Online or onsite, instructor-led live Large Language Models (LLMs) training courses demonstrate through interactive hands-on practice how to use Large Language Models for various natural language tasks.
LLMs training is available as "online live training" or "onsite live training". Online live training (aka "remote live training") is carried out by way of an interactive, remote desktop. Lyon onsite live Large Language Models (LLMs) trainings can be carried out locally on customer premises or in NobleProg corporate training centers.
NobleProg also offers bespoke Large Language Models (LLMs) consultancy services in Lyon. Our consultants have helped hundreds of clients around the world get unstuck. Our clients value our highly-personalized consulting approach and find consulting to be well-suited for complex long-term projects, short-term projects requiring niche expertise, urgent problem fixing, critical knowledge transfer, and team coaching and support. To learn more about our past consultancy engagements, see consultancy case studies.
If instead you need people for continuous projects, NobleProg can support your organisation with a full range of staff. Whether your needs are for medium-term or long-term assignments, entry-level or highly-skilled expertise, single-person or multi-person personnel, our interim staffing / staff augmentation solutions can provide you with the talent needed to complete your most challenging projects. Contact us for more information.
NobleProg -- Your Local Training Provider
Lyon, Swisslife Tower
NobleProg Lyon, 10 Place Charles Béraudier, Lyon, france, 69000
Located 200 meters far from the train station TGV, Swisslife Tower is today the most representative building of this quarter of Lyon. The Business Center offers you a perfect location for your training.
Gares TGV
100meters from Gare TGV Part-Dieu , porte du Rhône Exit
Aéroport
30 minutes from Lyon Saint Exupéry (Satolas)
Rhône Express from Saint Exupéry airport (Terminus Gare part-Dieu)
This instructor-led, live training in Lyon (online or onsite) is aimed at senior management professionals who wish to understand what LLMs are, explore their potential impact on business operations, and evaluate practical uses of AI tools such as ChatGPT, Microsoft Copilot, or Grok for real-world tasks like content creation, data summarization, and decision support.
By the end of this training, participants will be able to:
Understand what LLMs are and how tools like ChatGPT and Copilot function.
Use prompt techniques to get practical, reliable results from LLMs.
Evaluate real use cases such as email drafting, summarizing documents, and productivity automation.
Identify investment opportunities and strategic applications for AI adoption.
This instructor-led, live training in Lyon (online or onsite) is aimed at senior management teams who wish to understand the strategic value of LLMs and enterprise AI tools. Participants will explore how to integrate these tools into high-level workflows, draft better prompts, and evaluate opportunities for increased productivity and ROI through AI adoption.
By the end of this training, participants will be able to:
Understand how LLMs function and how tools like ChatGPT and Copilot apply them.
Use prompt-based interactions to automate and accelerate tasks.
Apply AI tools to real scenarios such as email drafting, report summarization, and agreement review.
Evaluate strategic benefits, limitations, and licensing considerations for LLM adoption.
This instructor-led, live training in Lyon (online or onsite) is aimed at intermediate-level to advanced-level AI researchers, data scientists, and developers who wish to understand, fine-tune, and implement Meta AI's Large Language Models for various NLP applications.
By the end of this training, participants will be able to:
Understand the architecture and functioning of Meta AI's Large Language Models.
Set up and fine-tune Meta AI LLMs for specific use cases.
Implement LLM-based applications such as text summarization, chatbots, and sentiment analysis.
Optimize and deploy large language models efficiently.
This instructor-led, live training in Lyon (online or onsite) is designed for intermediate-level AI professionals, business analysts, and technology leaders who wish to understand the principles of generative AI and the applications of LLMs in business settings. Participants will learn about transformers, prompt engineering, and ethical considerations in deploying these models for real-world solutions.
By the end of this training, participants will be able to:
Understand the underlying principles of generative AI and large language models.
Implement and fine-tune LLMs for specific business applications.
Apply prompt engineering techniques for optimal model outputs.
Recognize ethical considerations and manage risks in LLM deployment.
This instructor-led, live training in Lyon (online or onsite) is aimed at intermediate-level AI professionals and ethicists, data scientists and engineers, and policy makers and stakeholders who wish to understand and navigate the ethical landscape of LLMs.
By the end of this training, participants will be able to:
Identify ethical issues and challenges associated with LLMs.
Apply ethical frameworks and principles to LLM deployment.
Assess the societal impact of LLMs and mitigate potential risks.
Develop strategies for responsible AI development and usage.
This instructor-led, live training in Lyon (online or onsite) is designed for intermediate NLP practitioners, data scientists, content creators, translators, and global businesses seeking to utilize LLMs for language translation and multilingual content creation.
By the end of this training, participants will be able to:
Understand the principles of cross-lingual learning and translation with LLMs.
Implement LLMs for translating content between various languages.
Create and manage multilingual datasets for training LLMs.
Develop strategies for maintaining consistency and quality in translation.
This instructor-led, live training in Lyon (online or onsite) is designed for intermediate-level financial analysts, data scientists, and investment professionals seeking to leverage LLMs for financial market analysis and prediction.
Upon completion of this training, participants will be able to:
Grasp how LLMs are applied in financial market analysis.
Utilize LLMs to analyze financial news, reports, and data for actionable market insights.
Create predictive models for stock prices, market trends, and economic indicators.
Incorporate insights from LLMs into investment decision-making workflows.
This instructor-led, live training in Lyon (online or onsite) is designed for intermediate-level environmental scientists, researchers, data analysts, and policy makers or advocates seeking to use LLMs for environmental modeling and analysis.
By the end of this training, participants will be able to:
Understand the application of LLMs in environmental science.
Utilize LLMs to analyze and model environmental data.
Interpret LLM outputs for environmental impact assessments.
Communicate findings effectively to inform policy and conservation efforts.
This instructor-led, live training in Lyon (online or onsite) is designed for intermediate-level VR and AR developers, game designers, and AI engineers who wish to incorporate LLMs into VR and AR applications to create more engaging and responsive environments.
By the end of this training, participants will be able to:
Understand the role of LLMs in creating immersive VR and AR experiences.
Develop VR and AR applications that utilize LLMs for interactive dialogues and content creation.
Integrate LLMs with VR and AR development tools for enhanced user engagement.
Apply best practices for designing AI-driven narratives and interactions in virtual spaces.
This instructor-led, live training in Lyon (online or onsite) is designed for intermediate-level data scientists, machine learning engineers, and software developers who wish to apply Large Language Models (LLMs) to multimodal data for advanced AI applications.
Upon completion of this training, participants will be able to:
Grasp the fundamental principles of multimodal learning using LLMs.
Deploy LLMs to process and analyze text, image, and audio data.
Develop applications that capitalize on the synergies of multimodal data integration.
This instructor-led, live training in Lyon (online or onsite) is designed for intermediate-level cybersecurity professionals and data scientists who aim to leverage LLMs to enhance cybersecurity measures and threat intelligence.
By the end of this training, participants will be able to:
Understand the role of LLMs in cybersecurity.
Implement LLMs for threat detection and analysis.
Utilize LLMs for security automation and response.
Integrate LLMs with existing security infrastructure.
This instructor-led, live training in Lyon (online or onsite) targets intermediate-level data scientists and business analysts who wish to utilize large language models (LLMs) to forecast trends and behaviors in various industries.
By the end of this training, participants will be able to:
Understand the fundamentals of LLMs and their role in predictive analytics.
Implement LLMs to analyze and forecast data in various industries.
Evaluate the effectiveness of predictive models using LLMs.
Integrate LLMs with existing data processing pipelines.
This instructor-led, live training in Lyon (online or onsite) is tailored for intermediate-level data scientists seeking to develop a comprehensive understanding and practical expertise in both Large Language Models (LLMs) and Reinforcement Learning (RL).
Upon completion of this training, participants will be capable of:
Grasping the components and functionality of transformer models.
Optimizing and fine-tuning LLMs for specific tasks and applications.
Comprehending the core principles and methodologies of reinforcement learning.
Understanding how reinforcement learning techniques can enhance the performance of LLMs.
This instructor-led, live training in Lyon (online or onsite) is designed for intermediate-level content creators, marketers, and educational technologists who want to harness the power of LLMs to generate high-quality, diverse, and engaging content across various fields.
By the end of this training, participants will be able to:
Understand the capabilities of LLMs and their application in content generation.
Set up and use LLMs for generating various types of content.
Apply best practices for prompting and fine-tuning LLMs to produce desired outputs.
Evaluate the quality of AI-generated content and refine it for specific audiences.
Explore advanced techniques for creative and multi-modal content generation with LLMs.
This instructor-led, live training in Lyon (online or onsite) is designed for educators, EdTech professionals, and researchers of varying expertise who wish to utilize LLMs to craft personalized educational experiences.
By the conclusion of this training, participants will be able to:
Understand the architecture and capabilities of LLMs.
Identify opportunities for personalization in educational content using LLMs.
Design adaptive learning platforms that utilize LLMs for content personalization.
Implement LLM-driven strategies for enhancing student engagement and learning outcomes.
Evaluate the effectiveness of LLMs in educational settings and make data-driven decisions for
This instructor-led, live training in Lyon (available online or onsite) is designed for intermediate-level machine learning practitioners and AI developers who wish to customize and deploy open-weight models such as LLaMA, Mistral, and Qwen for specific business or internal applications.
Upon completion of this training, participants will be capable of:
Gaining a comprehensive understanding of the open-source LLM ecosystem and the distinctions between various models.
Preparing datasets and configuring fine-tuning parameters for models like LLaMA, Mistral, and Qwen.
Executing fine-tuning pipelines using Hugging Face Transformers and PEFT.
Evaluating, saving, and deploying fine-tuned models within secure environments.
This instructor-led, live training in Lyon (online or onsite) is designed for beginner to intermediate software developers and data scientists who wish to implement LLMs in speech recognition and synthesis systems.
By the end of this training, participants will be able to:
Understand the role of LLMs in speech technologies.
Implement LLMs for accurate speech recognition and natural-sounding speech synthesis.
Integrate LLMs with speech recognition engines and speech synthesizers.
Evaluate and improve the performance of speech systems using LLMs.
Stay informed about current trends and future directions in speech technologies.
This instructor-led, live training in Lyon (online or onsite) is designed for beginner to intermediate-level customer support and IT professionals who wish to implement LLMs to create responsive and intelligent customer support chatbots.
By the end of this training, participants will be able to:
Understand the fundamentals and architecture of Large Language Models (LLMs).
Design and integrate LLMs into customer support systems.
Enhance the responsiveness and user experience of chatbots.
Address ethical considerations and ensure compliance with industry standards.
Deploy and maintain an LLM-based chatbot for real-world applications.
This instructor-led, live training in Lyon (online or on-site) targets intermediate data scientists and AI engineers who aim to fine-tune large language models more affordably and efficiently using techniques such as LoRA, Adapter Tuning, and Prefix Tuning.
By the end of this training, participants will be able to:
Understand the theoretical basis of parameter-efficient fine-tuning approaches.
Implement LoRA, Adapter Tuning, and Prefix Tuning using Hugging Face PEFT.
Compare the performance and cost trade-offs of PEFT methods against full fine-tuning.
Deploy and scale fine-tuned LLMs with reduced compute and storage requirements.
This instructor-led, live training in Lyon (online or onsite) is aimed at intermediate-level to advanced-level machine learning engineers, AI developers, and data scientists who wish to learn how to use QLoRA to efficiently fine-tune large models for specific tasks and customizations.
By the end of this training, participants will be able to:
Understand the theory behind QLoRA and quantization techniques for LLMs.
Implement QLoRA in fine-tuning large language models for domain-specific applications.
Optimize fine-tuning performance on limited computational resources using quantization.
Deploy and evaluate fine-tuned models in real-world applications efficiently.
This instructor-led, live training in Lyon (online or onsite) targets intermediate-level data and marketing professionals who aim to apply LLMs to analyze and interpret public sentiment from various text sources, such as social media posts, product reviews, and customer feedback.
By the end of this training, participants will be able to:
Grasp the principles of sentiment analysis and its application using LLMs.
Preprocess and prepare datasets for sentiment analysis.
Train and fine-tune LLMs to accurately reflect sentiment in text.
Analyze sentiment in real-time from social media and other text sources.
Integrate sentiment analysis findings into business strategies and decision-making processes.
This instructor-led, live training in Lyon (online or onsite) is designed for intermediate-level software developers and technical writers who want to leverage LLMs to streamline their coding workflows and produce detailed, comprehensive documentation.
Upon completion of this training, participants will be able to:
Grasp the role of LLMs in automating code generation and software documentation.
Utilize LLMs to create accurate and efficient code snippets and documentation.
Integrate LLMs into their software development lifecycle to enhance productivity.
Maintain high-quality documentation standards using automated tools.
Address ethical considerations and best practices for using AI in software development.
This instructor-led, live training in Lyon (online or onsite) is designed for intermediate-level business professionals and data analysts seeking to leverage the power of LLMs to extract valuable business insights.
By the end of this training, participants will be able to:
Understand the fundamentals and applications of LLMs in the context of business intelligence.
Apply LLMs to analyze large datasets and extract meaningful insights.
Integrate LLM-driven analytics into strategic business decision-making processes.
Evaluate the ethical considerations and best practices for using LLMs in business.
Anticipate future trends in AI and prepare for the evolving landscape of business intelligence.
This instructor-led, live training in Lyon (online or on-site) is designed for intermediate to advanced developers and data scientists who wish to master LlamaIndex for creating innovative LLM-powered applications.
By the end of this training, participants will be able to:
Install and configure LlamaIndex for use with LLMs.
Index and query custom datasets using LlamaIndex to enhance LLM functionality.
Design and develop sophisticated applications that utilize LlamaIndex and LLMs.
Understand and apply best practices for working with LLMs and LlamaIndex.
Navigate the ethical considerations involved in deploying LLM-powered applications.
This instructor-led, live training in Lyon (online or onsite) is designed for intermediate-level AI researchers, machine learning professionals, and data scientists who intend to use LlamaIndex to enhance AI model capabilities, making them more accurate and reliable for various applications.
By the end of this training, participants will be able to:
Understand the principles and components of LlamaIndex.
Ingest and structure data for use with LLMs.
Implement context augmentation to improve AI model performance.
Integrate LlamaIndex into existing AI systems and workflows.
This instructor-led, live training in Lyon (available online or onsite) is targeted at intermediate-level professionals aiming to leverage prompt engineering and few-shot learning to enhance LLM performance for real-world applications.
Upon completion of this training, participants will be able to:
Understand the principles of prompt engineering and few-shot learning.
Design effective prompts for various NLP tasks.
Leverage few-shot techniques to adapt LLMs with minimal data.
Optimize LLM performance for practical applications.
LangGraph is a framework designed for constructing stateful, multi-actor LLM applications as composable graphs, featuring persistent state and precise execution control.
This instructor-led live training, available both online and onsite, targets intermediate to advanced professionals who aim to design, implement, and manage LangGraph-based legal solutions, ensuring the necessary compliance, traceability, and governance controls are in place.
Upon completion of this training, participants will be able to:
Design legal-specific LangGraph workflows that maintain auditability and compliance.
Integrate 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 environments with observability and cost controls.
Course Format
Interactive lectures and discussions.
Extensive exercises and practice sessions.
Hands-on implementation within a live laboratory environment.
Course Customization Options
To request a customized training for this course, please contact us to arrange.
This instructor-led, live training (online or onsite) targets advanced-level engineers, AI specialists, and localization leaders who want to implement large language model (LLM) systems for automated translation, quality assessment, and enterprise governance.
Upon completion of this training, participants will be able to:
Create enterprise-grade LLM localization pipelines that integrate both open and proprietary models.
Set up automated QA workflows and quality metrics to ensure translation consistency.
Establish governance and approval frameworks for multilingual content production.
Deploy scalable, auditable LLM-based localization systems within secure environments.
AI for SQL involves applying artificial intelligence and large language models (LLMs) to automate, optimize, and improve how SQL queries are generated, executed, and interpreted within enterprise data environments.
This instructor-led, live training (available online or onsite) targets intermediate-level data engineers and technical leads who want to integrate AI capabilities into SQL workflows to enable natural language querying, intelligent optimization, and automated data analysis.
By the end of this training, participants will be able to:
Integrate LLMs such as GPT, DeepSeek, LLaMA, Qwen, and Mistral into SQL environments.
Build natural-language-to-SQL pipelines for conversational data access.
Implement AI-driven query optimization and error detection.
Design secure, auditable AI-SQL workflows for enterprise use.
Format of the Course also allows for the evaluation of participants.
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.
LangGraph serves as a framework designed for constructing stateful, multi-agent Large Language Model (LLM) applications through composable graphs, featuring persistent state and precise execution control.
This instructor-led, live training—available either online or onsite—is tailored for intermediate to advanced professionals seeking to design, implement, and manage LangGraph-based financial solutions that adhere to strict governance, observability, and compliance standards.
Upon completion of this training, participants will be equipped to:
Design finance-specific LangGraph workflows that align with regulatory and audit requirements.
Integrate financial data standards and ontologies into graph states and associated tooling.
Implement reliability, safety, and human-in-the-loop controls essential for critical processes.
Deploy, monitor, and optimize LangGraph systems to ensure optimal performance, cost-efficiency, and adherence to Service Level Agreements (SLAs).
Course Format
Interactive lectures and discussions.
Extensive exercises and practical applications.
Hands-on implementation within a live laboratory environment.
Customization Options
To request customized training for this course, please contact us to arrange your specific needs.
Vertex AI offers robust tools for constructing multimodal LLM workflows that seamlessly integrate text, audio, and image data into a unified pipeline. By leveraging long context window support and Gemini API parameters, it facilitates the development of sophisticated applications focused on planning, reasoning, and cross-modal intelligence.
This instructor-led live training (available online or onsite) is designed for intermediate to advanced practitioners aiming to design, build, and optimize multimodal AI workflows within Vertex AI.
Upon completion of this training, participants will be capable of:
Utilizing Gemini models to handle multimodal inputs and outputs.
Implementing long-context workflows to address complex reasoning tasks.
Designing pipelines that effectively combine text, audio, and image analysis.
Optimizing Gemini API parameters to enhance performance and cost efficiency.
Course Format
Interactive lectures and discussions.
Hands-on labs focused on multimodal workflows.
Project-based exercises addressing real-world multimodal use cases.
Customization Options
To request a tailored version of this course, please reach out to us to arrange details.
LangGraph facilitates stateful, multi-actor workflows driven by Large Language Models (LLMs), offering precise control over execution paths and state persistence. These capabilities are essential in healthcare for ensuring compliance, enabling interoperability, and developing decision-support systems that align with clinical workflows.
This instructor-led, live training (available online or onsite) is designed for intermediate to advanced professionals looking 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 LangGraph workflows tailored to healthcare, ensuring 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 in healthcare production settings.
Course Format
Interactive lectures and discussions.
Hands-on exercises using real-world case studies.
Practical implementation in a live-lab environment.
Customization Options
To request a customized version of this training, please contact us to arrange.
This instructor-led live training (available online or on-site) is tailored for intermediate-level AI developers and localization engineers who wish to design scalable, automated translation pipelines using both proprietary and open-source LLMs.
Upon completion of this training, participants will be able to:
Design and deploy translation workflows using modern LLM frameworks and APIs.
Integrate open-source and commercial models into scalable translation systems.
Optimize translation quality through fine-tuning, prompt engineering, and automation.
Implement cost-efficient and compliant translation infrastructure for enterprise environments.
LangGraph serves as a framework for developing stateful, multi-agent LLM applications by composing graphs with persistent state and execution control.
This instructor-led live training, available online or onsite, is designed for advanced AI platform engineers, AI DevOps specialists, 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.
Build reliability through retries, timeouts, idempotency, and checkpoint-based recovery mechanisms.
Debug and trace graph executions, inspect states, and systematically reproduce production issues.
Instrument graphs with logs, metrics, and traces; deploy to production; and monitor SLAs and costs.
Course Format
Interactive lectures and discussions.
Extensive exercises and practice sessions.
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 Lyon (online or onsite) is designed for intermediate-level developers who want to learn how to utilize generative AI with LLMs for a wide range of tasks and domains.
By the conclusion of this training, participants will be able to:
Explain what generative AI is and how it works.
Describe the transformer architecture that powers LLMs.
Use empirical scaling laws to optimize LLMs for different tasks and constraints.
Apply state-of-the-art tools and methods to train, fine-tune, and deploy LLMs.
Discuss the opportunities and risks of generative AI for society and business.
Large language models (LLMs) and autonomous agent frameworks, such as AutoGen and CrewAI, are transforming the way DevOps teams automate critical tasks like change tracking, test generation, and alert triage by emulating human-like collaboration and decision-making processes.
This instructor-led training, available both online and onsite, is designed for advanced-level engineers who aim to design and implement DevOps automation workflows driven by large language models (LLMs) and multi-agent systems.
Upon completion of this training, participants will be able to:
Integrate LLM-based agents into CI/CD pipelines to enable intelligent automation.
Automate test generation, commit analysis, and change summaries using agent-driven processes.
Orchestrate multiple agents to triage alerts, generate responses, and deliver DevOps recommendations.
Develop secure and maintainable agent-powered workflows using open-source frameworks.
Course Format
Interactive lectures and discussions.
Extensive exercises and practical practice.
Hands-on implementation within a live laboratory environment.
Customization Options
To request a customized version of this course, please contact us to make arrangements.
PostgreSQL is a sophisticated open-source relational database that can serve as the backbone for AI-powered systems and data intelligence applications.
This instructor-led, live training (available online or onsite) is designed for intermediate-level database professionals and developers who wish to integrate, manage, and optimize AI capabilities directly within PostgreSQL.
By the end of this training, participants will be able to:
Set up and configure PostgreSQL extensions for AI workloads.
Implement embeddings and similarity search using pgvector.
Integrate open source and proprietary LLMs with PostgreSQL for real-time insights.
Optimize PostgreSQL for handling AI-driven queries and workflows.
Format of the Course also allows for the evaluation of participants.
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 Lyon (online or onsite) targets intermediate to advanced AI developers, architects, and product managers who want to identify and mitigate risks associated with LLM-powered applications, such as prompt injection, data leakage, and unfiltered outputs. The course also covers implementing security controls like input validation, human-in-the-loop oversight, and output guardrails.
Upon completion of this training, participants will be able to:
Understand the core vulnerabilities of LLM-based systems.
Apply secure design principles to LLM app architecture.
Utilize tools such as Guardrails AI and LangChain for validation, filtering, and safety.
Integrate techniques like sandboxing, red teaming, and human-in-the-loop review into production-grade pipelines.
LangGraph serves as a graph-based orchestration framework designed to facilitate conditional, multi-step workflows involving LLMs and tools, making it an excellent choice for automating and personalizing content pipelines.
This instructor-led live training, available either 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 completion of this training, participants will be capable of:
Designing graph-structured content and email workflows that incorporate conditional logic.
Integrating LLMs, APIs, and data sources to achieve automated personalization.
Managing state, memory, and context throughout multi-step campaigns.
Evaluating, monitoring, and optimizing workflow performance and delivery outcomes.
Course Format
Interactive lectures and group discussions.
Hands-on labs focused on implementing email workflows and content pipelines.
Scenario-based exercises covering personalization, segmentation, and branching logic.
Course Customization Options
To request customized training for this course, please contact us to arrange.
This instructor-led, live training in Lyon (online or onsite) is aimed at intermediate-level to advanced-level professionals who wish to customize pre-trained models for specific tasks and datasets.
By the end of this training, participants will be able to:
Understand the principles of fine-tuning and its applications.
Prepare datasets for fine-tuning pre-trained models.
Fine-tune large language models (LLMs) for NLP tasks.
Optimize model performance and address common challenges.
LangGraph is a framework designed for composing graph-structured LLM workflows that support branching, tool use, memory, and controllable execution.
This instructor-led, live training (available online or onsite) targets intermediate-level engineers and product teams who aim to combine LangGraph’s graph logic with LLM agent loops to build 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 fallbacks for robust execution.
Integrate retrieval, APIs, and structured outputs into agent loops.
Evaluate, monitor, and harden agent behavior for reliability and safety.
Course Format
Interactive lecture and facilitated discussion.
Guided labs and code walkthroughs 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 arrange.
LLMs for Code Understanding, Refactoring, and Documentation is a specialized course designed to leverage large language models (LLMs) to enhance code quality, minimize technical debt, and automate documentation processes across software development teams.
This instructor-led, live training (available online or onsite) targets intermediate to advanced software professionals seeking to utilize LLMs, such as GPT, to more effectively analyze, refactor, and document complex or legacy codebases.
Upon completion of this training, participants will be equipped to:
Employ LLMs to clarify code, dependencies, and logic within unfamiliar repositories.
Identify and refactor anti-patterns to enhance code readability.
Automate the creation and maintenance of in-line comments, README files, and API documentation.
Integrate LLM-driven insights into existing CI/CD and code review workflows.
Course Format
Interactive lectures and discussions.
Extensive exercises and practical application.
Hands-on implementation in a live-lab environment.
Customization Options
To request a customized training for this course, please contact us to make arrangements.
This instructor-led, live training in Lyon (online or onsite) is designed for intermediate-level data scientists, AI developers, and AI enthusiasts who wish to utilize LLMs for various NLP tasks and create novel, diverse content for different purposes.
By the end of this training, participants will be able to:
Establish a development environment with LLMs and essential tools.
Expertly perform NLU and NLI tasks with LLMs.
Extract, infer, and utilize knowledge graphs effectively.
Generate and manage dialogues using LLMs for conversational applications.
Evaluate content quality and diversity generated by LLMs and generative AI.
Apply ethical principles, ensuring fairness and responsible use of LLMs.
LangGraph is a framework designed for creating graph-structured applications powered by large language models (LLMs), supporting features such as planning, branching, tool usage, memory management, and controllable execution.
This instructor-led live training, available either online or onsite, is tailored for beginner-level developers, prompt engineers, and data practitioners who aim to design and implement reliable, multi-step LLM workflows using LangGraph.
Upon completion of this training, participants will be able to:
Articulate the core concepts of LangGraph (nodes, edges, and state) and understand their appropriate use cases.
Construct prompt chains that branch, invoke tools, and maintain memory context.
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 combined with facilitated discussions.
Guided laboratory sessions and code walkthroughs conducted in a sandbox environment.
Scenario-based exercises focusing on design, testing, and evaluation.
Course Customization Options
To request a customized training session for this course, please contact us to make arrangements.
This instructor-led live training in Lyon (online or onsite) targets developers from beginner to intermediate levels who wish to utilize Large Language Models for various natural language tasks.
By the end of this training, participants will be able to:
Set up a development environment that includes a popular LLM.
Create a basic LLM and fine-tune it on a custom dataset.
Use LLMs for different natural language tasks such as text summarization, question answering, text generation, and more.
Debug and evaluate LLMs using tools such as TensorBoard, PyTorch Lightning, and Hugging Face Datasets.
This instructor-led, live training in Lyon (online or onsite) is aimed at intermediate-level engineers and architects who wish to use Tencent Hunyuan to deploy large and MoE models with lower latency, stronger throughput, and better cost control.
By the end of this training, participants will be able to: explain Hunyuan production deployment patterns, optimize inference performance, implement batching and quantization strategies, and plan scalable serving operations.
This instructor-led, live training in Lyon (online or onsite) is aimed at intermediate-level developers, technical product teams, and AI practitioners who wish to use Hunyuan models to create multimodal applications for image, 3D, and video generation and delivery.
By the end of this training, participants will be able to: build prompt-based workflows, generate and review multimodal assets, serve outputs through apps or APIs, and connect Hunyuan capabilities to enterprise product stacks.
This instructor-led, live training in Lyon (online or onsite) targets beginner, intermediate, and advanced-level AI professionals who wish to use MCP to link AI assistants with external tools, data, and enterprise services.
By the end of this training, participants will be able to explain MCP concepts, identify key architectural components, set up a basic integration, and apply security best practices.
This instructor-led, live training in Lyon (online or onsite) is aimed at intermediate-level enterprise architects who wish to use Model Context Protocol to design secure, scalable, and governable agent integration platforms for enterprise environments.
By the end of this training, participants will be able to: explain MCP architecture and enterprise patterns, design secure integration platforms, apply governance and access controls, and evaluate deployment and scaling options.
This instructor-led live training in Lyon (online or on-site) is designed for intermediate developers, architects, and platform engineers aiming to use MCP to build reliable servers and clients for enterprise deployment and operations.
By the end of this training, participants will be able to: explain MCP architecture in practice, build production-ready integrations, deploy and monitor MCP services, and apply patterns for versioning, resilience, and support.
This instructor-led, live training in Lyon (online or onsite) is designed for intermediate-level IT leaders, compliance professionals, security teams, and enterprise architects who wish to leverage sovereign AI principles and governance practices. The goal is to design AI environments that protect sensitive data, support localization mandates, and reduce vendor lock-in.
By the end of this training, participants will be able to explain sovereign AI concepts, evaluate hosting and governance options, define controls for prompts and logs, and create a practical adoption roadmap.
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Olga - GE HealthCare
Course - Generative AI with Large Language Models (LLMs)
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