Generative AI in Education: Enhancing Personalized Learning Training Course

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

This instructor-led, live training (available both online and on-site) targets advanced-level AI platform engineers, DevOps professionals for AI, and ML architects who aim to optimize, debug, monitor, and manage 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.
• Ensure reliability by implementing retries, timeouts, idempotency, and checkpoint-based recovery mechanisms.
• Debug and trace graph executions, inspect state, and systematically replicate production issues.
• Instrument graphs with logs, metrics, and traces, deploy them to production, and monitor SLAs and costs effectively.

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.

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

This instructor-led, live training (available both online and on-site) is targeted at intermediate to advanced ML engineers, developer-tooling teams, and SREs who aim 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.
• Apply best practices for secure and efficient agent deployment.

Format of the Course

• Interactive lectures and discussions.
• Plenty of 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 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 to enhance performance for specific domains.
• Implement versioning, monitoring, and lifecycle governance practices.
• Ensure the security, compliance, 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.

This instructor-led, live training in Norway (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 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 with proper governance, observability, and compliance.

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

• Design finance-specific LangGraph workflows that align with regulatory and audit requirements.
• Incorporate financial data standards and ontologies into graph state and tooling.
• Implement reliability, safety, and human-in-the-loop controls for critical processes.
• Deploy, monitor, and optimize LangGraph systems to ensure performance, cost efficiency, and service level agreements (SLAs).

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 LLM applications that support planning, branching, tool integration, memory management, and controllable execution.

This instructor-led, live training (available online or on-site) is tailored for beginner-level developers, prompt engineers, and data professionals 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 their appropriate use cases.
• Create prompt chains that can branch, call tools, and maintain memory.
• Incorporate retrieval mechanisms 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 focusing 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 processes.

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.
• Practical exercises with real-world case studies.
• Hands-on 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 creating stateful, multi-actor LLM applications as composable graphs with persistent state and precise execution control.

This instructor-led, live training (available both online and onsite) is targeted at intermediate to advanced professionals who aim to design, implement, and operate LangGraph-based legal solutions while ensuring 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 the graph state and processing.
• Implement guardrails, human-in-the-loop approvals, and traceable decision-making paths.
• Deploy, monitor, and maintain LangGraph services in a production environment with observability and cost management.

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-level engineers and product teams who aim to integrate 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 workflows based on graphs that coordinate LLM agents, tools, and memory.
• Implement conditional routing, retries, and fallback mechanisms for robust execution.
• Integrate retrieval functions, 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 that facilitates conditional, multi-step workflows involving language models and tools. It is particularly suited for automating and personalizing content pipelines.

This instructor-led, live training (available online or on-site) is designed for intermediate-level marketers, content strategists, and automation developers who want to implement dynamic, branching email campaigns and content generation processes using LangGraph.

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

• Design 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 across multi-step campaigns effectively.
• Evaluate, 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

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

Le Chat Enterprise is a private ChatOps solution designed to offer secure, customizable, and governed conversational AI capabilities for organizations. It supports features such as 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 tailored for intermediate-level product managers, IT leaders, solution engineers, and security/compliance teams who aim to deploy, configure, and manage Le Chat Enterprise in their organizational 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 lecture and discussion sessions.
• Extensive exercises and practice 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.

Mistral is a high-performance family of large language models designed for cost-effective and scalable deployment in production environments.

This instructor-led, live training (available online or on-site) is tailored for advanced-level infrastructure engineers, cloud architects, and MLOps leads 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.
• Utilize batching, quantization, and efficient serving techniques.
• Optimize inference costs without compromising performance.
• Create production-ready serving architectures for enterprise workloads.

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.

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

This instructor-led, live training (available both online and on-site) targets intermediate to advanced AI/ML engineers, platform architects, and MLOps teams who are looking to deploy, optimize, and secure Mistral Medium 3 for enterprise applications.

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

• Deploy Mistral Medium 3 using API integration or self-hosted solutions.
• 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 hands-on practice.
• Practical 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 artificial intelligence platform that offers features for secure, compliant, and responsible AI deployment.

This instructor-led, live training (available online or on-site) is designed for intermediate-level compliance leads, security architects, and legal/operations stakeholders who wish to implement responsible AI practices using Mistral. The focus will be on leveraging privacy, data residency, and enterprise control mechanisms.

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

• Implement privacy-preserving techniques in their 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 to ensure compliance alignment.

Format of the Course

• Interactive lecture and discussion sessions.
• 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 AI technologies that now support multimodal workflows, enabling both language and vision tasks for enterprise and research applications.

This instructor-led, live training (available online or on-site) 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 with natural language processing (NLP) pipelines.
• Design document understanding applications 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.