Large Language Models (LLMs) Training in Gaia

This instructor-led, live training in Gaia (online or onsite) is designed for senior management professionals who wish to understand what LLMs are, explore their potential impact on business operations, and evaluate the 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 live, instructor-led training conducted in Gaia (available online or on-site) targets senior management teams aiming to comprehend the strategic value of LLMs and enterprise AI tools. Participants will delve into integrating these tools into high-level workflows, crafting more effective prompts, and identifying opportunities to enhance productivity and ROI through AI adoption.

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

• Understand the functionality of LLMs and how tools like ChatGPT and Copilot apply them.
• Utilize prompt-based interactions to automate and speed up tasks.
• Apply AI tools to real-world scenarios such as email drafting, report summarization, and agreement review.
• Evaluate the strategic benefits, limitations, and licensing considerations associated with LLM adoption.

This instructor-led live training in Gaia (available online or onsite) is designed for intermediate to advanced AI researchers, data scientists, and developers aiming to master the architecture, fine-tuning, and implementation of Meta AI's Large Language Models for diverse NLP applications.

Upon completion, participants will be capable of:

• Understanding the core architecture and functional mechanisms of Meta AI's Large Language Models.
• Setting up and fine-tuning Meta AI LLMs for targeted use cases.
• Building LLM-based applications, including text summarization, chatbots, and sentiment analysis tools.
• Optimizing model performance and executing efficient deployment strategies.

This instructor-led live training in Gaia (online or onsite) is designed for intermediate-level AI professionals, business analysts, and technology leaders who want to understand the principles of generative AI and explore LLM applications within business environments. Participants will learn about transformers, prompt engineering, and the ethical considerations involved in deploying these models for real-world solutions.

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

• Grasp the fundamental principles of generative AI and large language models.
• Implement and fine-tune LLMs for specific business applications.
• Apply prompt engineering techniques to achieve optimal model outputs.
• Identify ethical considerations and manage risks associated with LLM deployment.

This instructor-led, live training in Gaia (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 Gaia (online or on-site) is designed for intermediate NLP practitioners, data scientists, content creators, translators, and global businesses aiming to leverage LLMs for language translation and multilingual content production.

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

• Grasp the fundamentals of cross-lingual learning and translation using LLMs.
• Deploy LLMs to translate content between multiple languages.
• Generate and manage multilingual datasets for training LLMs.
• Formulate strategies to ensure consistency and high quality in translation outcomes.

This instructor-led, live training in Gaia (available online or onsite) is tailored for intermediate-level financial analysts, data scientists, and investment professionals looking to utilise LLMs for financial market analysis and forecasting.

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

• Understand how LLMs are applied in financial market analysis.
• Employ LLMs to process financial news, reports, and data for deeper market insights.
• Develop predictive models for stock prices, market trends, and economic indicators.
• Seamlessly integrate LLM-derived insights into investment decision-making processes.

This instructor-led, live training in Gaia (available online or onsite) targets intermediate-level environmental scientists, researchers, data analysts, and policy makers or environmental advocates who wish to apply LLMs to environmental modeling and analysis.

By the conclusion 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 Gaia (online or on-site) 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.

Upon completing this training, participants will be able to:

• Comprehend the role of LLMs in crafting immersive VR and AR experiences.
• Develop VR and AR applications that leverage LLMs for interactive dialogues and content creation.
• Integrate LLMs with VR and AR development tools to enhance user engagement.
• Apply best practices for designing AI-driven narratives and interactions within virtual spaces.

This instructor-led, live training in Gaia (online or on-site) 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.

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

• Understand the principles of multimodal learning with LLMs.
• Implement LLMs to process and analyze text, image, and audio data.
• Develop applications that leverage the strengths of multimodal data integration.
• Evaluate the performance of multimodal LLM systems.

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

Upon completing this training, participants will be able to:

• Grasp 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 Gaia (online or onsite) is designed for data scientists and business analysts at an intermediate level who aim to utilise large language models (LLMs) to forecast trends and behaviours 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 Gaia (online or on-site) is targeted at intermediate-level data scientists seeking to acquire a comprehensive grasp and practical skills in both Large Language Models (LLMs) and Reinforcement Learning (RL).

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

• Understanding the structure and operation of transformer models.
• Optimizing and fine-tuning LLMs for specific tasks and use cases.
• Grasping the core principles and methodologies of reinforcement learning.
• Learning how reinforcement learning techniques can boost LLM performance.

This instructor-led, live training in Gaia (online or onsite) is aimed at intermediate-level content creators, marketers, and educational technologists who wish to harness the power of LLMs for generating high-quality, diverse, and engaging content across various domains.

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 Gaia (online or onsite) targets educators, EdTech professionals, and researchers with diverse expertise levels who wish to leverage LLMs to craft personalised educational experiences.

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

• Comprehend the architecture and capabilities of LLMs.
• Identify opportunities for personalising educational content using LLMs.
• Design adaptive learning platforms that utilise LLMs for content personalisation.
• Implement LLM-driven strategies to enhance 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 Gaia (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 Gaia (online or onsite) targets beginner to intermediate software developers and data scientists who wish to implement LLMs within speech recognition and synthesis systems.

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

• Grasp the role of LLMs in speech technologies.
• Implement LLMs to achieve accurate speech recognition and natural-sounding speech synthesis.
• Integrate LLMs with speech recognition engines and synthesizers.
• Evaluate and enhance the performance of speech systems using LLMs.
• Keep abreast of current trends and future directions in speech technologies.

This instructor-led, live training in Gaia (online or onsite) is designed for beginner to intermediate-level customer support and IT professionals aiming to implement LLMs to create responsive and intelligent customer support chatbots.

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

• Grasp the fundamentals and architecture of Large Language Models (LLMs).
• Design and integrate LLMs into customer support systems.
• Improve the responsiveness and user experience of chatbots.
• Address ethical considerations and ensure compliance with industry standards.
• Deploy and maintain an LLM-based chatbot for practical, real-world applications.

This live, instructor-led training in Gaia (offered online or onsite) is designed for intermediate-level data scientists and AI engineers aiming to fine-tune large language models with improved affordability and efficiency, employing techniques such as LoRA, Adapter Tuning, and Prefix Tuning.

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

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

This instructor-led, live training in Gaia (online or on-site) is designed for intermediate to advanced-level machine learning engineers, AI developers, and data scientists who wish to learn how to employ QLoRA to efficiently fine-tune large models for specific tasks and customisations.

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

• Comprehend the theory behind 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 through quantization.
• Deploy and evaluate fine-tuned models in real-world applications efficiently.

This instructor-led live training in Gaia (available online or onsite) targets intermediate-level data and marketing professionals who wish 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:

• 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 Gaia (online or onsite) is aimed at intermediate-level software developers and technical writers who wish to leverage LLMs to streamline their coding workflow and create 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 Gaia (online or onsite) is designed for intermediate-level business professionals and data analysts who wish to harness the power of LLMs for extracting 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 Gaia (online or onsite) is aimed at intermediate-level to advanced-level 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 Gaia (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:

• Grasp the principles and components of LlamaIndex.
• Ingest and structure data for use with LLMs.
• Apply context augmentation to improve AI model performance.
• Integrate LlamaIndex into existing AI systems and workflows.

This instructor-led, live training in Gaia (online or onsite) is aimed at intermediate-level professionals who wish to leverage the power of prompt engineering and few-shot learning to optimize LLM performance for real-world applications.

By the end 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.

This live, instructor-led programme (available online or on-site) is designed for senior engineers, AI specialists, and localization leaders aiming to implement large language model (LLM) systems for automated translation, quality assessment, and enterprise governance.

Upon completion, participants will be equipped to:

• Construct enterprise-grade LLM localization pipelines that integrate both open-source and proprietary models.
• Deploy automated QA workflows and quality metrics to ensure translation consistency.
• Define governance and approval structures for multilingual content production.
• Roll out scalable, auditable LLM-based localization systems within secure environments.

This live, instructor-led training in Gaia empowers data engineers with the competencies required to integrate LLMs into SQL environments. Learners will develop natural language pipelines, apply AI-driven optimization techniques, and architect secure enterprise workflows for automated data analysis.

This live training in Gaia empowers practitioners to design, construct, and optimise multimodal LLM workflows within Vertex AI. The curriculum explores Gemini models, long-context reasoning, and pipelines that merge text, audio, and image data. Through hands-on labs, the course ensures practical competence for real-world application.

This instructor-led, live session (available online or onsite) is designed for intermediate AI developers and localization engineers looking to build scalable, automated translation pipelines using a mix of proprietary and open-source LLMs.

By the end of this program, you will have the ability to:

• Design and implement translation workflows using state-of-the-art LLM frameworks and APIs.
• Incorporate both open-source and commercial models into scalable translation architectures.
• Enhance translation quality through fine-tuning, prompt engineering, and automated processes.
• Deploy cost-efficient and compliant translation infrastructure for enterprise settings.

This instructor-led live training in Gaia (online or onsite) is designed for intermediate-level developers who wish to learn how to use generative AI with LLMs for various tasks and domains.

By the end 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.

Gain mastery over AI integration in Postgres through this live, instructor-led training in Gaia. You will learn to configure extensions, implement pgvector embeddings, and connect LLMs for real-time insights. Optimise queries and build intelligent systems within a hands-on live-lab environment.

This instructor-led live training in Gaia, offered online or onsite, targets intermediate to advanced AI developers, architects, and product managers. The course focuses on identifying and mitigating risks associated with LLM-powered applications, including prompt injection, data leakage, and unfiltered outputs. Participants will learn to implement security controls such as input validation, human-in-the-loop oversight, and output guardrails.

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

• Understand the core vulnerabilities of LLM-based systems.
• Apply secure design principles to LLM app architecture.
• Use 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.

This instructor-led, live training in Gaia (online or onsite) is designed for intermediate to advanced 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 Natural Language Processing (NLP) tasks.
• Optimize model performance and address common challenges.

This instructor-led, live training in Gaia (online or onsite) is aimed at intermediate-level data scientists, AI developers, and AI enthusiasts who wish to use LLMs to perform various NLP tasks and create novel and 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.

This instructor-led, live training in Gaia (online or onsite) is designed for developers at beginner to intermediate levels who wish to utilize Large Language Models for various natural language tasks.

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

• Configure a development environment integrated with a prominent LLM.
• Construct a foundational LLM and fine-tune it using a custom dataset.
• Apply LLMs to various natural language tasks such as text summarization, question answering, and text generation.
• Debug and evaluate LLMs using tools like TensorBoard, PyTorch Lightning, and Hugging Face Datasets.

This instructor-led, live training in Gaia (online or onsite) is aimed at observability and SRE engineers who want to integrate LLMs and AI into their monitoring, alerting, and incident analysis workflows.

This instructor-led, live training in Gaia (available online or onsite) is designed for IT support professionals who wish to use AI tools and automation platforms to streamline support processes, standardize responses, and reduce manual documentation effort.

This instructor-led, live training in Gaia (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 Gaia (online or onsite) is designed for intermediate-level developers, technical product teams, and AI practitioners who wish to use Hunyuan models to develop 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 evaluate multimodal assets, serve outputs through apps or APIs, and connect Hunyuan capabilities to enterprise product stacks.

Course objectives turn software / 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 Gaia (online or onsite) is aimed at beginner-, intermediate-, or advanced-level AI professionals who wish 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 Gaia (online or onsite) targets intermediate-level enterprise architects who wish to use 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 in Gaia (online or on-site) is aimed at intermediate developers, architects, and platform engineers who wish 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 practical MCP architecture, build production-ready integrations, deploy and observe MCP services, and apply patterns for versioning, resilience, and support.

This instructor-led, live training in Gaia (online or onsite) targets intermediate-level IT leaders, compliance professionals, security teams, and enterprise architects who wish to apply sovereign AI principles and governance practices to design AI environments that safeguard sensitive data, meet localization requirements, and minimize vendor lock-in.

Upon completing 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.