Natural Language Processing (NLP) Training in Évora

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

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

• Comprehend the theory behind QLoRA and quantization techniques for LLMs.
• Implement QLoRA for fine-tuning large language models in domain-specific applications.
• Optimize fine-tuning performance on limited computational resources through quantization.
• Deploy and evaluate fine-tuned models in real-world applications efficiently.

This instructor-led live training in Évora (available online or onsite) targets intermediate-level data and marketing professionals who wish to apply LLMs to analyze and interpret public sentiment from various text sources such as social media posts, product reviews, and customer feedback.

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

• Understand the principles of sentiment analysis and its application using LLMs.
• Preprocess and prepare datasets for sentiment analysis.
• Train and fine-tune LLMs to accurately reflect sentiment in text.
• Analyze sentiment in real-time from social media and other text sources.
• Integrate sentiment analysis findings into business strategies and decision-making processes.

Ollama is a lightweight platform for running large language models locally.

This instructor-led, live training (online or onsite) is aimed at intermediate-level finance practitioners and IT personnel who wish to implement, customize, and operationalize Ollama-based AI solutions in financial environments.

By completing this training, participants will gain the skills needed to:

• Deploy and configure Ollama for secure use in financial operations.
• Integrate local LLMs into analytical and reporting workflows.
• Adapt models to finance-specific terminology and tasks.
• Apply security, privacy, and compliance best practices.

Format of the Course

• Interactive lecture and discussion.
• Hands-on financial data exercises.
• Live-lab implementation of finance-focused scenarios.

Course Customization Options

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

Ollama is a platform for running large language and multimodal models locally, supporting governance and responsible AI practices.

This instructor-led, live training (online or onsite) is aimed at intermediate-level to advanced-level professionals who wish to implement fairness, transparency, and accountability in Ollama-powered applications.

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

• Apply responsible AI principles in Ollama deployments.
• Implement content filtering and bias mitigation strategies.
• Design governance workflows for AI alignment and auditability.
• Establish monitoring and reporting frameworks for compliance.

Format of the Course

• Interactive lecture and discussion.
• Hands-on governance workflow design labs.
• Case studies and compliance-focused exercises.

Course Customization Options

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

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

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

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

Claude AI is an advanced language model designed to support complex analytical, strategic, and organizational tasks.

This instructor-led, live training (online or onsite) is aimed at beginner-level project management and planning professionals who wish to use Claude AI to strengthen project design, documentation, communication, and long-term planning activities.

Upon completing this training, participants will gain the ability to:

• Create project documentation such as charters, briefs, and scopes using Claude AI.
• Analyze risks, constraints, and dependencies with AI-supported reasoning.
• Develop stakeholder communications and reporting outputs tailored to different audiences.
• Use Claude AI to support sprint planning, prioritization, and roadmap refinement.

Format of the Course

• Instructor explanations combined with guided demonstrations.
• Hands-on practice using real-world project management scenarios.
• Structured exercises applying Claude AI in a live environment.

Course Customization Options

• Custom scenarios, organization-specific templates, or industry-focused workflows can be integrated upon request.

This instructor-led, live training in Évora (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.

Ollama is a platform that allows users to run large language and multimodal models locally.

This instructor-led live training (available online or onsite) is designed for intermediate practitioners seeking to master prompt engineering techniques to optimise Ollama outputs.

Upon completion, participants will be able to:

• Design effective prompts for a variety of use cases.
• Apply techniques such as priming and chain-of-thought structuring.
• Implement prompt templates and context management strategies.
• Build multi-stage prompting pipelines for complex workflows.

Course Format

• Interactive lectures and discussions.
• Hands-on exercises focused on prompt design.
• Practical implementation within a live lab environment.

Customisation Options

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

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.

This instructor-led, live training in Évora (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.

Devstral and Mistral are open-source AI technologies engineered for flexible deployment, fine-tuning capabilities, and scalable integration.

This instructor-led live training (available online or onsite) targets intermediate to advanced ML engineers, platform teams, and research engineers looking to self-host, fine-tune, and govern Mistral and Devstral models within production environments.

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

• Establish and configure self-hosted environments for Mistral and Devstral models.
• Apply fine-tuning techniques to enhance domain-specific performance.
• Implement versioning, monitoring, and lifecycle governance mechanisms.
• Ensure security, compliance, and responsible usage of open-source models.

Course Format

• Interactive lectures and discussions.
• Practical exercises focused on self-hosting and fine-tuning.
• Live-lab implementation of governance and monitoring pipelines.

Customization Options

• To request 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.

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

This instructor-led training, available online or onsite, is tailored 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 able to:

• Integrate LLM-based agents into CI/CD workflows to enable intelligent automation.
• Automate processes such as test generation, commit analysis, and change summarization using agents.
• Orchestrate multiple agents to triage alerts, generate responses, and provide DevOps recommendations.
• Develop secure and maintainable agent-driven workflows using open-source frameworks.

Course Format

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

Customization Options

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

This instructor-led, live training in Évora (online or onsite) is designed for intermediate-level professionals seeking to acquire practical expertise in automating text summarization and content generation using NLG.

Upon completing this training, participants will be capable of:

• Grasping the core principles of NLG for text summarization and content generation.
• Deploying NLG models to condense extensive documents and articles.
• Utilizing pre-trained NLG models, such as GPT, for content creation.
• Applying advanced techniques to fine-tune NLG models for specialized content generation tasks.

This instructor-led, live training in Évora (online or onsite) is aimed at developers and IT professionals of all skill levels who wish to automate tasks and processes using AI without writing extensive code.

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

• Design and implement complex workflows using n8n's visual programming interface.
• Integrate AI capabilities into workflows using LangChain.
• Build custom chatbots and virtual assistants for various use cases.
• Perform advanced data analysis and processing with AI agents.

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 Évora (online or onsite) is designed for advanced professionals interested in exploring the latest techniques in NLU and semantic understanding.

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

• Comprehend the principles of semantic understanding and contextual AI.
• Work with state-of-the-art models like transformers and pre-trained language models.
• Implement NLU techniques for improved AI language comprehension.
• Develop applications that leverage semantic analysis and contextual AI.

This instructor-led, live training in Évora (online or onsite) is aimed at advanced-level professionals who wish to master AI-driven NLG techniques for chatbot and virtual assistant applications.

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

• Understand the core principles of NLG for conversational AI.
• Leverage deep learning techniques to enhance chatbot dialogue generation.
• Integrate state-of-the-art NLG models like GPT-3 into chatbot frameworks.
• Apply contextual AI for improving conversational coherence and fluidity.

This instructor-led, live training in Évora (online or onsite) targets intermediate-level data scientists and AI researchers aiming to create engaging and efficient AI-powered conversational experiences using small language models.

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

• Grasping the core principles of conversational AI and understanding the specific role of SLMs.
• Designing and implementing user-centric AI interactions.
• Developing and training SLMs for interactive applications.
• Assessing and enhancing the effectiveness of human-AI communication through suitable metrics.
• Deploying scalable and ethical AI-driven conversational interfaces in real-world contexts.

Devstral is an open-source framework engineered to build and operate coding agents capable of interacting with codebases, developer tools, and APIs to boost engineering productivity.

This instructor-led live training (available online or onsite) targets intermediate to advanced-level ML engineers, developer-tooling teams, and SREs who aim to design, implement, and optimize coding agents using Devstral.

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

• Configure and set up Devstral for coding agent development.
• Design agentic workflows tailored for codebase exploration and modification.
• Integrate coding agents seamlessly with developer tools and APIs.
• Apply best practices for secure and efficient agent deployment.

Course Format

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

Customization Options

• For personalized training requests, please contact us to arrange.

This instructor-led, live training in Évora (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 Évora (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.

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.

This 2-step training programme is designed for software delivery teams that want to integrate AI-assisted engineering workflows into their day-to-day activities using Claude Code.

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

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.

This intensive 2-day programme is tailored for professionals aiming to evolve from using AI merely as a casual chatbot to embedding it as an indispensable digital work partner.

The course combines strategic theoretical insights (fully aligned with the 2026 AI landscape) with extensive practical application, featuring 9 hands-on exercises directly applied to participants' real-world business scenarios.

• Day 1 (In-Person): Mastering the Anthropic Ecosystem. Focuses on advanced prompting techniques, profile personalization (Custom Instructions), and leveraging persistent workspaces (Projects, Artifacts, Skills) to manage internal knowledge bases.
• Day 2 (Online): Automation and Ecosystem Integration. Focuses on running Claude in the background via Cowork features, the MCP (Model Context Protocol) ecosystem, and seamless, native integration with the Microsoft 365 suite (Word, Excel, PowerPoint, Teams, SharePoint, and OneDrive).

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.

Ollama is an open-source tool for running large language models locally on consumer and enterprise hardware. It abstracts model quantization, GPU allocation, and API serving into a single command-line interface, enabling organizations to self-host LLMs like Llama, Mistral, and Qwen without sending prompts or data to OpenAI, Anthropic, or Google.