discussions.
• Guided labs and code walkthroughs in a sandbox environment.
• Scenario-based exercises focused 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 features are essential for ensuring compliance, interoperability, and the development of decision-support systems that align with medical workflows.

This instructor-led, live training (available online or on-site) is designed for intermediate to advanced professionals who aim to design, implement, and manage LangGraph-based healthcare solutions while addressing regulatory, ethical, and operational challenges.

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

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

Format of the Course

• Interactive lectures and discussions.
• Hands-on exercises with real-world case studies.
• Practical implementation 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 using composable graphs that maintain persistent state and offer precise control over execution.

This instructor-led, live training (available both online and onsite) targets intermediate to advanced professionals who aim 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 ensure 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 lectures and discussions.
• Extensive exercises and practice sessions.
• 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 is a framework designed for creating graph-structured workflows with LLMs, supporting branching, tool integration, memory management, and controlled execution.

This instructor-led, live training (available online or on-site) is targeted at intermediate engineers and product teams who want to merge LangGraph’s graph logic with LLM agent loops to develop 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 effectively.
• Implement conditional routing, retries, and fallbacks to ensure robust execution.
• Integrate retrieval mechanisms, APIs, and structured outputs into agent loops.
• Evaluate, monitor, and enhance the reliability and safety of agent behavior.

Format of the Course

• Interactive lectures and facilitated discussions.
• Guided labs and code walkthroughs in 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 is a graph-based orchestration framework designed to facilitate conditional, multi-step workflows involving language models and tools. It is particularly useful for automating and personalizing content pipelines.

This instructor-led, live training (available both online and on-site) is tailored for intermediate-level marketers, content strategists, and automation developers who are interested in implementing dynamic, branching email campaigns and content generation pipelines using LangGraph.

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

• Create graph-structured content and email workflows that incorporate conditional logic.
• Integrate language models, APIs, and data sources for automated personalization.
• Manage state, memory, and context throughout multi-step campaigns.
• Assess, monitor, and optimize the performance and delivery outcomes of workflows.

Format of the Course

• Interactive lectures and group discussions.
• Hands-on labs for implementing email workflows and content pipelines.
• Scenario-based exercises focusing on personalization, segmentation, and branching logic.

Course Customization Options

• For a customized training session for this course, please contact us to arrange.

Le Chat Enterprise is a private ChatOps solution that offers secure, customizable, and governed 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, live training (available online or on-site) is designed for intermediate-level product managers, IT leaders, solution engineers, and security/compliance teams who want to deploy, configure, and govern Le Chat Enterprise in their enterprise environments.

By the end 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 lectures and discussions.
• Extensive exercises and practice sessions.
• 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 is a family of high-performance large language models designed for cost-effective and scalable deployment in production environments.

This instructor-led, live training (available both online and on-site) is targeted at 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.

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

• Implement scalable deployment strategies for Mistral Medium 3.
• Apply techniques such as batching, quantization, and efficient serving methods.
• Optimize inference costs while ensuring performance levels are maintained.
• Create production-ready serving architectures suitable for enterprise workloads.

Course Format

• Interactive lectures and discussions.
• Ample exercises and practical activities.
• Hands-on implementation in a live lab environment.

Customization Options for the Course

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

Mistral AI is an open artificial intelligence platform that empowers teams to develop and integrate conversational assistants into both enterprise and customer-facing workflows.

This instructor-led, live training (available online or on-site) is designed for product managers, full-stack developers, and integration engineers at beginner to intermediate levels who want to design, integrate, and commercialize conversational assistants using Mistral connectors and integrations.

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

• Integrate Mistral's conversational models with enterprise and SaaS connectors.
• Implement retrieval-augmented generation (RAG) for more accurate responses.
• Create user experience (UX) patterns for both internal and external chat assistants.
• Deploy assistants into product workflows for real-world applications.

Format of the Course

• Interactive lectures and discussions.
• Practical integration exercises.
• Live development sessions for 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 deployment in enterprise environments at a production-grade level.

This instructor-led, live training (available online or onsite) is targeted at intermediate to advanced AI/ML engineers, platform architects, and MLOps teams who aim to deploy, optimize, and secure Mistral Medium 3 for various enterprise applications.

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

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

Format of the Course

• Interactive lectures and discussions.
• Extensive exercises and practice sessions.
• 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 offers features for secure, compliant, and responsible AI deployment.

This instructor-led, live training (online or onsite) is designed for intermediate-level compliance leads, security architects, and legal/operations stakeholders who want to implement responsible AI practices with Mistral by utilizing 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 comply with regulatory requirements.
• Set up enterprise-grade controls such as role-based access control (RBAC), single sign-on (SSO), and audit logs.
• Evaluate vendor and deployment options for alignment with compliance standards.

Format of the Course

• Interactive lectures and discussions.
• Compliance-focused case studies and exercises.
• Practical 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 AI technologies that now support multimodal workflows, enhancing both language and vision tasks for enterprise and research applications.

This instructor-led, live training (available online or onsite) is designed for intermediate-level ML researchers, applied engineers, and product teams who want to develop multimodal applications using 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 into NLP pipelines.
• Design document understanding applications suitable for enterprise use cases.
• Develop vision-text search and assistive user interface functionalities.

Format of the Course

• Interactive lectures and discussions.
• 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.