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.

This instructor-led, live training (available online or onsite) is tailored for advanced-level AI platform engineers, AI DevOps professionals, and ML architects who aim to optimize, debug, monitor, and manage 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 reliability by implementing retries, timeouts, idempotency, and checkpoint-based recovery mechanisms.
• Debug and trace graph executions, inspect state data, and systematically reproduce production issues.
• Instrument graphs with logs, metrics, and traces; deploy to production environments; and monitor SLAs and costs.

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.

Devstral is an open-source framework engineered to facilitate the creation and execution of coding agents capable of interacting with codebases, developer utilities, and APIs to boost engineering productivity.

This instructor-led, live training (available online or onsite) targets intermediate to advanced ML engineers, developer-tooling teams, and SREs looking 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 codebase exploration and modification.
• Integrate coding agents with developer tools and APIs.
• Implement best practices for secure and efficient agent deployment.

Course Format

• Interactive lecture and discussion.
• 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.

This instructor-led, live training in India (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 ML engineers, platform teams, and research engineers looking to self-host, fine-tune, and govern Mistral and Devstral models in production environments.

Upon completing this training, participants will be able to:

• Set up and configure self-hosted environments for Mistral and Devstral models.
• Apply fine-tuning techniques to optimize domain-specific performance.
• Implement versioning, monitoring, and lifecycle governance.
• Ensure security, compliance, and responsible usage of open-source models.

Course Format

• Interactive lectures and discussions.
• Hands-on exercises focused on self-hosting and fine-tuning.
• Live-lab sessions for implementing governance and monitoring pipelines.

Course Customization Options

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

This instructor-led live training, offered online or on-site, is designed for developers who wish to utilize the FARM (FastAPI, React, and MongoDB) stack to create dynamic, high-performance, and scalable web applications.

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

• Establish the necessary development environment integrating FastAPI, React, and MongoDB.
• Comprehend the essential concepts, features, and benefits associated with the FARM stack.
• Master the process of building REST APIs with FastAPI.
• Learn techniques for designing interactive applications using React.
• Develop, test, and deploy full-stack applications (frontend and backend) leveraging the FARM stack.

This instructor-led live training in India (online or onsite) is designed for developers who want to utilize FastAPI with Python to build, test, and deploy RESTful APIs with greater ease and speed.

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

• Set up the essential development environment for building APIs with Python and FastAPI.
• Produce APIs faster and more efficiently using the FastAPI library.
• Learn to create data models and schemas based on Pydantic and OpenAPI.
• Link APIs to a database using SQLAlchemy.
• Apply security and authentication features to APIs using FastAPI utilities.
• Construct container images and deploy web APIs onto a cloud server.

This instructor-led, live training in India (online or onsite) is designed for beginner to intermediate-level 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 effectively use ImageJ’s core capabilities.
• Preprocess and enhance scientific images to improve analytical accuracy.
• Perform quantitative image analysis, including cell counting and area measurements.
• Automate routine tasks using macros and plugins.
• Tailor workflows to meet specific image analysis requirements in biological studies.

LangGraph serves as a framework for constructing stateful, multi-agent LLM applications through composable graphs, enabling persistent state management and precise execution control.

This instructor-led live training, available online or onsite, targets intermediate to advanced professionals seeking to design, implement, and manage finance solutions based on LangGraph, ensuring proper governance, observability, and compliance.

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

• Develop finance-specific LangGraph workflows that align with regulatory and audit requirements.
• Integrate financial data standards and ontologies into graph states and tooling.
• Implement reliability, safety, and human-in-the-loop controls for critical operations.
• Deploy, monitor, and optimize LangGraph systems to enhance performance, manage costs, and meet SLAs.

Course Format

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

Customization Options

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

LangGraph serves as a framework for constructing LLM applications with graph structures, enabling capabilities such as planning, branching, tool integration, memory management, and controllable execution.

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

Upon completing this training, participants will be able to:

• Articulate the fundamental concepts of LangGraph (nodes, edges, state) and identify appropriate use cases.
• Construct prompt chains that support branching, tool invocation, and memory retention.
• Incorporate retrieval mechanisms and external APIs into graph-based workflows.
• Conduct testing, debugging, and evaluation of LangGraph applications to ensure reliability and safety.

Course Format

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

Customization Options

• For personalized training arrangements for this course, please reach out to us.

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 vital for ensuring compliance, enabling interoperability, and developing decision-support systems that align with medical workflows.

This instructor-led, live training (available online or onsite) is designed for 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 in healthcare production settings.

Format of the Course

• Interactive lecture and discussion.
• Hands-on exercises with real-world case studies.
• Implementation practice in a live-lab environment.

Course Customization Options

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

LangGraph serves as a framework for constructing stateful, multi-actor LLM applications through composable graphs, enabling persistent state management and precise control over execution flow.

This instructor-led live training, available online or on-site, targets intermediate to advanced professionals aiming to design, implement, and manage LangGraph-based legal solutions, ensuring necessary compliance, traceability, and governance controls.

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

• Design LangGraph workflows tailored for legal requirements that maintain auditability and compliance.
• Integrate legal ontologies and document standards into graph states and processing logic.
• Implement guardrails, human-in-the-loop approval mechanisms, and traceable decision paths.
• Deploy, monitor, and maintain LangGraph services in production environments with robust observability and cost management.

Course Format

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

Customization Options

• For customized training arrangements, please reach out to us to coordinate.

LangGraph serves as a framework designed for assembling graph-structured LLM workflows, offering support for branching, tool integration, memory management, and controllable execution.

This instructor-led live training (available online or onsite) is tailored for intermediate-level engineers and product teams seeking 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.

Upon completing this training, participants will be equipped to:

• Design graph-based workflows that effectively coordinate LLM agents, tools, and memory.
• Implement conditional routing, retry mechanisms, and fallbacks to ensure robust execution.
• Integrate retrieval processes, APIs, and structured outputs into agent loops.
• Evaluate, monitor, and fortify agent behaviour to enhance reliability and safety.

Course Format

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

Course Customization Options

• To request customized training for this course, please get in touch with us to make arrangements.

LangGraph serves as a graph-based orchestration framework that facilitates conditional, multi-step workflows involving Large Language Models (LLMs) and tools, making it ideally suited for automating and personalizing content pipelines.

This instructor-led live training, available either online or at the participant's site, targets intermediate-level marketers, content strategists, and automation developers looking to build dynamic, branching email campaigns and content generation pipelines using LangGraph.

Upon completing this training, participants will be capable of:

• Designing graph-structured workflows for email and content that incorporate conditional logic.
• Integrating LLMs, APIs, and various data sources to achieve automated personalization.
• Managing state, memory, and context across complex, multi-step marketing campaigns.
• Evaluating, monitoring, and optimizing the performance and delivery outcomes of these workflows.

Course Format

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

Customization Options

• For those interested in tailored training for this course, please get in touch with us to arrange a customized schedule.

Le Chat Enterprise offers a private ChatOps solution, delivering secure, customizable, and governed conversational AI capabilities tailored for organizational needs. It supports Role-Based Access Control (RBAC), Single Sign-On (SSO), connectors, and seamless integration with enterprise applications.

This instructor-led live training, available online or onsite, targets intermediate-level product managers, IT leads, solution engineers, and security/compliance teams who aim to deploy, configure, and govern Le Chat Enterprise within enterprise settings.

Upon completion 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.
• Extensive 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.

Mistral is a suite of high-performance large language models, specifically engineered for cost-efficient production deployment at scale.

This instructor-led live training, available online or on-site, is designed for advanced infrastructure engineers, cloud architects, and MLOps leaders aiming to design, deploy, and optimize Mistral-based architectures to achieve maximum throughput with minimal cost.

Upon completing this training, participants will be equipped to:

• Implement scalable deployment patterns for Mistral Medium 3.
• Utilize batching, quantization, and efficient serving strategies.
• Optimize inference costs while preserving performance standards.
• Design production-ready serving topologies tailored for enterprise workloads.

Course Format

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

Customization Options

• For customized training requests, please contact us to make arrangements.