Large Language Models (LLMs) Training in Nicosia

This instructor-led, live training in Nicosia (online or onsite) is designed for senior management professionals eager to understand LLMs, 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:

• Comprehend what LLMs are and how tools like ChatGPT and Copilot operate.
• Apply prompting techniques to obtain practical and reliable results from LLMs.
• Assess real-world use cases, including email drafting, document summarization, and productivity automation.
• Identify investment opportunities and strategic applications for AI adoption.

This instructor-led, live training in Nicosia (online or onsite) is designed for senior management teams seeking to understand the strategic value of LLMs and enterprise AI tools. Participants will explore how to integrate these tools into high-level workflows, craft effective prompts, and assess opportunities for enhanced 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 Nicosia (online or on-site) is designed for intermediate to advanced AI researchers, data scientists, and developers who aim to understand, fine-tune, and implement Meta AI's Large Language Models for various NLP applications.

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

• Understand the architecture and functionality 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 Nicosia (online or onsite) targets intermediate-level AI professionals, business analysts, and technology leaders seeking to understand generative AI principles and LLM applications in business contexts. Participants will study transformers, prompt engineering, and the ethical aspects of deploying these models for real-world solutions.

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

• Grasp 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 Nicosia (online or onsite) is designed for intermediate-level AI professionals, ethicists, data scientists, engineers, and policy makers or stakeholders seeking to understand and navigate the ethical landscape of LLMs.

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

• Identify the 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 Nicosia (online or onsite) is tailored for intermediate-level NLP practitioners and data scientists, content creators and translators, and global businesses wishing to utilise LLMs for language translation and multilingual content creation.

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

• Grasp the principles of cross-lingual learning and translation with LLMs.
• Implement LLMs for translating content between diverse languages.
• Create and manage multilingual datasets for training LLMs.
• Formulate strategies to uphold consistency and quality in translation.

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

Upon completing this training, participants will be able to:

• Grasp how LLMs are applied in financial market analysis.
• Leverage LLMs to analyze financial news, reports, and data to derive market insights.
• Construct predictive models for stock prices, market trends, and economic indicators.
• Incorporate LLM-generated insights into investment decision-making workflows.

This live, instructor-led training in Nicosia (online or onsite) targets intermediate-level environmental scientists, researchers, data analysts, and policy makers or advocates interested in using LLMs for environmental modeling and analysis.

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

• Grasp how LLMs are applied within environmental science.
• Leverage 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, delivered in Nicosia (online or onsite), is designed for intermediate-level VR and AR developers, game designers, and AI engineers who wish to integrate 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 Nicosia (online or on-site) is tailored for intermediate-level data scientists, machine learning engineers, and software developers who aim 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 guided, live training session in Nicosia (online or on-site) targets intermediate-level cybersecurity experts and data scientists looking to leverage LLMs to improve security measures and threat intelligence capabilities.

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

• Grasping the function of LLMs within the cybersecurity domain.
• Deploying LLMs for the detection and analysis of threats.
• Applying LLMs to automate security processes and response mechanisms.
• Connecting LLMs with current security infrastructure.

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

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

• Grasp the core principles of LLMs and their application within predictive analytics.
• Deploy LLMs to analyze and predict data trends in diverse industries.
• Assess the efficacy of predictive models constructed using LLMs.
• Seamlessly integrate LLMs into current data processing workflows.

This instructor-led, live training in Nicosia (online or onsite) is designed for intermediate-level data scientists who wish to acquire 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 [Greece] (available online or onsite) targets intermediate-level content creators, marketers, and educational technologists who wish to leverage LLMs to produce 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 Nicosia (online or onsite) is designed for educators, EdTech professionals, and researchers with varying levels of experience who wish to leverage LLMs to create personalized educational experiences.

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

• Understand the architecture and capabilities of LLMs.
• Identify opportunities for personalizing educational content using LLMs.
• Design adaptive learning platforms that utilize LLMs for content personalization.
• 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 improvements.

This live, instructor-led training in Nicosia (available online or onsite) is designed for intermediate-level ML practitioners and AI developers looking 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 Nicosia (online or onsite) targets 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:

• Grasp the role of LLMs within speech technologies.
• Implement LLMs for accurate speech recognition and natural-sounding speech synthesis.
• Integrate LLMs with speech recognition engines and speech synthesizers.
• Evaluate and enhance the performance of speech systems using LLMs.
• Stay informed about current trends and future directions in speech technologies.

This instructor-led, live training in Nicosia (online or onsite) is designed for beginner to intermediate-level customer support and IT professionals who wish to apply LLMs to build responsive and intelligent customer support chatbots.

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

• Comprehend 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 Nicosia (available online or onsite) targets intermediate-level data scientists and AI engineers seeking to fine-tune large language models more affordably and efficiently using techniques like LoRA, Adapter Tuning, and Prefix Tuning.

By the conclusion 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.

This instructor-led, live training in Nicosia (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 Nicosia (online or onsite) is designed for intermediate-level data and marketing professionals aiming to leverage LLMs to analyze and interpret public sentiment across diverse text sources, including social media posts, product reviews, and customer feedback.

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

• Grasp the core principles of sentiment analysis and its application via LLMs.
• Preprocess and prepare datasets tailored for sentiment analysis.
• Train and fine-tune LLMs to accurately capture sentiment within text.
• Analyze sentiment in real-time from social media and other textual sources.
• Integrate insights from sentiment analysis into business strategies and decision-making frameworks.

This instructor-led, live training in Nicosia (online or onsite) is designed for intermediate-level software developers and technical writers who aim to leverage 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 Nicosia (online or onsite) targets 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 Nicosia (online or on-site) targets intermediate to advanced developers and data scientists seeking to master LlamaIndex for the development of 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 Nicosia (online or onsite) is designed for intermediate-level AI researchers, machine learning professionals, and data scientists who wish to utilise 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 session (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 conclusion of this training, participants will be able to:

• Understand the fundamental 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 serves as a framework designed to construct stateful, multi-agent LLM applications through composable graphs that maintain persistent state and offer precise control over execution processes.

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

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

• Designing legal-specific LangGraph workflows that ensure auditability and compliance.
• Integrating legal ontologies and document standards into graph state and processing mechanisms.
• Implementing guardrails, human-in-the-loop approvals, and traceable decision pathways.
• Deploying, monitoring, and maintaining LangGraph services in production environments with effective observability and cost management.

Format of the Course

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

Course Customization Options

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

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

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

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

AI for SQL involves the application of 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 onsite) is designed for intermediate-level data engineers and technical leads who aim to integrate AI capabilities into SQL workflows to facilitate natural language querying, intelligent optimization, and automated data analysis.

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

• Integrate LLMs such as GPT, DeepSeek, LLaMA, Qwen, and Mistral into SQL environments.
• Construct 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.

Course Format

• Interactive lecture and discussion.
• Extensive exercises and practice.
• Hands-on implementation in a live-lab environment.

Course Customization Options

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

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

This instructor-led training, available either online or onsite, targets intermediate to advanced professionals seeking to design, implement, and manage LangGraph-based financial solutions with appropriate governance, observability, and compliance standards.

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

• Designing finance-specific LangGraph workflows that align with regulatory and audit requirements.
• Integrating financial data standards and ontologies into graph states and tooling.
• Implementing reliability, safety measures, and human-in-the-loop controls for critical processes.
• Deploying, monitoring, and optimizing LangGraph systems for performance, cost efficiency, and service level agreements (SLAs).

Course Format

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

Customization Options

• To request a tailored version of this course, please contact us to make arrangements.

Vertex AI equips developers with robust tools to construct multimodal LLM workflows that seamlessly integrate text, audio, and image data into a unified pipeline. Leveraging support for long context windows and configurable Gemini API parameters, it facilitates the creation of sophisticated applications focused on planning, reasoning, and cross-modal intelligence.

This instructor-led live training, available both online and onsite, is designed for intermediate to advanced practitioners eager to design, build, and optimize multimodal AI workflows within the Vertex AI ecosystem.

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.
• Architect pipelines that effectively integrate text, audio, and image analysis.
• Optimize Gemini API parameters to enhance performance and cost-efficiency.

Course Format

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

Customization Options

• For customized training options for this course, please contact us to arrange details.

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

This instructor-led live training, available both online and onsite, targets intermediate to advanced-level professionals aiming to design, implement, and manage LangGraph-based healthcare solutions while navigating regulatory, ethical, and operational challenges.

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

• Design healthcare-specific LangGraph workflows with a focus on compliance and auditability.
• Integrate LangGraph applications with medical ontologies and standards 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.

Format of the Course

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

Course Customization Options

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

This instructor-led, live training (available online or onsite) targets intermediate-level AI developers and localization engineers seeking to design scalable, automated translation pipelines using proprietary and open-source LLMs.

By the end 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 designed for constructing stateful, multi-agent LLM applications through composable graphs, featuring persistent state and precise control over execution flows.

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

Upon completing this training, participants will be capable of:

• Designing and optimizing complex LangGraph topologies to enhance speed, reduce costs, and improve scalability.
• Ensuring reliability through retries, timeouts, idempotency, and checkpoint-based recovery mechanisms.
• Debugging and tracing graph executions, inspecting states, and systematically reproducing production issues.
• Instrumenting graphs with logs, metrics, and traces, deploying them to production, and monitoring SLAs and costs.

Course Format

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

Customization Options

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

This instructor-led, live training in Nicosia (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.

Large language models (LLMs) and autonomous agent frameworks such as AutoGen and CrewAI are transforming the way DevOps teams automate tasks like change tracking, test generation, and alert triage by emulating human-like collaboration and decision-making processes.

This instructor-led, live training (available online or onsite) is designed for advanced-level engineers who aim to design and implement DevOps automation workflows powered by large language models (LLMs) and multi-agent systems.

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

• Integrate LLM-based agents into CI/CD workflows for intelligent automation.
• Automate test generation, commit analysis, and change summaries using agents.
• Coordinate multiple agents for triaging alerts, generating responses, and providing DevOps recommendations.
• Build secure and maintainable agent-powered workflows using open-source frameworks.

Format of the Course

• Interactive lecture and discussion.
• Extensive exercises and practice.
• Hands-on implementation in a live-lab environment.

Course Customization Options

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

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

This instructor-led live training, available both online and onsite, is designed for intermediate-level database professionals and developers aiming to integrate, manage, and optimize AI capabilities directly within Postgres.

Upon completing this course, participants will be equipped to:

• Configure Postgres extensions specifically for AI workloads.
• Implement embeddings and similarity search functionalities using pgvector.
• Integrate both open-source and proprietary Large Language Models (LLMs) with Postgres to derive real-time insights.
• Optimize Postgres performance to efficiently handle AI-driven queries and workflows.

Course Format

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

Course Customization Options

• For customized training arrangements, please contact us directly.

This instructor-led, live training in Nicosia (online or onsite) is aimed at intermediate-level to advanced-level AI developers, architects, and product managers who wish to identify and mitigate risks associated with LLM-powered applications, including prompt injection, data leakage, and unfiltered output, while incorporating security controls like 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.

LangGraph is a graph-based orchestration framework designed to facilitate conditional, multi-step workflows involving LLMs and tools, making it ideal for automating and personalizing content pipelines.

This instructor-led live training (available online or onsite) is tailored for intermediate-level marketers, content strategists, and automation developers aiming 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 enable automated personalization.
• Managing state, memory, and context across 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

• For requests regarding customized training for this course, please contact us to arrange details.

This instructor-led, live training in Nicosia (online or onsite) is designed for 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:

• 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.

LangGraph is a framework designed for composing graph-structured workflows involving Large Language Models (LLMs), supporting features such as branching, tool integration, memory management, and controllable execution.

This instructor-led, live training (available online or onsite) is tailored for intermediate-level engineers and product teams aiming to merge LangGraph’s graph logic with LLM agent loops to create dynamic, context-aware applications like customer support assistants, decision trees, and information retrieval systems.

Upon completing this training, participants will be capable of:

• Designing graph-based workflows that coordinate LLM agents, tools, and memory.
• Implementing conditional routing, retries, and fallback mechanisms to ensure robust execution.
• Integrating retrieval systems, APIs, and structured outputs into agent loops.
• Evaluating, monitoring, and securing agent behavior to enhance reliability and safety.

Course Format

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

Customization Options

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

‘Large Language Models for Code Comprehension, Refactoring, and Documentation’ is a specialized technical course designed to demonstrate how organizations can 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 both online and onsite, targets intermediate to advanced software professionals looking to utilize LLMs, such as GPT, to more efficiently analyze, refactor, and document complex or legacy codebases.

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

• Utilize LLMs to clarify code, dependencies, and logical structures within unfamiliar repositories.
• Spot and refactor anti-patterns to enhance code readability.
• Automatically generate and upkeep inline comments, README files, and API documentation.
• Embed LLM-derived insights into established CI/CD and code review workflows.

Course Format

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

Customization Options

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

This instructor-led, live training in Nicosia (online or onsite) is designed for intermediate-level data scientists, AI developers, and AI enthusiasts who aim to leverage LLMs for various NLP tasks and to create novel, diverse content for specific applications.

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

• Set up a development environment equipped with LLMs and essential tools.
• Expertly execute NLU and NLI tasks using LLMs.
• Effectively extract, infer, and utilize knowledge graphs.
• Generate and manage dialogues using LLMs for conversational applications.
• Evaluate the quality and diversity of content generated by LLMs and generative AI.
• Apply ethical principles to ensure fairness and responsible use of LLMs.

LangGraph is a framework designed for constructing LLM applications with a graph structure, supporting planning, branching, tool usage, memory, and controllable execution.

This instructor-led, live training (available online or on-site) is targeted at beginner-level developers, prompt engineers, and data practitioners aiming to design and build reliable, multi-step LLM workflows using LangGraph.

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

• Explain core LangGraph concepts (nodes, edges, state) and when to use them.
• Build prompt chains that branch, call tools, and maintain memory.
• Integrate retrieval and external APIs into graph workflows.
• Test, debug, and evaluate LangGraph apps for reliability and safety.

Format of the Course

• Interactive lecture and facilitated discussion.
• Guided labs and code walkthroughs in a sandbox environment.
• Scenario-based exercises on design, testing, and evaluation.

Course Customization Options

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

This instructor-led, live training session Nicosia (online or onsite) targets beginner to intermediate-level developers seeking to utilize Large Language Models for various natural language tasks.

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

• Establish a development environment integrated with a popular LLM.
• Construct a foundational LLM and fine-tune it using custom datasets.
• Apply LLMs to diverse natural language tasks, such as summarizing text, answering questions, and generating content.
• Debug and evaluate LLM performance utilizing tools like TensorBoard, PyTorch Lightning, and Hugging Face Datasets.

This instructor-led, live training in Nicosia (online or onsite) targets intermediate-level engineers and architects who wish to utilize Tencent Hunyuan to deploy large and MoE models with reduced latency, enhanced throughput, and tighter 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 Nicosia (online or onsite) targets intermediate-level developers, technical product teams, and AI practitioners aiming to utilize Hunyuan models for creating multimodal applications that generate and deliver images, 3D assets, and video content.

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

This instructor-led, live training in Nicosia (online or onsite) is aimed at beginner-level / intermediate-level / 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 good practices.

This instructor-led, live training in Nicosia (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 session in Nicosia (offered online or onsite) targets intermediate-level developers, architects, and platform engineers keen to utilise MCP for building reliable servers and clients suited for enterprise deployment and operational management.

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

This instructor-led, live training in Nicosia (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.