Large Language Models (LLMs) Training in Sud-Vest

This instructor-led, live training in Sud-Vest (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 Sud-Vest (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 guided, live training session in Sud-Vest (online or onsite) is designed for AI researchers, data scientists, and developers with intermediate to advanced expertise who aim to grasp, customize, and apply Meta AI's Large Language Models across various Natural Language Processing (NLP) tasks.

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

• Comprehend the architecture and operational mechanics of Meta AI's Large Language Models.
• Configure and tailor Meta AI LLMs for specific application scenarios.
• Develop LLM-driven applications such as summarization tools, conversational agents, and sentiment analyzers.
• Efficiently optimize and deploy large language models.

This live, instructor-led training in Sud-Vest (available online or onsite) is tailored for intermediate-level AI professionals, business analysts, and technology leaders seeking to understand the fundamentals of generative AI and the application of LLMs in business environments. Participants will gain insights into transformers, prompt engineering, and the ethical aspects of 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 Sud-Vest (online or onsite) is designed for intermediate-level AI professionals, ethicists, data scientists, engineers, and policymakers and stakeholders who want to understand and navigate the ethical landscape surrounding LLMs.

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

• Recognize ethical issues and challenges related to LLMs.
• Apply ethical frameworks and principles to LLM implementation.
• Evaluate the societal impact of LLMs and mitigate potential risks.
• Create strategies for responsible AI development and usage.

This instructor-led, live training in Sud-Vest (online or on-site) is designed for intermediate NLP specialists, data scientists, content creators, translators, and global enterprises seeking to utilize LLMs for language translation and the creation of multilingual content.

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

• Grasp the fundamental principles of cross-lingual learning and translation utilizing LLMs.
• Deploy LLMs to translate content across various languages.
• Construct and manage multilingual datasets for training LLMs.
• Formulate strategies to ensure consistency and high quality in translation outputs.

This instructor-led, live training in Sud-Vest (online or onsite) is aimed at intermediate-level financial analysts, data scientists, and investment professionals who wish to leverage LLMs for financial market analysis and prediction.

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

• Understand the application of LLMs in financial market analysis.
• Use LLMs to process financial news, reports, and data for market insights.
• Develop predictive models for stock prices, market trends, and economic indicators.
• Integrate LLM insights into investment decision-making processes.

This instructor-led, live training in Sud-Vest (online or onsite) is aimed at intermediate-level environmental scientists and researchers, data analysts, and policy makers and environmental advocates who wish 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 Sud-Vest (available online or on-site) is tailored for intermediate-level VR and AR developers, game designers, and AI engineers who aim to incorporate LLMs into their 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 Sud-Vest (online or onsite) is designed for intermediate-level data scientists, machine learning engineers, and software developers looking to harness LLMs with multimodal data to build advanced AI solutions.

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

• Comprehend the core principles of multimodal learning using LLMs.
• Deploy LLMs to process and analyze text, image, and audio data.
• Build applications that capitalize on the synergies of multimodal data integration.
• Assess the performance of multimodal LLM systems.

This instructor-led, live training in Sud-Vest (online or onsite) is designed for intermediate-level cybersecurity professionals and data scientists who wish to leverage LLMs to enhance cybersecurity measures and threat intelligence.

Upon completing this training, participants will be capable of:

• Grasping the role of LLMs in cybersecurity.
• Implementing LLMs for threat detection and analysis.
• Applying LLMs for security automation and response.
• Integrating LLMs with existing security infrastructure.

This instructor-led, live training in Sud-Vest (online or onsite) is designed for intermediate-level data scientists and business analysts who aim to leverage large language models (LLMs) to forecast trends and behaviors across diverse industries.

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

• Grasp the fundamentals of LLMs and their significance in predictive analytics.
• Deploy LLMs to analyze and forecast data within various sectors.
• Assess the efficacy of predictive models utilizing LLMs.
• Integrate LLMs into current data processing workflows.

This instructor-led, live training in Sud-Vest (online or onsite) is aimed at intermediate-level data scientists who wish to gain a comprehensive understanding and practical skills in both Large Language Models (LLMs) and Reinforcement Learning (RL).

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

• Understand the components and functionality of transformer models.
• Optimize and fine-tune LLMs for specific tasks and applications.
• Understand the core principles and methodologies of reinforcement learning.
• Learn how reinforcement learning techniques can enhance the performance of LLMs.

This instructor-led live training in Sud-Vest (online or onsite) is designed for intermediate-level content creators, marketers, and educational technologists who want to leverage LLMs to produce high-quality, diverse, and engaging content across various sectors.

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 Sud-Vest (online or onsite) is designed for educators, EdTech professionals, and researchers of varying experience levels who aim to leverage LLMs for creating personalized educational experiences.

By the end 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 improvements.

This instructor-led, live training in Sud-Vest (online or onsite) is aimed at intermediate-level ML practitioners and AI developers who wish to fine-tune and deploy open-weight models like LLaMA, Mistral, and Qwen for specific business or internal applications.

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

• Understand the ecosystem and differences between open-source LLMs.
• Prepare datasets and fine-tuning configurations for models like LLaMA, Mistral, and Qwen.
• Execute fine-tuning pipelines using Hugging Face Transformers and PEFT.
• Evaluate, save, and deploy fine-tuned models in secure environments.

This instructor-led, live training in Sud-Vest (online or on-site) is designed for software developers and data scientists at beginner to intermediate levels 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 Sud-Vest (online or onsite) is designed for beginner to intermediate-level customer support and IT professionals seeking to implement LLMs for creating 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 Sud-Vest (online or on-site) is tailored for intermediate-level data scientists and AI engineers who want to fine-tune large language models more affordably and efficiently using methods like LoRA, Adapter Tuning, and Prefix Tuning.

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

• Understand the theory behind parameter-efficient fine-tuning approaches.
• Implement LoRA, Adapter Tuning, and Prefix Tuning using Hugging Face PEFT.
• Compare performance and cost trade-offs of PEFT methods vs. full fine-tuning.
• Deploy and scale fine-tuned LLMs with reduced compute and storage requirements.

Delivered as an instructor-led live session (online or on-site), this training is designed for intermediate to advanced machine learning engineers, AI developers, and data scientists seeking to learn how to leverage QLoRA for the efficient fine-tuning of large models for specific tasks and customizations.

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

• Understand the theoretical basis of QLoRA and quantization techniques for LLMs.
• Implement QLoRA for fine-tuning large language models in domain-specific applications.
• Optimize fine-tuning performance on limited computational resources using quantization.
• Deploy and evaluate fine-tuned models efficiently in real-world applications.

This instructor-led, live training in Sud-Vest (online or onsite) is designed for intermediate-level data and marketing professionals who wish to leverage 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:

• Understand 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 Sud-Vest (online or onsite) is designed for intermediate-level software developers and technical writers who aim to utilize LLMs to streamline their coding workflows and produce detailed, comprehensive documentation.

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

• Understand 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 for enhanced 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 Sud-Vest (online or onsite) targets intermediate-level business professionals and data analysts eager to leverage LLMs for extracting actionable business insights.

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

• Grasp the fundamentals and practical applications of LLMs within business intelligence.
• Utilize LLMs to analyze large datasets and derive meaningful insights.
• Integrate LLM-driven analytics into strategic business decision-making processes.
• Evaluate ethical considerations and best practices for deploying LLMs in business environments.
• Anticipate future AI trends and prepare for the evolving business intelligence landscape.

This instructor-led, live training in Sud-Vest (online or on-site) is aimed at intermediate to advanced developers and data scientists who wish to master LlamaIndex for developing innovative LLM-powered applications.

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

• Set up 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 Sud-Vest (online or onsite) is aimed at intermediate-level AI researchers, machine learning professionals, and data scientists who wish to use LlamaIndex to enhance the capabilities of AI models, 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 delivered in Sud-Vest (online or onsite) is designed for intermediate-level professionals who aim to utilize prompt engineering and few-shot learning to enhance LLM performance for real-world applications.

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

• Understand the core principles of prompt engineering and few-shot learning.
• Design effective prompts for various NLP tasks.
• Apply few-shot techniques to adapt LLMs with minimal data.
• Optimize LLM performance for practical applications.

This instructor-led, live training (online or onsite) targets advanced engineers, AI specialists, and localization leaders who aim to implement large language model (LLM) systems for automated translation, quality assessment, and enterprise governance.

Upon completing this training, participants will be capable of:

• Developing enterprise-grade LLM localization pipelines that incorporate both open-source and proprietary models.
• Implementing automated QA workflows and quality metrics to ensure translation consistency.
• Setting up governance and approval frameworks for multilingual content production.
• Deploying scalable, auditable LLM-based localization systems within secure environments.

AI for SQL applies artificial intelligence and large language models (LLMs) to automate, optimize, and enhance the generation, execution, and interpretation of SQL queries within enterprise data environments.

This instructor-led live training (available online or on-site) targets intermediate data engineers and technical leads aiming 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

• 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 for constructing stateful, multi-agent LLM applications using composable graphs that maintain persistent state and provide 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 financial solutions with robust governance, observability, and regulatory compliance.

Upon completion of 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 states and associated tools.
• Implement reliability, safety measures, and human-in-the-loop controls for critical operations.
• Deploy, monitor, and optimize LangGraph systems to ensure high performance, cost efficiency, and adherence to SLAs.

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.

Vertex AI offers robust tools for constructing multimodal LLM workflows that unify text, audio, and image data within a single pipeline. By leveraging long context window support and Gemini API parameters, it facilitates the development of advanced applications involving planning, reasoning, and cross-modal intelligence.

This instructor-led, live training session, available both online and onsite, targets intermediate to advanced practitioners who aim to design, build, and optimize multimodal AI workflows in Vertex AI.

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

• Utilize Gemini models to handle multimodal inputs and outputs.
• Implement workflows capable of managing long contexts for complex reasoning tasks.
• Design pipelines that seamlessly integrate text, audio, and image analysis.
• Optimize Gemini API parameters to enhance performance and cost efficiency.

Format of the Course

• Interactive lectures and discussions.
• Practical labs focused on multimodal workflows.
• Project-based exercises addressing real-world multimodal use cases.

Course Customization Options

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

LangGraph empowers stateful, multi-actor workflows driven by LLMs, offering precise control over execution paths and state persistence. For the healthcare sector, these capabilities are essential for ensuring compliance, enabling interoperability, and developing decision-support systems that seamlessly integrate with medical workflows.

This instructor-led, live training—available either online or on-site—is designed for intermediate to advanced professionals looking to design, implement, and manage LangGraph-based healthcare solutions while navigating regulatory, ethical, and operational challenges.

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

• Designing healthcare-specific LangGraph workflows that prioritize compliance and auditability.
• Integrating LangGraph applications with medical ontologies and standards (FHIR, SNOMED CT, ICD).
• Applying best practices for reliability, traceability, and explainability within sensitive environments.
• Deploying, monitoring, and validating LangGraph applications in healthcare production settings.

Format of the Course

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

Course Customization Options

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

This live, instructor-led program (available online or in-person) is designed for intermediate AI developers and localization engineers who aim to build scalable, automated translation pipelines using both proprietary and open-source LLMs.

By the conclusion 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 is a framework designed for creating stateful, multi-actor LLM applications through composable graphs that maintain persistent state and provide execution control.

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

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

• Design and optimize complex LangGraph topologies for enhanced speed, cost-efficiency, and scalability.
• Engineer 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 to production; and monitor SLAs and costs.

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 a customized training session for this course, please contact us to arrange details.

This instructor-led, live training in Sud-Vest (online or onsite) is designed for intermediate-level developers who want to learn how to leverage generative AI and LLMs for various tasks and domains.

Upon completing this training, participants will be able to:

• Define generative AI and explain its underlying mechanisms.
• Describe the transformer architecture that drives LLMs.
• Apply empirical scaling laws to optimize LLMs for specific tasks and constraints.
• Utilize cutting-edge tools and methods to train, fine-tune, and deploy LLMs.
• Analyze the opportunities and risks associated with generative AI for both society and business.

Autonomous agent frameworks such as AutoGen and CrewAI, along with Large Language Models (LLMs), are transforming how DevOps teams automate critical tasks like change tracking, test generation, and alert triage by mimicking human-like collaboration and decision-making processes.

This live training session, led by an instructor and available both online and onsite, is designed for advanced engineers who want to design and implement DevOps automation workflows driven by LLMs and multi-agent systems.

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

• Integrating LLM-based agents into CI/CD workflows for intelligent automation.
• Utilizing agents to automate test generation, commit analysis, and change summaries.
• Coordinating multiple agents to triage alerts, generate responses, and provide DevOps recommendations.
• Developing secure and maintainable agent-driven 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 arrange customized training for this course, please contact us.

Postgres, an advanced open-source relational database, serves as a robust foundation for building AI-powered systems and data intelligence applications.

This instructor-led live training, available online or on-site, targets intermediate-level database professionals and developers seeking to integrate, manage, and optimize AI capabilities directly within Postgres.

Upon completing this training, participants will be able to:

• Set up and configure Postgres extensions designed for AI workloads.
• Implement embeddings and similarity search using pgvector.
• Integrate both open-source and proprietary LLMs with Postgres to deliver real-time insights.
• Optimize Postgres for handling AI-driven queries and workflows.

Format of the Course

• Interactive lecture and discussion.
• Extensive exercises and practical 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 Sud-Vest (online or in-person) targets intermediate to advanced AI developers, architects, and product managers aiming to identify and mitigate risks linked to LLM-powered applications. These risks include prompt injection, data leakage, and unfiltered outputs, while implementing security controls such as input validation, human-in-the-loop oversight, and output guardrails.

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

• Comprehend the primary vulnerabilities of LLM-based systems.
• Apply secure design principles to the architecture of LLM applications.
• Employ tools like Guardrails AI and LangChain for validation, filtering, and safety assurance.
• Integrate methods such as sandboxing, red teaming, and human-in-the-loop review into production-grade pipelines.

This instructor-led, live training in Sud-Vest (online or onsite) targets intermediate to advanced professionals who want 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.

This technical course, 'LLMs for Code Understanding, Refactoring, and Documentation,' focuses on leveraging large language models (LLMs) to enhance code quality, minimize technical debt, and automate documentation processes within software teams.

Delivered as an instructor-led live session (available online or onsite), this training is designed for intermediate to advanced software professionals aiming to effectively analyze, refactor, and document complex or legacy codebases using LLMs like GPT.

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

• Employing LLMs to clarify code structure, dependencies, and logic within unfamiliar repositories.
• Identifying and refactoring anti-patterns while enhancing overall code readability.
• Automating the generation and upkeep of inline comments, README files, and API documentation.
• Integrating LLM-driven insights into current CI/CD and code review workflows.

Course Format

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

Customization Options

• To arrange a customized training version of this course, please contact us directly.

This instructor-led live training in Sud-Vest (online or onsite) is targeted at intermediate-level data scientists, AI developers, and AI enthusiasts who wish to utilize LLMs for various NLP tasks and generate 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 constructing graph-structured LLM applications that facilitate planning, branching, tool utilization, memory management, and controlled execution.

This instructor-led, live training session (available 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.

By the conclusion of this training, participants will be capable of:

• Describing core LangGraph concepts (nodes, edges, state) and understanding their appropriate use cases.
• Constructing prompt chains that support branching, tool invocation, and memory retention.
• Integrating retrieval mechanisms and external APIs into graph-based workflows.
• Testing, debugging, and evaluating LangGraph applications to ensure reliability and safety.

Course Format

• Interactive lectures and facilitated discussions.
• Guided laboratory exercises and code walkthroughs within a sandbox environment.
• Scenario-based exercises focused on design, testing, and evaluation.

Course Customization Options

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

This instructor-led, live training in Sud-Vest (online or onsite) is designed for 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 Sud-Vest (online or onsite) targets observability and SRE engineers looking to incorporate LLMs and AI into their monitoring, alerting, and incident analysis processes.

This instructor-led, live training in Sud-Vest (online or onsite) is designed for IT support professionals aiming to leverage AI tools and automation platforms to streamline support processes, standardize responses, and reduce manual documentation effort.

This instructor-led, live training in Sud-Vest (online or onsite) is designed for intermediate-level engineers and architects who aim to use Tencent Hunyuan to deploy large and MoE models with reduced latency, enhanced throughput, and improved cost control.

By the end of this training, participants will be able to: explain production deployment patterns for Hunyuan, optimize inference performance, implement batching and quantization strategies, and plan scalable serving operations.

This instructor-led, live training in Sud-Vest (available online or onsite) is designed for intermediate-level developers, technical product teams, and AI practitioners who aim to utilize Hunyuan models for creating multimodal applications involving image, 3D, and video generation and delivery.

By the end of this training, participants will be able to: build prompt-driven workflows, generate and assess multimodal assets, distribute outputs through apps or APIs, and link Hunyuan capabilities to enterprise product stacks.

Course objectives turn software and AI engineers into legal engineers – the people who can actually build AI for legal work (eDiscovery, review, investigations).

In two days, participants build the full core stack: ingest and extract messy real-world legal data, search and retrieve it, add retrieval-augmented generation (RAG) with citations, keep it private on a local model and prove it, run a defensible AI review with court-ready metrics, and package the result for deployment.

This instructor-led live training in Sud-Vest (online or onsite) is designed for beginner, intermediate, or advanced-level AI professionals who want to use MCP to connect 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 architecture components, set up a basic integration, and apply security best practices.

This instructor-led live training in Sud-Vest (available online or onsite) is designed for intermediate-level enterprise architects who wish to utilize the 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, conducted in Sud-Vest (online or onsite), is designed for intermediate-level developers, architects, and platform engineers who aim to use MCP to build reliable servers and clients suitable for enterprise deployment and operations.

By the end of this training, participants will be able to explain MCP architecture in practice, construct production-ready integrations, deploy and monitor MCP services, and apply patterns for versioning, resilience, and support.

This instructor-led training in Sud-Vest (delivered online or onsite) targets mid-level IT executives, compliance officers, security specialists, and enterprise architects seeking to utilize sovereign AI principles and governance strategies. The goal is to design AI environments that protect sensitive data, adhere to localization rules, and decrease vendor lock-in.

By the end of this session, participants will be able to explain sovereign AI concepts, assess hosting and governance alternatives, define controls for prompts and logs, and develop a practical roadmap for adoption.