Large Language Models (LLMs) Training in Espírito Santo

This instructor-led, live training in Espírito Santo (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 use of AI tools such as ChatGPT, Microsoft Copilot, or Grok for real-world tasks like content creation, data summarization, and decision support.

Upon completing this training, participants will be able to:

• Understand what LLMs are and how tools like ChatGPT and Copilot function.
• Apply prompting techniques to achieve practical and reliable results from LLMs.
• Assess real-world use cases such as email drafting, summarizing documents, and automating productivity tasks.
• Identify investment opportunities and strategic applications for adopting AI.

This live, instructor-led training in Espírito Santo (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 better prompts, and evaluate opportunities to increase 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 Espírito Santo (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 diverse NLP applications.

Upon completion 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, including text summarization, chatbots, and sentiment analysis.
• Optimize and deploy large language models efficiently.

This instructor-led, live training in Espírito Santo (online or onsite) is designed for intermediate-level AI professionals, business analysts, and technology leaders seeking to understand the principles of generative AI and the applications of LLMs in business settings. Participants will explore 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:

• 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 Espírito Santo (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 Espírito Santo (online or onsite) is designed for intermediate-level NLP practitioners, data scientists, content creators, translators, and global businesses that wish to leverage LLMs for language translation and multilingual content development.

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

• Grasp the principles of cross-lingual learning and translation using LLMs.
• Deploy LLMs to translate content between various languages.
• Build and manage multilingual datasets for training LLMs.
• Develop strategies to ensure consistency and quality in translation.

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

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

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

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

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

• Understand the application of LLMs in environmental science.
• Utilize LLMs to analyze and model environmental data.
• Interpret LLM outputs for environmental impact assessments.
• Communicate findings effectively to inform policy and conservation efforts.

This instructor-led, live training in Espírito Santo (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 instructor-led, live training in Espírito Santo (online or onsite) is aimed at 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 Espírito Santo (online or onsite) is aimed at intermediate-level cybersecurity professionals and data scientists who wish to utilize LLMs for enhancing cybersecurity measures and threat intelligence.

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

• Understand the role of LLMs in cybersecurity.
• Implement LLMs for threat detection and analysis.
• Utilize LLMs for security automation and response.
• Integrate LLMs with existing security infrastructure.

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

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

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

This instructor-led, live training in Espírito Santo (online or onsite) is tailored for intermediate-level data scientists who seek a thorough understanding and practical proficiency in both Large Language Models (LLMs) and Reinforcement Learning (RL).

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

• Comprehending the components and operational mechanics of transformer models.
• Optimizing and fine-tuning LLMs for targeted tasks and applications.
• Grasping the fundamental principles and methodologies underpinning reinforcement learning.
• Understanding how reinforcement learning techniques can augment the performance of LLMs.

This instructor-led, live training in Espírito Santo (online or on-site) is designed for intermediate-level content creators, marketers, and educational technologists who wish to utilize LLMs to generate high-quality, diverse, and engaging content across multiple 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 Espírito Santo (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 Espírito Santo (online or onsite) is designed for intermediate-level machine learning practitioners and AI developers who aim to fine-tune and deploy open-weight models, such as LLaMA, Mistral, and Qwen, for specific business or internal applications.

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

• Grasp the ecosystem and distinctions among various open-source LLMs.
• Prepare datasets and configure fine-tuning settings for models like LLaMA, Mistral, and Qwen.
• Execute fine-tuning pipelines utilizing Hugging Face Transformers and PEFT.
• Evaluate, save, and deploy fine-tuned models within secure environments.

This instructor-led, live training in Espírito Santo (online or onsite) is designed for beginner to intermediate software developers and data scientists who wish to implement LLMs in speech recognition and synthesis systems.

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

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

This instructor-led, live training in Espírito Santo (online or onsite) is aimed at beginner-level to intermediate-level customer support and IT professionals who wish to implement LLMs to create responsive and intelligent customer support chatbots.

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

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

This guided, live training in Espírito Santo (online or in-person) targets intermediate-level data scientists and AI engineers who wish to fine-tune large language models more affordably and efficiently using methods like LoRA, Adapter Tuning, and Prefix Tuning.

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

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

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

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

• Install and configure LlamaIndex for use with LLMs.
• Index and query custom datasets using LlamaIndex to enhance LLM functionality.
• Design and develop sophisticated applications that utilize LlamaIndex and LLMs.
• Understand and apply best practices for working with LLMs and LlamaIndex.
• Navigate the ethical considerations involved in deploying LLM-powered applications.

This instructor-led, live training in Espírito Santo (online or onsite) is aimed at intermediate-level AI researchers, machine learning professionals, and data scientists who wish to use LlamaIndex to enhance the capabilities of AI models, making them more accurate and reliable for various applications.

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

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

This instructor-led, live training in Espírito Santo (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.

LangGraph is a framework designed for creating stateful, multi-actor LLM applications by composing graphs that maintain persistent state and offer precise execution control.

This instructor-led live training, available online or onsite, targets intermediate to advanced professionals seeking to design, implement, and manage LangGraph-based legal solutions 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.
• Implementing guardrails, human-in-the-loop approvals, and traceable decision paths.
• Deploying, monitoring, and maintaining LangGraph services in production environments with observability and cost controls.

Course Format

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

Customization Options

• For customized training on this topic, please contact us to arrange a session.

This instructor-led, live training (online or onsite) is aimed at advanced-level engineers, AI specialists, and localization leads who wish to implement large language model (LLM) systems for automated translation, quality evaluation, and enterprise governance.

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

• Build enterprise-grade LLM localization pipelines integrating open and proprietary models.
• Implement automated QA workflows and quality metrics for translation consistency.
• Establish governance and approval frameworks for multilingual content production.
• Deploy scalable, auditable LLM-based localization systems in secure environments.

AI for SQL involves applying artificial intelligence and large language models (LLMs) to automate, optimize, and improve how SQL queries are generated, executed, and interpreted in enterprise data environments.

This instructor-led, live training (available online or onsite) targets intermediate-level data engineers and technical leads who want to integrate AI capabilities into SQL workflows to enable natural language querying, intelligent optimization, and automated data analysis.

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

• Integrate LLMs such as GPT, DeepSeek, LLaMA, Qwen, and Mistral into SQL environments.
• Develop 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 lectures and discussions.
• Numerous exercises and practice sessions.
• Hands-on implementation in a live lab environment.

Course Customization Options

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

LangGraph is a framework designed for constructing stateful, multi-actor LLM applications as composable graphs, featuring persistent state and granular control over execution flow.

This instructor-led, live training (available online or on-site) targets intermediate to advanced professionals aiming to design, implement, and manage LangGraph-based financial solutions with robust governance, observability, and compliance.

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

• Design finance-specific LangGraph workflows that align with regulatory and audit standards.
• Integrate financial data standards and ontologies into graph state and tooling.
• Implement reliability, safety, and human-in-the-loop controls for critical processes.
• Deploy, monitor, and optimize LangGraph systems to ensure optimal performance, cost-efficiency, and SLA adherence.

Course Format

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

Customization Options

• For customized training requests, please contact us to arrange a session.

Vertex AI offers robust tools for constructing multimodal LLM workflows that seamlessly integrate text, audio, and image data into a unified pipeline. Supported by long context window capabilities and configurable Gemini API parameters, it facilitates the development of sophisticated applications focused on planning, reasoning, and cross-modal intelligence.

This instructor-led, live training (available online or onsite) is designed for intermediate to advanced practitioners aiming to design, build, and optimize multimodal AI workflows within Vertex AI.

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

• Utilize Gemini models to handle multimodal inputs and outputs.
• Implement long-context workflows to address complex reasoning tasks.
• Design pipelines that combine text, audio, and image analysis.
• Optimize Gemini API parameters to enhance performance and cost efficiency.

Course Format

• Interactive lectures and discussions.
• Practical labs involving multimodal workflows.
• Project-based exercises focused on applied multimodal use cases.

Customization Options

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

LangGraph empowers stateful, multi-actor workflows driven by LLMs, offering precise control over execution paths and state persistence. These capabilities are vital in healthcare for ensuring compliance, interoperability, and developing decision-support systems that align with clinical workflows.

This instructor-led, live training (available online or onsite) is designed for intermediate to advanced professionals seeking to design, implement, and manage LangGraph-based healthcare solutions while addressing regulatory, ethical, and operational challenges.

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

• Design healthcare-specific LangGraph workflows with compliance and auditability in mind.
• Integrate LangGraph applications with medical ontologies and standards (FHIR, SNOMED CT, 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 (online or onsite) is aimed at intermediate-level AI developers and localization engineers who wish to design scalable, automated translation pipelines using both 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 for constructing stateful, multi-agent LLM applications by utilizing composable graphs that maintain persistent state and precise control over execution flow.

This instructor-led live training, available both online and onsite, is tailored for advanced AI platform engineers, AI-focused DevOps professionals, and ML architects aiming to optimize, debug, monitor, and operate production-grade LangGraph systems.

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

• Design and optimize complex LangGraph topologies to enhance speed, manage costs, and ensure scalability.
• Ensure system reliability through retries, timeouts, idempotency, and checkpoint-based recovery mechanisms.
• Debug and trace graph executions, inspect state variables, and systematically reproduce production issues.
• Instrument graphs with logs, metrics, and traces; deploy to production environments; and monitor SLAs and costs effectively.

Course Format

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

Course Customization Options

• For those interested in customizing this training to fit specific needs, please contact us to arrange a tailored session.

This instructor-led, live training Espírito Santo (online or on-site) is designed for intermediate-level developers who want to learn how to utilize 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 how DevOps teams automate tasks like change tracking, test generation, and alert triage by mimicking human-like collaboration and decision-making.

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

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

• Integrating LLM-based agents into CI/CD workflows for intelligent automation.
• Automating test generation, commit analysis, and change summaries through agents.
• Coordinating multiple agents to triage alerts, generate responses, and provide DevOps recommendations.
• Building secure and maintainable agent-powered workflows using open-source frameworks.

Course Format

• Interactive lectures and discussions.
• Numerous exercises and practical activities.
• Hands-on implementation in a live laboratory environment.

Course Customization Options

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

Postgres is a sophisticated open-source relational database that serves as a robust foundation for AI-driven systems and data intelligence applications.

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

Upon completing this training, participants will be able to:

• Set up and configure Postgres extensions tailored for AI workloads.
• Implement embeddings and perform similarity searches using pgvector.
• Integrate both open-source and proprietary Large Language Models (LLMs) with Postgres to gain real-time insights.
• Optimize Postgres to effectively 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.

Customization Options

• To request a customized version of this course, please contact us to arrange your training.

This instructor-led live training in Espírito Santo (online or onsite) is designed for AI developers, architects, and product managers at an intermediate to advanced level. The course focuses on helping participants identify and mitigate risks associated with LLM-powered applications, including prompt injection, data leakage, and unfiltered outputs, while incorporating security controls like input validation, human-in-the-loop oversight, and output guardrails.

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

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

LangGraph is a graph-based orchestration framework that enables conditional, multi-step LLM and tool workflows, ideal for automating and personalizing content pipelines.

This instructor-led, live training (online or onsite) is aimed at intermediate-level marketers, content strategists, and automation developers who wish to implement dynamic, branching email campaigns and content generation pipelines using LangGraph.

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

• Design graph-structured content and email workflows with conditional logic.
• Integrate LLMs, APIs, and data sources for automated personalization.
• Manage state, memory, and context across multi-step campaigns.
• Evaluate, monitor, and optimize workflow performance and delivery outcomes.

Format of the Course

• Interactive lectures and group discussions.
• Hands-on labs implementing email workflows and content pipelines.
• Scenario-based exercises on personalization, segmentation, and branching logic.

Course Customization Options

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

This instructor-led, live training in Espírito Santo (online or onsite) is aimed at intermediate-level to advanced-level professionals who wish to customize pre-trained models for specific tasks and datasets.

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

• Understand the principles of fine-tuning and its applications.
• Prepare datasets for fine-tuning pre-trained models.
• Fine-tune large language models (LLMs) for NLP tasks.
• Optimize model performance and address common challenges.

LangGraph is a framework designed for composing graph-structured LLM workflows that support branching, tool use, memory, and controllable execution.

This instructor-led, live training (online or onsite) targets intermediate-level engineers and product teams who wish to combine LangGraph’s graph logic with LLM agent loops to build dynamic, context-aware applications such as customer support agents, decision trees, and information retrieval systems.

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

• Design graph-based workflows that coordinate LLM agents, tools, and memory.
• Implement conditional routing, retries, and fallbacks for robust execution.
• Integrate retrieval, APIs, and structured outputs into agent loops.
• Evaluate, monitor, and harden agent behavior for reliability and safety.

Format of the Course

• Interactive lecture and facilitated discussion.
• Guided labs and code walkthroughs in a sandbox environment.
• Scenario-based design exercises and peer reviews.

Course Customization Options

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

LLMs for Code Understanding, Refactoring, and Documentation is a technical course focused on applying large language models (LLMs) to improve code quality, reduce technical debt, and automate documentation tasks across software teams.

This instructor-led, live training (online or onsite) is aimed at intermediate-level to advanced-level software professionals who wish to use LLMs such as GPT to analyze, refactor, and document complex or legacy codebases more effectively.

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

• Use LLMs to explain code, dependencies, and logic in unfamiliar repositories.
• Identify and refactor anti-patterns and improve code readability.
• Automatically generate and maintain in-line comments, README files, and API documentation.
• Integrate LLM-driven insights into existing CI/CD and review workflows.

Format of the Course

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

Course Customization Options

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

This instructor-led live training in Espírito Santo (online or onsite) is designed for intermediate-level data scientists, AI developers, and AI enthusiasts who want to utilize 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:

• Set up a development environment equipped with LLMs and essential tools.
• Proficiently execute NLU and NLI tasks using LLMs.
• Effectively extract, infer, and apply knowledge graphs.
• Create and manage dialogues with LLMs for conversational applications.
• Assess the quality and diversity of content generated by LLMs and generative AI.
• Implement ethical principles to ensure fairness and responsible LLM usage.

LangGraph is a framework designed for developing LLM applications structured as graphs, featuring capabilities for planning, branching, tool usage, memory management, and controllable execution.

This instructor-led live training, available online or on-site, targets beginner-level developers, prompt engineers, and data practitioners who aim to design and build reliable, multi-step LLM workflows using LangGraph.

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

• Explain core LangGraph concepts (nodes, edges, state) and their appropriate use cases.
• Construct prompt chains that branch, invoke tools, and maintain memory.
• Integrate retrieval mechanisms and external APIs into graph-based workflows.
• Test, debug, and evaluate LangGraph applications to ensure reliability and safety.

Course Format

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

Course Customization Options

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

This instructor-led, live training in Espírito Santo (online or onsite) is designed for beginner to intermediate-level developers who wish to leverage Large Language Models for a variety of natural language tasks.

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

• Configure a development environment that incorporates a popular LLM.
• Construct a basic LLM and fine-tune it using a custom dataset.
• Apply LLMs to diverse natural language tasks such as text summarization, question answering, and text generation.
• Debug and evaluate LLMs utilizing tools like TensorBoard, PyTorch Lightning, and Hugging Face Datasets.

This instructor-led, live training in Espírito Santo (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 Espírito Santo (online or onsite) targets intermediate developers, technical product teams, and AI practitioners aiming to use Hunyuan models to create and deliver multimodal applications for image, 3D, and video generation.

By the end of this training, participants will be capable of building prompt-based workflows, generating and reviewing multimodal assets, serving outputs through apps or APIs, and connecting Hunyuan capabilities to enterprise product stacks.

This instructor-led, live training in Espírito Santo (online or onsite) is aimed at beginner-level, intermediate-level, and 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 Espírito Santo (online or in person) 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 Espírito Santo (online or onsite) targets intermediate-level developers, architects, and platform engineers aiming to utilize MCP to construct reliable servers and clients for enterprise deployment and operations.

By the end of this training, participants will be capable of: explaining MCP architecture in practice, building production-ready integrations, deploying and monitoring MCP services, and applying patterns for versioning, resilience, and support.

This instructor-led, live training in Espírito Santo (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 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.