Online Natural Language Processing (NLP) Training in Portugal

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

Upon completing this training, participants will be able to:

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

This instructor-led, live training in Portugal (online or onsite) is designed for data scientists and business analysts at an intermediate level who aim to utilise large language models (LLMs) to forecast trends and behaviours in various industries.

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

• Understand the fundamentals of LLMs and their role in predictive analytics.
• Implement LLMs to analyze and forecast data in various industries.
• Evaluate the effectiveness of predictive models using LLMs.
• Integrate LLMs with existing data processing pipelines.

This instructor-led, live training in Portugal (online or onsite) targets educators, EdTech professionals, and researchers with diverse expertise levels who wish to leverage LLMs to craft personalised educational experiences.

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

• Comprehend the architecture and capabilities of LLMs.
• Identify opportunities for personalising educational content using LLMs.
• Design adaptive learning platforms that utilise LLMs for content personalisation.
• Implement LLM-driven strategies to enhance student engagement and learning outcomes.
• Evaluate the effectiveness of LLMs in educational settings and make data-driven decisions for

This instructor-led, live training in Portugal (online or onsite) targets beginner to intermediate software developers and data scientists who wish to implement LLMs within speech recognition and synthesis systems.

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

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

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

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

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

The CANN SDK (Compute Architecture for Neural Networks) offers robust deployment and optimization utilities for real-time AI applications in computer vision and NLP, particularly on Huawei Ascend hardware.

This instructor-led live training (available online or onsite) is designed for intermediate-level AI professionals seeking to build, deploy, and optimize vision and language models using the CANN SDK for production-grade solutions.

Upon completing this training, participants will be capable of:

• Deploying and optimizing CV and NLP models utilizing CANN and AscendCL.
• Leveraging CANN utilities to convert models and integrate them into active pipelines.
• Enhancing inference performance for tasks such as detection, classification, and sentiment analysis.
• Constructing real-time CV/NLP pipelines tailored for edge or cloud-based deployment environments.

Course Format

• Interactive lectures and demonstrations.
• Practical labs focused on model deployment and performance profiling.
• Designing live pipelines using real-world CV and NLP scenarios.

Customization Options

• For those requiring customized training for this course, please contact us to arrange.

Mistral models are open-source AI technologies that have expanded into multimodal workflows, supporting both language and vision tasks for enterprise and research applications.

This instructor-led, live training (available online or onsite) targets intermediate-level ML researchers, applied engineers, and product teams looking to build multimodal applications using Mistral models, including OCR and document comprehension pipelines.

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

• Set up and configure Mistral models for multimodal tasks.
• Implement OCR workflows and integrate them with NLP pipelines.
• Design document comprehension applications for enterprise use cases.
• Develop vision-text search and assistive UI functionalities.

Format of the Course

• Interactive lecture and discussion.
• Hands-on coding exercises.
• Live-lab implementation of multimodal pipelines.

Course Customization Options

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

This instructor-led, live training in Portugal (online or onsite) is designed for intermediate-level data scientists and developers wishing to apply NLP techniques using Python in Google Colab.

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

• Understand the core concepts of natural language processing.
• Preprocess and clean text data for NLP tasks.
• Perform sentiment analysis using NLTK and SpaCy libraries.
• Work with text data using Google Colab for scalable and collaborative development.

This instructor-led, live training session in Portugal (online or onsite) is designed for intermediate-level educational technologists, instructional designers, and AI developers in the education field who seek to integrate Small Language Models (SLMs) into educational platforms to improve teaching and learning processes.

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

• Understand the role of SLMs in educational technology.
• Design AI-driven learning experiences using SLMs.
• Implement SLMs in various educational settings.
• Evaluate the effectiveness of SLMs in learning outcomes.

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 developing stateful, multi-actor LLM applications through composable graphs that maintain persistent state and provide precise control over execution workflows.

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

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

• Design and optimize complex LangGraph topologies to enhance speed, reduce costs, and improve scalability.
• Engineer reliability through the implementation of 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 them to production environments, and monitor SLAs and costs effectively.

Format of the Course

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

Course Customization Options

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

This instructor-led, live training in Portugal (online or onsite) is designed for advanced professionals seeking to fine-tune and customize AI models on Ollama for enhanced performance and domain-specific applications.

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

• Establish an efficient environment for fine-tuning AI models on Ollama.
• Prepare datasets for supervised fine-tuning and reinforcement learning.
• Optimize AI models for improved performance, accuracy, and efficiency.
• Deploy customized models within production environments.
• Evaluate model enhancements and ensure system robustness.

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 who aim to integrate, manage, and optimize AI capabilities directly within Postgres.

Upon completion of 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 LLMs with Postgres to gain real-time insights.
• Optimize Postgres to efficiently handle AI-driven queries and workflows.

Format of the Course

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

Course Customization Options

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

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

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

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

This instructor-led, live training in Portugal (online or onsite) is designed for intermediate-level software developers and AI engineers who wish to integrate Claude AI into their applications, build AI-powered chatbots, and enhance software functionality with AI-driven automation.

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

• Use the Claude AI API to integrate AI into applications.
• Develop AI-driven chatbots and virtual assistants.
• Enhance applications with AI-powered automation and NLP.
• Optimize and fine-tune Claude AI models for different use cases.

This instructor-led, live training in Portugal (online or onsite) is aimed at intermediate-level professionals who wish to deploy, optimize, and integrate LLMs using Ollama.

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

• Set up and deploy LLMs using Ollama.
• Optimize AI models for performance and efficiency.
• Leverage GPU acceleration for improved inference speeds.
• Integrate Ollama into workflows and applications.
• Monitor and maintain AI model performance over time.

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

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

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

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) is aimed at 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.

This technical course explores how to leverage Large Language Models (LLMs) to enhance code quality, minimize technical debt, and automate documentation processes within software teams.

Delivered as an instructor-led live training (available online or on-site), this programme is designed for intermediate to advanced software professionals eager to utilise LLMs, such as GPT, to analyse, refactor, and document complex or legacy codebases more efficiently.

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

• Utilise LLMs to elucidate code structures, dependencies, and logic within unfamiliar repositories.
• Spot and refactor anti-patterns to boost code readability.
• Automate the creation and upkeep of in-line comments, README files, and API documentation.
• Seamlessly integrate LLM-driven insights into existing CI/CD and code review workflows.

Course Format

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

Customisation Options

• To arrange bespoke training for this course, please get in touch with us.

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

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

• Establish a development environment with LLMs and essential tools.
• Expertly perform NLU and NLI tasks with LLMs.
• Extract, infer, and utilize knowledge graphs effectively.
• Generate and manage dialogues using LLMs for conversational applications.
• Evaluate content quality and diversity generated by LLMs and generative AI.
• Apply ethical principles, ensuring fairness and responsible use of LLMs.

This instructor-led, live training in Portugal (online or on-site) is aimed at intermediate-level data scientists and machine learning engineers who wish to create and apply small language models tailored for specific domains such as legal, medical, and technical fields.

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

• Understand the importance and application of domain-specific language models.
• Curate and preprocess specialized datasets for model training.
• Train and fine-tune language models for domain-specific applications.
• Evaluate and benchmark models using domain-relevant metrics.
• Deploy domain-specific language models in real-world scenarios.

This instructor-led, live training in Portugal (online or onsite) is aimed at intermediate-level professionals who wish to enhance their NLP projects through the effective fine-tuning of pre-trained language models.

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

• Understand the fundamentals of fine-tuning for NLP tasks.
• Fine-tune pre-trained models such as GPT, BERT, and T5 for specific NLP applications.
• Optimize hyperparameters for improved model performance.
• Evaluate and deploy fine-tuned models in real-world scenarios.

This instructor-led, live training in Portugal (online or onsite) is tailored for beginner-level business professionals, customer support teams, and technology enthusiasts eager to grasp the fundamentals of Claude AI and apply it to business contexts.

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

• Grasp Claude AI’s capabilities and practical use cases.
• Set up and interact with Claude AI effectively.
• Automate business workflows using conversational AI.
• Improve customer engagement and support through AI-driven solutions.

This instructor-led live training in Portugal (online or onsite) is designed for intermediate developers and software engineers who aim to build AI-powered applications using the LangChain framework.

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

• Understand the fundamentals of LangChain and its components.
• Integrate LangChain with large language models (LLMs) like GPT-4.
• Build modular AI applications using LangChain.
• Troubleshoot common issues in LangChain applications.

An exploration of artificial intelligence fundamentals demonstrates how intelligent technology transforms digital strategy, automation, and decision-making processes within enterprise operations. The course examines core concepts including the history of AI, problem-solving frameworks, knowledge representation, reasoning under uncertainty, and machine learning paradigms, alongside aspects of communication, perception, and autonomous action. It equips executives and architects to evaluate AI-driven transformation opportunities, assess emerging technology trends, and implement practical intelligent solutions to enhance business agility.

Artificial intelligence training covers data analysis, distributed artificial intelligence, and natural language processing. The course aims to provide developers and data scientists with the application technologies needed to build large-scale AI systems. Course content includes distributed machine learning, Apache Spark MLlib, and the core principles of MapReduce-based predictions. It also delves into practical methods for recommendation engines, text classification, semantic analysis using Word2Vec, and RNN-LSTM architectures. This course helps professionals deploy artificial intelligence pipelines suitable for production environments, transforming raw data into automated decision-making capabilities.

Claude Code is not merely a code-completion tool — it acts as a terminal-native development agent capable of reading your entire codebase, planning multi-step changes, executing tests, and driving tasks from a single instruction to a functional outcome. This one-day workshop provides participants with structured, hands-on experience: configuring Claude Code for real-world projects, writing precise delegations that yield reviewable results, leveraging CLAUDE.md as persistent project memory, and integrating internal tools via the Model Context Protocol.

This instructor-led, live training in Portugal (online or onsite) is aimed at software developers and engineering teams who wish to use Claude Code to accelerate development cycles, improve code quality, and automate repetitive programming tasks.

By the end of this training, participants will be able to install and configure Claude Code, edit multi-file codebases with natural language, leverage approval modes, and integrate with Git and CI/CD.

This instructor-led live training Portugal (online or onsite) is designed for intermediate developers, technical product teams, and AI practitioners who wish to utilise Hunyuan models to create multimodal applications for the generation and delivery of images, 3D assets, and video.

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

Natural Language Processing converts raw text into actionable intelligence, allowing machines to understand human communication. The course explores fundamental techniques including corpus analysis, sentence structure parsing, text preprocessing pipelines, and dimensionality reduction using SVD and NMF methods. Participants are guided through practical implementations of document clustering, topic modelling, sentiment analysis, named entity recognition, and Latent Dirichlet Allocation in Python. This equips practitioners with the skills to build intelligent text analytics systems for automated content classification and search.