CANN SDK for Computer Vision and NLP Pipelines Training Course

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

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

Upon completing this training, participants will be able to:

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

Course Format

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

Customization Options

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

Devstral is an open-source framework engineered for the creation and operation of coding agents capable of interacting with code repositories, developer utilities, and APIs to boost engineering productivity.

This instructor-led, live training session (available online or onsite) targets intermediate to advanced ML engineers, developer-tooling teams, and Site Reliability Engineers (SREs) seeking to design, implement, and optimize coding agents using Devstral.

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

• Establish and configure the Devstral environment for coding agent development.
• Architect agentic workflows tailored for codebase exploration and modification.
• Integrate coding agents seamlessly with developer tools and APIs.
• Adopt 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-lab environment.

Customization Options

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

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 Norway (online or onsite) is designed for beginner-level law enforcement officers who wish to transition from manual facial sketching to utilizing AI tools for developing facial recognition systems.

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

• Grasp the core principles of Artificial Intelligence and Machine Learning.
• Acquire foundational knowledge of digital image processing and its role in facial recognition.
• Build competence in employing AI tools and frameworks to construct facial recognition models.
• Obtain practical experience in developing, training, and evaluating facial recognition systems.
• Comprehend the ethical implications and adhere to best practices when deploying facial recognition technology.

Fiji is a powerful open-source image processing suite that combines ImageJ (a program designed for scientific multidimensional images) along with a comprehensive suite of plugins for scientific image analysis.

In this instructor-led live training, participants will learn how to leverage the Fiji distribution and its underlying ImageJ program to create robust image analysis applications.

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

• Use Fiji's advanced programming features and software components to extend ImageJ capabilities
• Stitch large 3D images from overlapping tiles
• Automate the update of a Fiji installation on startup using the integrated update system
• Choose from a broad selection of scripting languages to build custom image analysis solutions
• Utilize Fiji's powerful libraries, such as ImgLib, to process large bioimage datasets efficiently
• Deploy applications and collaborate effectively with other scientists on similar projects

Format of the Course

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

Course Customization Options

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

This instructor-led, live training in Norway (online or on-site) targets beginner to intermediate researchers and laboratory professionals who need to process and analyze images of histological tissues, blood cells, algae, and other biological specimens.

Upon completing this training, participants will be able to:

• Navigate the Fiji interface and leverage ImageJ’s core capabilities.
• Preprocess and enhance scientific images to improve analytical outcomes.
• Perform quantitative image analysis, including cell counting and area measurements.
• Automate routine tasks through macros and plugins.
• Tailor workflows to meet specific image analysis requirements in biological research.

LangGraph is a framework designed for constructing stateful, multi-agent LLM applications by composing graphs that maintain persistent state and allow precise control over execution flow.

This instructor-led training, available both online and on-site, is tailored for intermediate to advanced professionals aiming to design, implement, and manage LangGraph-based financial solutions with robust governance, observability, and compliance.

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

• Design financial LangGraph workflows that align with regulatory and audit requirements.
• Integrate 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 for performance, cost, and SLAs.

Course Format

• Interactive lectures and discussions.
• Extensive exercises and practical application.
• 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 for building graph-structured LLM applications that support planning, branching, tool use, memory, and controllable execution.

This instructor-led, live training (online or onsite) is aimed at beginner-level developers, prompt engineers, and data practitioners who wish 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 Large Language Models (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 integrate seamlessly with medical workflows.

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

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

• Design healthcare-specific LangGraph workflows with a focus on compliance and auditability.
• 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 within healthcare production settings.

Format of the Course

• Interactive lectures and discussions.
• Hands-on exercises using 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 serves as a framework for constructing stateful, multi-agent 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 manage LangGraph-based legal solutions with the necessary compliance, traceability, and governance controls.

Upon completing this training, participants will be capable of:

• Designing legal-specific LangGraph workflows that ensure auditability and compliance.
• Integrating legal ontologies and document standards into graph state and processing.
• Implementing guardrails, human-in-the-loop approvals, and traceable decision paths.
• Deploying, monitoring, and maintaining LangGraph services in production with observability and cost controls.

Course Format

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

Customization Options

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

LangGraph serves as a framework designed for assembling graph-structured workflows powered by large language models (LLMs), featuring support for branching, tool integration, memory management, and controlled execution.

This instructor-led live training, available both online and onsite, is tailored for intermediate-level engineers and product teams looking to merge LangGraph’s graph logic with LLM agent cycles to develop dynamic, context-aware applications. Examples include 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 procedures to ensure robust execution.
• Integrate retrieval systems, APIs, and structured outputs into agent loops.
• Evaluate, monitor, and strengthen agent behavior to ensure reliability and safety.

Course Format

• Interactive lectures and facilitated discussions.
• Guided labs and code walkthroughs conducted in a sandbox environment.
• Scenario-based design exercises and peer reviews.

Course Customization Options

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

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 live training, led by an instructor and 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 capable of:

• Designing graph-structured content and email workflows utilizing conditional logic.
• Integrating LLMs, APIs, and data sources to enable automated personalization.
• Managing state, memory, and context across multi-step campaigns.
• Evaluating, monitoring, and optimizing workflow performance and delivery outcomes.

Course Format

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

Customization Options

• For a customized training session tailored to your needs, please get in touch with us to arrange it.

Le Chat Enterprise is a private ChatOps solution that offers secure, customizable, and governed conversational AI capabilities for organizations, supporting RBAC, SSO, connectors, and enterprise app integrations.

This instructor-led, live training (online or onsite) is aimed at intermediate-level product managers, IT leads, solution engineers, and security/compliance teams who wish to deploy, configure, and govern Le Chat Enterprise in 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 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.

This instructor-led live training in Norway (online or onsite) is designed for software engineers who wish to apply Python and OpenCV 4 to deep learning projects.

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

• View, load, and classify images and videos using OpenCV 4.
• Implement deep learning in OpenCV 4 with TensorFlow and Keras.
• Run deep learning models and generate impactful reports from images and videos.

This instructor-led live training in Norway (available online or onsite) is targeted at intermediate-level professionals who wish to leverage Vision Builder AI to design, implement, and optimize automated inspection systems for SMT (Surface-Mount Technology) processes.

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

• Set up and configure automated inspections using Vision Builder AI.
• Acquire and preprocess high-quality images for analysis.
• Implement logic-based decisions for defect detection and process validation.
• Generate inspection reports and optimize system performance.