Natural Language Processing (NLP) Training in Coimbra

This instructor-led, live training in Coimbra (online or onsite) is designed for intermediate-level AI professionals, ethicists, data scientists, 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 Coimbra (online or on-site) is designed for 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.

Upon completing this training, participants will be able to:

• Comprehend the role of LLMs in crafting immersive VR and AR experiences.
• Develop VR and AR applications that leverage LLMs for interactive dialogues and content creation.
• Integrate LLMs with VR and AR development tools to enhance user engagement.
• Apply best practices for designing AI-driven narratives and interactions within virtual spaces.

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

This instructor-led, live training in Coimbra (online or onsite) is designed for intermediate-level business professionals and data analysts who wish to harness the power of LLMs for extracting business insights.

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

• Understand the fundamentals and applications of LLMs in the context of business intelligence.
• Apply LLMs to analyze large datasets and extract meaningful insights.
• Integrate LLM-driven analytics into strategic business decision-making processes.
• Evaluate the ethical considerations and best practices for using LLMs in business.
• Anticipate future trends in AI and prepare for the evolving landscape of business intelligence.

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.

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.

Claude AI is a sophisticated language and reasoning engine designed to support structured data operations, analytical workflows, and the enhancement of business intelligence capabilities.

This instructor-led training session, available either online or onsite, targets professionals ranging from beginner to intermediate proficiency who aim to utilise Claude to expedite data analysis, derive actionable insights, and streamline BI processes.

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

• Utilise Claude to conduct ad-hoc exploratory data analysis.
• Generate SQL queries, summaries, and data transformations via natural language prompts.
• Leverage Claude to design dashboards, define KPIs, and create analytical views with greater efficiency.
• Interpret business data with improved accuracy through structured AI-assisted reasoning.

Course Format

• Instructor-led demonstrations alongside guided discussions.
• Practical exercises utilising real-world business datasets.
• Application of Claude within BI-focused scenarios.

Customization Options

• If you require the content to be tailored to your internal BI tools or workflows, please contact us to arrange a bespoke version of this course.

This instructor-led, live training in Coimbra (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 in-depth course focuses on diagnosing, testing, and measuring model behaviour when running local or private Ollama deployments.

Delivered as instructor-led live training (available online or onsite), it is designed for advanced AI engineers, ML Ops professionals, and QA practitioners who wish to ensure the reliability, fidelity, and operational readiness of Ollama-based models in production.

Upon completion, participants will be able to:

• Conduct systematic debugging of Ollama-hosted models and reliably reproduce failure modes.
• Design and execute robust evaluation pipelines using quantitative and qualitative metrics.
• Implement observability (logs, traces, metrics) to monitor model health and drift.
• Automate testing, validation, and regression checks integrated into CI/CD pipelines.

Course Format

• Interactive lectures and discussions.
• Hands-on labs and debugging exercises using Ollama deployments.
• Case studies, group troubleshooting sessions, and automation workshops.

Customisation Options

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

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 in Coimbra (online or onsite) is aimed at intermediate-level IT professionals who wish to deploy small language models directly onto devices with limited processing capabilities, opening up possibilities for innovative applications in various sectors.

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

• Understand the challenges and solutions for implementing AI on compact hardware.
• Optimize and compress AI models for efficient on-device deployment.
• Utilize modern AI frameworks and tools for on-device model implementation.
• Design and develop real-time AI applications for mobile and IoT devices.
• Evaluate and ensure the security and privacy of on-device AI systems.

This instructor-led, live training in Coimbra (online or on-site) is aimed at beginner-level to intermediate-level content creators, writers, and marketers who want to leverage Claude AI for content generation, editing, and summarization to enhance blogs, reports, and marketing materials.

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

• Use Claude AI for content brainstorming and idea expansion.
• Enhance writing with AI-assisted editing and proofreading.
• Generate summaries for long-form content and reports.
• Automate marketing copy creation for different platforms.

This instructor-led, live training in Coimbra (online or onsite) is aimed at intermediate-level professionals who wish to deepen their expertise in modern NLU techniques.

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

• Implement advanced NLU techniques for AI systems.
• Leverage deep learning models for semantic understanding.
• Perform intent recognition and classification in complex applications.
• Utilize state-of-the-art tools like Hugging Face Transformers for NLU tasks.

This instructor-led, live training in Coimbra (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 Coimbra (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 (available online or on-site) is designed for data scientists, machine learning engineers, NLP researchers, and AI enthusiasts who aim to grasp the inner workings of GPT models, investigate the capabilities of GPT-3 and GPT-4, and learn how to effectively utilise these models for their NLP tasks.

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

• Grasp the core concepts and principles underlying Generative Pre-trained Transformers.
• Understand the architecture and training process of GPT models.
• Employ GPT-3 for tasks such as text generation, completion, and translation.
• Investigate the latest advancements in GPT-4 and its potential applications.
• Apply GPT models to their own NLP projects and tasks.

This instructor-led, live training delivered in Coimbra (either online or onsite) targets beginner-level professionals seeking to learn the basics of NLG and its role in AI and content generation.

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

• Comprehending the fundamental principles of Natural Language Generation.
• Investigating how NLG is applied across different sectors.
• Acquiring basic skills for producing human-like text using AI.
• Utilizing Python libraries and models to generate text.

Unstructured data is estimated to constitute over 90% of all data, with a significant portion appearing as text. This volume continues to expand rapidly through blog posts, tweets, social media activity, and other digital publications.

This instructor-led, live course focuses on extracting valuable insights and meaning from this vast amount of information. By leveraging the R programming language and Natural Language Processing (NLP) libraries, we integrate concepts and techniques from computer science, artificial intelligence, and computational linguistics to algorithmically interpret the meaning within text data. Data samples are provided in various languages to meet specific customer needs.

Upon completion of this training, participants will be capable of preparing datasets (both large and small) from diverse sources and applying appropriate algorithms to analyze and report on their significance.

Format of the Course

• A blend of lectures and discussions, with a strong emphasis on hands-on practice and occasional assessments to evaluate understanding

This course is designed for managers, solutions architects, innovation officers, CTOs, software architects, and anyone seeking an overview of applied artificial intelligence and its near-term development forecast.

Artificial Intelligence (AI) encompasses a range of technologies designed to create intelligent systems that can interpret data and context to make "intelligent decisions". For telecom providers, leveraging AI in the development of applications and services can significantly enhance operational efficiency and service delivery, particularly in areas such as maintenance and network optimization.

This course explores the various technologies that constitute AI and the skill sets necessary to implement them effectively. Throughout the program, we delve into specific AI applications within the telecom sector.

Audience

• Network engineers
• Network operations staff
• Telecom technical managers

Course Format

• A blend of lectures, discussions, and hands-on exercises

This course is designed for developers and data scientists who wish to understand and implement artificial intelligence in their applications. It specifically focuses on data analysis, distributed AI, and natural language processing.

Chatbots are automated programs that mimic human conversation through chat interfaces. They enable organizations to optimize operational efficiency by offering faster and more streamlined user interaction channels.

During this instructor-led live training, participants will acquire the skills necessary to construct chatbots using Python.

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

• Grasp the fundamental principles of chatbot development
• Construct, evaluate, deploy, and resolve issues with various types of chatbots using Python

Audience

• Developers

Course Format

• A blend of lectures, discussions, practical exercises, and intensive hands-on practice

Note

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

This instructor-led live training in Coimbra (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, higher throughput, and better cost control.

By the end of this training, participants will be able to: explain Hunyuan production deployment patterns, optimise inference performance, implement batching and quantisation strategies, and plan scalable serving operations.

In this instructor-led, live training in Coimbra, participants will learn to utilize Python libraries for NLP by building an application that processes a set of images and generates captions.

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

• Design and implement DL for NLP using Python libraries.
• Write Python code that reads a large volume of images and generates keywords.
• Develop Python code that generates captions based on the detected keywords.

This classroom-based training session will delve into NLP techniques alongside the application of AI and Robotics in business. Delegates will undertake computer-based examples and case study solving exercises using Python

This instructor-led, live training (available online or onsite) is designed for developers and data scientists who wish to use spaCy to process very large volumes of text to find patterns and gain insights.

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

• Install and configure spaCy.
• Understand spaCy's approach to Natural Language Processing (NLP).
• Extract patterns and obtain business insights from large-scale data sources.
• Integrate the spaCy library with existing web and legacy applications.
• Deploy spaCy to live production environments to predict human behavior.
• Use spaCy to pre-process text for Deep Learning

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.
• To learn more about spaCy, please visit: https://spacy.io/

In the realm of Python Machine Learning, the Text Summarization feature allows users to ingest input text and generate a concise summary. This functionality is accessible via the command line or as a Python API/Library. A compelling use case is the rapid production of executive summaries, which is highly beneficial for organizations that must review substantial volumes of text data prior to creating reports and presentations.

During this instructor-led live training, participants will learn how to utilize Python to develop a straightforward application that automatically generates summaries from input text.

Upon completing this training, participants will be able to:

• Utilize a command-line tool designed for text summarization.
• Design and build Text Summarization code using Python libraries.
• Evaluate three Python summarization libraries: sumy 0.7.0, pysummarization 1.0.4, and readless 1.0.17.

Audience

• Developers
• Data Scientists

Format of the course

• A blend of lectures, discussions, exercises, and extensive hands-on practice.

TensorFlow™ is an open-source software library designed for numerical computation via data flow graphs.

SyntaxNet serves as a neural network-based Natural Language Processing framework built for TensorFlow.

Word2Vec facilitates the learning of vector representations for words, known as "word embeddings". It offers a highly computationally efficient predictive model for deriving word embeddings from raw text. This technology is available in two variations: the Continuous Bag-of-Words model (CBOW) and the Skip-Gram model (refer to Chapters 3.1 and 3.2 in Mikolov et al.).

When employed together, SyntaxNet and Word2Vec enable users to generate Learned Embedding models from Natural Language input.

Audience

This course is designed for developers and engineers who plan to integrate SyntaxNet and Word2Vec models into their TensorFlow graphs.

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

• Grasp the structure and deployment mechanisms of TensorFlow
• Execute installation, production environment setup, architecture tasks, and configuration
• Assess code quality, perform debugging, and implement monitoring
• Implement advanced production-level tasks such as training models, embedding terms, constructing graphs, and logging