Large Language Models (LLMs) Training in Prague

This instructor-led, live training in Prague (online or onsite) is designed for senior management professionals who aim to understand the nature of LLMs, explore their potential impact on business operations, and assess the practical utility of AI tools such as ChatGPT, Microsoft Copilot, or Grok for real-world tasks including content creation, data summarization, and decision support.

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

• Comprehend the fundamentals of LLMs and the operational mechanics of tools like ChatGPT and Copilot.
• Apply effective prompting techniques to derive practical and reliable outcomes from LLMs.
• Assess real-world use cases, such as drafting emails, summarizing documents, and automating productivity tasks.
• Identify strategic investment opportunities and applications for AI adoption within the organization.

This instructor-led, live training in Prague (available online or onsite) is tailored for senior management teams aiming to understand the strategic impact of LLMs and enterprise AI tools. Participants will explore strategies for integrating these tools into high-level workflows, drafting improved prompts, and evaluating opportunities to enhance productivity and ROI through AI adoption.

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

• Understand the functionality of LLMs and how applications like ChatGPT and Copilot utilize them.
• Utilize prompt-based interactions to automate and speed up tasks.
• Deploy AI tools in real-world scenarios, such as email composition, report summarization, and contract review.
• Evaluate the strategic benefits, constraints, and licensing requirements for LLM implementation.

This instructor-led live training Prague (online or onsite) is designed for intermediate to advanced AI researchers, data scientists, and developers who want to understand, fine-tune, and implement Meta AI's Large Language Models for various NLP applications.

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

• Grasping the architecture and operational mechanics of Meta AI's Large Language Models.
• Configuring and fine-tuning Meta AI LLMs for specific use cases.
• Developing LLM-powered applications, including text summarization, chatbots, and sentiment analysis.
• Efficiently optimizing and deploying large language models.

This instructor-led, live training in Prague (available 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 Prague (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 Prague (online or onsite) is aimed at intermediate-level NLP practitioners and data scientists, content creators and translators, and global businesses who wish to use LLMs for language translation and creating multilingual content.

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, held in Prague (either online or onsite), is tailored for intermediate-level financial analysts, data scientists, and investment professionals seeking to leverage LLMs for enhanced market analysis and prediction.

By the conclusion of the course, participants will be able to:

• Understand the practical application of LLMs in financial market analysis.
• Use LLMs to derive market insights from financial news, reports, and data.
• Build predictive models targeting stock prices, market trends, and economic indicators.
• Integrate LLM-generated insights into the investment decision-making process.

This instructor-led, live training in Prague (online or on-site) is designed for intermediate-level environmental scientists, researchers, data analysts, and policy makers or advocates interested in leveraging LLMs for environmental modeling and analysis.

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

• Grasp how LLMs are applied within environmental science.
• Employ LLMs to analyze and model environmental data.
• Interpret LLM outputs for environmental impact assessments.
• Effectively communicate findings to influence policy and conservation initiatives.

This instructor-led, live training in Prague (online or onsite) is aimed at 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 live, instructor-led training in Prague (online or on-site) targets 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 Prague (online or onsite) targets intermediate-level cybersecurity professionals and data scientists who aim to leverage LLMs to improve security measures and threat intelligence.

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

• Grasp the role of LLMs in cybersecurity.
• Deploy LLMs for the detection and analysis of threats.
• Apply LLMs to automate security tasks and respond to incidents.
• Integrate LLMs into existing security infrastructure.

This instructor-led, live training in Prague (online or onsite) is designed for intermediate-level data scientists and business analysts who want to leverage large language models (LLMs) to anticipate trends and behaviors across various industries.

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

• Grasp the fundamentals of LLMs and their role in predictive analytics.
• Apply LLMs to analyze and forecast data across different sectors.
• Assess the effectiveness of predictive models powered by LLMs.
• Integrate LLMs into existing data processing pipelines.

This instructor-led live training in Prague (online or onsite) is designed for intermediate-level data scientists aiming to develop a comprehensive understanding and practical skills in both Large Language Models (LLMs) and Reinforcement Learning (RL).

By the conclusion 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 Prague (online or onsite) targets 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 Prague (online or onsite) is aimed at educators, EdTech professionals, and researchers with varying levels of experience and expertise who wish 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

This instructor-led, live training in Prague (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 Prague (online or onsite) is designed for beginner to intermediate-level 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 Prague (online or onsite) is designed for customer support and IT professionals with beginner to intermediate proficiency who wish to utilize LLMs to develop 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 live, instructor-led training in Prague, available either online or onsite, is designed for intermediate data scientists and AI engineers seeking to fine-tune large language models with improved affordability and efficiency through methods like LoRA, Adapter Tuning, and Prefix Tuning.

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

• Comprehend the theoretical underpinnings of parameter-efficient fine-tuning strategies.
• Apply LoRA, Adapter Tuning, and Prefix Tuning using Hugging Face PEFT.
• Evaluate and compare the trade-offs regarding performance and cost between PEFT methods and full fine-tuning.
• Deploy and scale fine-tuned LLMs with minimized compute and storage overhead.

This instructor-led, live training in Prague (online or onsite) targets machine learning engineers, AI developers, and data scientists with intermediate to advanced proficiency levels who aim to master the efficient refinement of large models for specific tasks and custom modifications using QLoRA.

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

• Comprehending the theoretical basis of QLoRA and quantization strategies for LLMs.
• Applying QLoRA to refine large language models for domain-specific use cases.
• Enhancing refinement performance on constrained computational hardware via quantization.
• Efficiently deploying and evaluating refined models within real-world contexts.

This instructor-led live training in Prague (available online or on-site) targets intermediate-level data and marketing professionals aiming 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 Prague (online or onsite) is aimed at intermediate 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 Prague (online or onsite) is designed for intermediate-level business professionals and data analysts who wish to harness 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 Prague (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:

• 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 Prague (online or onsite) is tailored for intermediate-level AI researchers, machine learning professionals, and data scientists who wish to utilize LlamaIndex to boost the capabilities of AI models, making them more accurate and reliable across various applications.

Upon completing this training, participants will be able to:

• Grasp the core principles and components of LlamaIndex.
• Ingest and structure data for effective use with LLMs.
• Implement context augmentation techniques to enhance AI model performance.
• Integrate LlamaIndex into existing AI systems and workflows.

This instructor-led, live training in Prague (online or onsite) is designed for intermediate-level professionals who aim to leverage 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 session (available online or on-site) targets senior engineers, AI specialists, and localization leads aiming to implement Large Language Model (LLM) systems for automated translation, quality assessment, and enterprise-level governance.

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

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

This instructor-led live training in Prague empowers data engineers to embed LLMs into SQL environments. Learners will construct natural language pipelines, apply AI-driven optimization, and design secure enterprise workflows for automated data analysis.

This live, instructor-led training—available either online or on-site—is tailored for intermediate-level AI developers and localization engineers looking to build scalable, automated translation pipelines leveraging both proprietary and open-source LLMs.

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

• Architect and deploy translation workflows utilizing modern LLM frameworks and APIs.
• Seamlessly integrate open-source and commercial models into scalable translation systems.
• Enhance translation quality through fine-tuning, advanced prompt engineering, and process automation.
• Establish cost-effective and compliant translation infrastructure suitable for enterprise environments.

This instructor-led, live training in Prague (online or on-site) is designed for intermediate-level developers who want to learn how to leverage generative AI with LLMs for diverse tasks and domains.

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

• Articulate the definition and operational mechanics of generative AI.
• Describe the transformer architecture that underpins LLMs.
• Apply empirical scaling laws to optimize LLMs for specific tasks and constraints.
• Utilize cutting-edge tools and methodologies to train, fine-tune, and deploy LLMs.
• Evaluate the opportunities and risks associated with generative AI for both society and business.

Gain mastery over AI integration in Postgres through this instructor-led live training in Prague. Learn to configure extensions, implement pgvector embeddings, and connect LLMs for instant insights. Optimize queries and build intelligent systems through hands-on activities in a live-lab setting.

This instructor-led live training in Prague (online or on-site) is designed for intermediate to advanced AI developers, architects, and product managers seeking to identify and mitigate risks in LLM-powered applications. Key risk areas include prompt injection, data leakage, and unfiltered outputs, with a focus on implementing security controls such as input validation, human 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 Prague (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:

• Grasp 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 instructor-led, live training in Prague (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 Prague (online or onsite) is tailored for beginner to intermediate-level developers seeking 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 Prague (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 Prague (online or onsite) is designed for IT support professionals who want to leverage AI tools and automation platforms to streamline support processes, standardize responses, and reduce manual documentation effort.

This instructor-led, live training in Prague (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 Prague (online or onsite) is designed for intermediate-level developers, technical product teams, and AI practitioners who wish to use Hunyuan models to create multimodal applications for generating and delivering image, 3D, and video content.

By the end of this training, participants will be able to: build prompt-based workflows, generate and review multimodal assets, serve outputs through applications or APIs, and connect Hunyuan capabilities to enterprise product stacks.

Course objectives transform 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 Prague (offered online or onsite) is designed for beginner-level, intermediate-level, and advanced-level AI professionals seeking 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 architectural components, set up a basic integration, and apply security best practices.

This instructor-led, live training in Prague (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 Prague (online or onsite) is designed for intermediate-level developers, architects, and platform engineers who aim 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 versioning, resilience, and support patterns.

This instructor-led, live training in Prague (online or onsite) is aimed at intermediate-level IT leaders, compliance professionals, security teams, and enterprise architects who wish to use sovereign AI principles and governance practices to design AI environments that protect sensitive data, support localization requirements, 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.