Natural Language Processing (NLP) Training in Almada

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

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

• Understand the architecture and functioning 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 Almada (online or on-site) is designed for intermediate NLP practitioners, data scientists, content creators, translators, and global businesses aiming to leverage LLMs for language translation and multilingual content production.

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

• Grasp the fundamentals of cross-lingual learning and translation using LLMs.
• Deploy LLMs to translate content between multiple languages.
• Generate and manage multilingual datasets for training LLMs.
• Formulate strategies to ensure consistency and high quality in translation outcomes.

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

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 lightweight platform designed for running large language models locally.

This instructor-led live training (available online or onsite) is designed for intermediate-level healthcare practitioners and IT teams looking to deploy, customize, and operationalize Ollama-based AI solutions within clinical and administrative settings.

Upon completing this training, participants will be able to:

• Install and configure Ollama for secure use in healthcare environments.
• Integrate local LLMs into clinical workflows and administrative processes.
• Customize models for healthcare-specific terminology and tasks.
• Apply best practices for privacy, security, and regulatory compliance.

Course Format

• Interactive lectures and discussions.
• Hands-on demonstrations and guided exercises.
• Practical implementation in a sandboxed healthcare simulation environment.

Customization Options

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

This instructor-led, live training in Almada (online or onsite) is aimed at intermediate-level to advanced-level developers and data scientists who wish to master LlamaIndex for developing innovative LLM-powered applications.

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

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

This instructor-led, live training in Almada (online or onsite) is aimed at advanced-level AI researchers and policy makers who wish to explore the ethical implications of AI development and learn how to apply ethical guidelines when building AI solutions with LangChain.

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

• Identify key ethical issues in AI development with LangChain.
• Understand the impact of AI on society and decision-making processes.
• Develop strategies for building fair and transparent AI systems.
• Implement ethical AI guidelines into LangChain-based projects.

This instructor-led, live training in Almada (online or onsite) is aimed at intermediate-level web developers and UX designers who wish to leverage LangChain to create intuitive and user-friendly web applications.

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

• Understand the fundamental concepts of LangChain and its role in enhancing web user experience.
• Implement LangChain in web apps to create dynamic and responsive interfaces.
• Integrate APIs into web apps to improve interactivity and user engagement.
• Optimize user experience using LangChain’s advanced customization features.
• Analyze user behavior data to fine-tune web app performance and experience.

This instructor-led, live training in Almada (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.

Claude AI is a generative artificial intelligence system engineered to aid in complex reasoning, content creation, information retrieval, and the automation of business workflows.

This guided training session, available both online and in-person, targets professionals at an introductory level who aim to integrate Claude AI into customer support and service delivery tasks.

After finishing this programme, participants will be equipped to:

• Utilise Claude to speed up support triage and classification processes.
• Generate customer responses and summaries that maintain a consistent tone.
• Automate the drafting of support tickets and streamline knowledge retrieval.
• Seamlessly incorporate Claude into current customer support workflows.

Course Format

• Interactive lectures grounded in real-world support scenarios.
• Practical exercises based on enterprise service cases.
• Direct application of Claude within a simulated support environment.

Customisation Options

• Should you require the course to be adapted to your organisation’s specific support workflows, please get in touch to discuss customisation possibilities.

AI for SQL refers to the application of artificial intelligence and large language models (LLMs) to automate, optimize, and improve how SQL queries are generated, executed, and interpreted within enterprise data environments.

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

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

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

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.

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 Almada (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.

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 Almada (online or onsite) is aimed at advanced-level professionals who wish to specialise in cutting-edge deep learning techniques for NLU.

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

• Understand the key differences between NLU and NLP models.
• Apply advanced deep learning techniques to NLU tasks.
• Explore deep architectures such as transformers and attention mechanisms.
• Leverage future trends in NLU for building sophisticated AI systems.

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.

Mistral comprises a family of high-performance large language models, meticulously engineered for cost-efficient production deployment at scale.

This instructor-led live training, available either online or onsite, is designed for advanced infrastructure engineers, cloud architects, and MLOps leaders who aim to design, deploy, and optimize Mistral-based architectures to achieve maximum throughput while minimizing costs.

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

• Implement scalable deployment patterns for Mistral Medium 3.
• Apply effective batching, quantization, and serving strategies.
• Optimize inference costs without compromising performance.
• Design production-ready serving topologies tailored for enterprise workloads.

Course Format

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

Course Customization Options

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

LangGraph serves as a graph-based orchestration framework that empowers conditional, multi-step workflows involving large language models (LLMs) and tools, making it highly suitable for automating and personalizing content pipelines.

This instructor-led live training, available either online or onsite, targets intermediate-level marketers, content strategists, and automation developers looking to build dynamic, branching email campaigns and content generation pipelines using LangGraph.

Upon completing this training, participants will be equipped to:

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

Course Format

• Interactive lectures paired with group discussions.
• Practical labs focused on implementing email workflows and content pipelines.
• Scenario-based exercises covering personalization, segmentation, and branching logic.

Course Customization Options

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

This instructor-led, live training in Almada (online or onsite) is aimed at intermediate-level professionals who wish to enhance their skills in generating high-quality, human-like text using advanced NLG methods.

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

• Understand advanced techniques for generating natural language text.
• Implement and fine-tune transformer-based models for NLG.
• Optimize NLG outputs for fluency, coherence, and relevance.
• Evaluate the quality of generated text using both automated and human metrics.

This instructor-led, live training in Almada (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 Almada (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 Almada (online or in-person) targets beginner-level professionals who want to install, configure, and utilise Ollama to run AI models on their own machines.

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

• Grasp the fundamentals of Ollama and its capabilities.
• Configure Ollama for running local AI models.
• Deploy and interact with LLMs using Ollama.
• Optimise performance and resource utilisation for AI workloads.
• Investigate use cases for local AI deployment across various industries.

This instructor-led, live training in Almada (online or onsite) is designed for beginner to intermediate data scientists and developers who wish to implement and leverage Small Language Models in various applications.

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

• Understand the architecture and functionality of Small Language Models.
• Implement SLMs for tasks such as text generation and sentiment analysis.
• Optimize and fine-tune SLMs for specific use cases.
• Deploy SLMs in resource-constrained environments.
• Evaluate and interpret the performance of SLMs 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.

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.

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.