Bespoke Applied Artificial Intelligence and LLM Engineering with Python Training Course

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

This instructor-led live training (available online or on-site) targets advanced AI platform engineers, AI DevOps professionals, 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 to enhance speed, reduce costs, and improve scalability.
• Ensure reliability through retries, timeouts, idempotency, and checkpoint-based recovery mechanisms.
• Debug and trace graph executions, inspect state variables, and systematically reproduce production issues.
• Instrument graphs with logs, metrics, and traces, deploy them to production, and monitor SLAs and costs effectively.

Course Format

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

Customization Options

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

Devstral is an open-source framework tailored for creating and operating coding agents capable of interacting with codebases, developer tools, and APIs to boost engineering productivity.

This instructor-led live training (available online or on-site) targets intermediate to advanced ML engineers, developer-tooling teams, and SREs who want to design, implement, and optimize coding agents using Devstral.

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

• Set up and configure Devstral for coding agent development.
• Design agentic workflows for exploring and modifying codebases.
• 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 practice.
• Hands-on implementation in a live-lab environment.

Customization Options

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

This instructor-led, live training in Vietnam (online or onsite) is aimed at intermediate-level Python developers and data analysts who wish to enhance their skills in data analysis and manipulation using Pandas and NumPy.

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

• Set up a development environment that includes Python, Pandas, and NumPy.
• Create a data analysis application using Pandas and NumPy.
• Perform advanced data wrangling, sorting, and filtering operations.
• Conduct aggregate operations and analyze time series data.
• Visualize data using Matplotlib and other visualization libraries.
• Debug and optimize their data analysis code.

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

This instructor-led live training (available online or onsite) targets 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.

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 live, instructor-led training (available online or onsite) is designed for developers who want to utilize the FARM stack (FastAPI, React, and MongoDB) to build dynamic, high-performance, and scalable web applications.

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

• Set up a development environment integrating FastAPI, React, and MongoDB.
• Comprehend the key concepts, features, and benefits of the FARM stack.
• Learn how to construct REST APIs using FastAPI.
• Learn how to design interactive applications with React.
• Develop, test, and deploy applications (covering both front end and back end) using the FARM stack.

This instructor-led live training in Vietnam (online or onsite) targets developers who wish to use FastAPI with Python to build, test, and deploy RESTful APIs more easily and quickly.

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

• Set up the necessary development environment for developing APIs with Python and FastAPI.
• Create APIs faster and easier using the FastAPI library.
• Learn how to create data models and schemas based on Pydantic and OpenAPI.
• Connect APIs to a database using SQLAlchemy.
• Implement security and authentication in APIs using the FastAPI tools.
• Build container images and deploy web APIs to a cloud server.

This instructor-led, live training in Vietnam (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 serves as a framework designed for constructing stateful, multi-agent LLM applications through composable graphs that maintain persistent state and provide granular control over execution.

This instructor-led live training, available online or on-site, targets intermediate to advanced professionals seeking to design, implement, and manage LangGraph-based financial solutions with robust governance, observability, and compliance measures.

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

• Create finance-specific LangGraph workflows that align with regulatory and audit requirements.
• Integrate financial data standards and ontologies into graph states and associated tooling.
• Establish reliability, safety mechanisms, 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 applications.
• Hands-on implementation within a live-lab environment.

Customization Options

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

LangGraph is a framework designed for constructing graph-structured Large Language Model (LLM) applications, enabling capabilities such as planning, branching, tool integration, memory management, and controlled execution.

This instructor-led live training, available both online and onsite, is tailored for beginner-level developers, prompt engineers, and data professionals who aim to design and implement reliable, multi-step LLM workflows using LangGraph.

Upon completing this training, participants will be able to:

• Articulate core LangGraph concepts—including nodes, edges, and state—and determine appropriate use cases for each.
• Create prompt chains that support branching logic, tool invocation, and persistent memory.
• Integrate retrieval mechanisms and external APIs into graph-based workflows.
• Test, debug, and evaluate LangGraph applications to ensure reliability and safety.

Course Format

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

Customization Options

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

LangGraph empowers the creation of 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 seamlessly align with medical processes.

This instructor-led, live training session (available online or onsite) is designed for intermediate to advanced-level professionals looking to design, implement, and manage LangGraph-based healthcare solutions while navigating regulatory, ethical, and operational challenges.

Upon completing this training, participants will be able to:

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

Course Format

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

Customization Options

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

LangGraph is a framework designed 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 who want to design, implement, and manage legal solutions based on LangGraph, incorporating necessary compliance, traceability, and governance controls.

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

• Create legal-specific LangGraph workflows that ensure auditability and compliance.
• Incorporate 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 lectures and discussions.
• Extensive exercises and practice sessions.
• Hands-on implementation in a live-lab environment.

Customization Options

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

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

This instructor-led live training, available online or on-site, targets intermediate engineers and product teams seeking to merge LangGraph’s graph logic with LLM agent loops. The goal is to develop dynamic, context-aware applications, including 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 mechanisms.
• Implement conditional routing, retry logic, and fallback strategies to ensure robust execution.
• Integrate retrieval systems, APIs, and structured outputs into agent loops.
• Evaluate, monitor, and secure agent behavior to guarantee reliability and safety.

Course Format

• Interactive lectures facilitated by expert instructors, accompanied by group discussions.
• Guided laboratory sessions and code walkthroughs within a sandbox environment.
• Scenario-based design exercises coupled with peer review feedback.

Customization Options for the Course

• To arrange customized training tailored to your specific needs, please reach out to us.

LangGraph serves as a graph-based orchestration framework designed to facilitate conditional, multi-step workflows involving Large Language Models (LLMs) and tools. It is particularly well-suited for automating and personalizing content pipelines.

This instructor-led training, available online or on-site, targets intermediate-level marketers, content strategists, and automation developers who aim to implement dynamic, branching email campaigns and content generation pipelines using LangGraph.

Upon completing this training, participants will be equipped to:

• Design graph-structured workflows for content and email that incorporate conditional logic.
• Integrate LLMs, APIs, and various data sources to enable automated personalization.
• Manage state, memory, and context effectively across multi-step campaigns.
• Evaluate, monitor, and optimize the performance and delivery outcomes of workflows.

Course Format

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

Customization Options

• To arrange customized training for this course, please contact us to discuss your needs.

Le Chat Enterprise is a dedicated ChatOps platform that delivers secure, customizable, and policy-driven conversational AI capabilities for enterprises. It supports 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 leaders, solution engineers, and security/compliance teams seeking to deploy, configure, and govern Le Chat Enterprise within corporate environments.

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

• Deploy and configure Le Chat Enterprise for secure operations.
• Implement RBAC, SSO, and compliance-focused controls.
• Connect Le Chat with enterprise applications and data repositories.
• Develop and execute governance and administrative playbooks for ChatOps.

Course Format

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

Customization Options

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

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.