CANN SDK for Computer Vision and NLP Pipelines Training Course

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

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

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

• Design and optimize complex LangGraph topologies to enhance speed, reduce costs, and ensure scalability.
• Engineer system 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 environments, and monitor SLAs and operational costs.

Course Format

• Interactive lectures and discussions.
• Extensive exercises and hands-on practice.
• Real-time implementation in a live-lab environment.

Course Customization Options

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

This instructor-led, live training in Uzbekistan (online or onsite) targets beginner-level law enforcement personnel who aim to shift from manual facial sketching to leveraging AI tools for facial recognition system development.

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

• Grasping the core concepts of Artificial Intelligence and Machine Learning.
• Mastering the fundamentals of digital image processing and its role in facial recognition.
• Acquiring practical skills in employing AI tools and frameworks to construct facial recognition models.
• Gaining hands-on experience in the creation, training, and testing of facial recognition systems.
• Understanding ethical implications and industry best practices regarding facial recognition technology.

Fiji is an open-source image processing package that bundles ImageJ (an image processing program for scientific multidimensional images) and a number of plugins for scientific image analysis.

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

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

• Leverage Fiji's advanced programming features and software components to extend ImageJ
• Stitch large 3D images from overlapping tiles
• Automatically update a Fiji installation at startup using the integrated update system
• Choose from a wide range of scripting languages to develop custom image analysis solutions
• Utilise Fiji's powerful libraries, such as ImgLib, for large bioimage datasets
• Deploy their applications and collaborate with other scientists on similar projects

Course Format

• Interactive lectures and discussions
• Extensive exercises and hands-on practice
• Practical implementation in a live lab environment

Course Customisation Options

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

This instructor-led, live training in Uzbekistan (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 as composable graphs, featuring persistent state and precise control over execution flow.

This instructor-led, live training session (available online or onsite) targets intermediate to advanced professionals who aim to design, implement, and manage LangGraph-based financial solutions with appropriate governance, observability, and compliance.

Upon completing this training, participants will be able to:

• Design finance-specific 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 to enhance performance, reduce costs, and meet 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 customized training for this course, please contact us to arrange.

LangGraph is a framework designed for constructing graph-structured LLM applications that facilitate 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 aiming to design and build reliable, multi-step LLM workflows using LangGraph.

Upon completing this training, participants will be able to:

• Explain core LangGraph concepts (nodes, edges, state) and their appropriate use cases.
• Create prompt chains that branch, invoke tools, and maintain memory.
• Integrate retrieval mechanisms and external APIs into graph workflows.
• Test, debug, and evaluate LangGraph applications for reliability and safety.

Course Format

• Interactive lectures and guided discussions.
• Hands-on labs and code walkthroughs in a sandbox environment.
• Scenario-based exercises focused on design, testing, and evaluation.

Customization Options

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

LangGraph enables 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, interoperability, and the development of decision-support systems that align with established medical workflows.

This instructor-led, live training (available online or on-site) is designed for intermediate to advanced-level 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 able to:

• Design healthcare-specific LangGraph workflows with compliance and auditability as core priorities.
• Integrate LangGraph applications with medical ontologies and standards such as FHIR, SNOMED CT, and ICD.
• Apply best practices to ensure reliability, traceability, and explainability within sensitive healthcare environments.
• Deploy, monitor, and validate LangGraph applications in production healthcare settings.

Course Format

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

Course Customization Options

• To request a customized version of this training, please contact us to arrange.

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

This instructor-led, live training (available online or on-site) is tailored for intermediate to advanced professionals aiming to design, implement, and operate LangGraph-based legal solutions, ensuring robust compliance, traceability, and governance controls.

Upon completing this training, participants will be able to:

• Design legal-specific LangGraph workflows that maintain auditability and regulatory compliance.
• Integrate legal ontologies and document standards into graph state and processing logic.
• Implement guardrails, human-in-the-loop approvals, and fully traceable decision paths.
• Deploy, monitor, and maintain LangGraph services in production environments with effective observability and cost management.

Course Format

• Interactive lectures and group discussions.
• Extensive hands-on exercises and practical sessions.
• Real-time implementation within a live-lab environment.

Course Customisation Options

• To request a customised version of this training, please contact us to arrange a session.

LangGraph is a framework designed for creating graph-structured LLM workflows that support branching, tool usage, memory management, and controlled execution.

This instructor-led, live training (available online or on-site) is tailored for 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 graph-based workflows that coordinate LLM agents, tools, and memory.
• Implement conditional routing, retries, and fallback mechanisms for 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 in a sandbox environment.
• Scenario-based design exercises and peer reviews.

Course Customization Options

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

LangGraph is a graph-based orchestration framework that enables conditional, multi-step LLM and tool workflows, ideal for automating and personalizing content pipelines.

This instructor-led, live training (online or onsite) is aimed at intermediate-level marketers, content strategists, and automation developers who wish to implement dynamic, branching email campaigns and content generation pipelines using LangGraph.

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

• Design graph-structured content and email workflows with conditional logic.
• Integrate LLMs, APIs, and data sources for automated personalization.
• Manage state, memory, and context across multi-step campaigns.
• Evaluate, monitor, and optimize workflow performance and delivery outcomes.

Format of the Course

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

Course Customization Options

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

OpenCV (Open Source Computer Vision Library: http://opencv.org) is a BSD-licensed, open-source library containing hundreds of computer vision algorithms.

Target Audience

This course is designed for engineers and architects who aim to leverage OpenCV for computer vision initiatives.

This instructor-led, live training in Uzbekistan (online or onsite) is aimed at software engineers who wish to program in Python with OpenCV 4 for deep learning.

By the end 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.

Pattern Matching is a technique used to locate specified patterns within an image. It can be used to determine the existence of specified characteristics within a captured image, for example the expected label on a defective product in a factory line or the specified dimensions of a component. It is different from "Pattern Recognition" (which recognizes general patterns based on larger collections of related samples) in that it specifically dictates what we are looking for, then tells us whether the expected pattern exists or not.

Format of the Course

• This course introduces the approaches, technologies and algorithms used in the field of pattern matching as it applies to Machine Vision.

This instructor-led, live training in Uzbekistan (available online or on-site) is designed for intermediate-level professionals who aim to use Vision Builder AI to design, implement, and optimise automated inspection systems for SMT (Surface-Mount Technology) processes.

Upon completion 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 detailed analysis.
• Implement logic-based decision-making for defect detection and process validation.
• Generate comprehensive inspection reports and optimise system performance.