Hotel Melia Setubal

58, Av. Alexandre Herculano, 58 2900-206 Setúbal, Setubal, Portugal, 2900-206 Setúbal

Located in the city centre, this hotel combines contemporary decoration, modernity and comfort in a beautiful setting surrounded by beaches and nature. It is also within very easy reach of all the main attractions in Setúbal, guaranteeing a stay that is equally restful and pleasure.

Subcategories (9)

Category for Large Language Models (LLMs)

Large Language Models (LLMs)
Category for Small Language Models (SLMs)

Small Language Models (SLMs)
Category for Natural Language Understanding (NLU)

Natural Language Understanding (NLU)
Category for Natural Language Generation (NLG)

Natural Language Generation (NLG)
Category for Sentiment Analysis

Sentiment Analysis
Category for Spark NLP

Spark NLP
Category for TextBlob

TextBlob
Category for Hugging Face

Hugging Face
Category for Speech Recognition

Speech Recognition

Explore Our Courses

Large Language Models Meta AI

 21 Hours
This instructor-led, live training in Setúbal (online or onsite) is aimed at intermediate-level to advanced-level AI researchers, data scientists, and developers 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.
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LLMs for Financial Market Prediction

 14 Hours
This instructor-led, live training in Setúbal (online or onsite) is aimed at intermediate-level financial analysts, data scientists, and investment professionals who wish to leverage LLMs for financial market analysis and prediction. By the end of this training, participants will be able to:
  • Understand the application of LLMs in financial market analysis.
  • Use LLMs to process financial news, reports, and data for market insights.
  • Develop predictive models for stock prices, market trends, and economic indicators.
  • Integrate LLM insights into investment decision-making processes.
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LLMs for Virtual Reality (VR) and Augmented Reality (AR)

 14 Hours
This instructor-led, live training in Setúbal (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.
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Fine-Tuning Open-Source LLMs (LLaMA, Mistral, Qwen, etc.)

 14 Hours
This instructor-led, live training in Setúbal (online or onsite) is aimed at intermediate-level ML practitioners and AI developers who wish to fine-tune and deploy open-weight models like LLaMA, Mistral, and Qwen for specific business or internal applications.By the end of this training, participants will be able to:
  • Understand the ecosystem and differences between open-source LLMs.
  • Prepare datasets and fine-tuning configurations for models like LLaMA, Mistral, and Qwen.
  • Execute fine-tuning pipelines using Hugging Face Transformers and PEFT.
  • Evaluate, save, and deploy fine-tuned models in secure environments.
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LLMs for Speech Recognition and Synthesis

 14 Hours
This instructor-led, live training in Setúbal (online or onsite) is aimed at beginner-level to intermediate-level 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.
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LLMs for Automated Customer Support

 14 Hours
This instructor-led, live training in Setúbal (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.
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Parameter-Efficient Fine-Tuning (PEFT) Techniques for LLMs

 14 Hours
This instructor-led, live training in Setúbal (online or onsite) is aimed at 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.
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LLMs for Sentiment Analysis

 21 Hours
This instructor-led, live training in Setúbal (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.
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Natural Language Processing (NLP) with Google Colab

 14 Hours
This instructor-led, live training in Setúbal (online or onsite) is aimed at intermediate-level data scientists and developers who wish 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.
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LlamaIndex: Developing LLM Powered Applications

 42 Hours
This instructor-led, live training in Setúbal (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.
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Google Gemini AI for Transformative Customer Service

 14 Hours
This instructor-led, live training in Setúbal (online or onsite) is aimed at intermediate-level customer service professionals who wish to implement Google Gemini AI in their customer service operations. By the end of this training, participants will be able to:
  • Understand the impact of AI on customer service.
  • Set up Google Gemini AI to automate and personalize customer interactions.
  • Utilize text-to-text and image-to-text transformations to improve service efficiency.
  • Develop AI-driven strategies for real-time customer feedback analysis.
  • Explore advanced features to create a seamless customer service experience.
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Fine-Tuning and Customizing AI Models on Ollama

 14 Hours
This instructor-led, live training in Setúbal (online or onsite) is aimed at advanced-level professionals who wish to fine-tune and customize AI models on Ollama for enhanced performance and domain-specific applications. By the end of this training, participants will be able to:
  • Set up an efficient environment for fine-tuning AI models on Ollama.
  • Prepare datasets for supervised fine-tuning and reinforcement learning.
  • Optimize AI models for performance, accuracy, and efficiency.
  • Deploy customized models in production environments.
  • Evaluate model improvements and ensure robustness.
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Small Language Models (SLMs): Developing Energy-Efficient AI

 21 Hours
This instructor-led, live training in Setúbal (online or onsite) is aimed at advanced-level machine learning engineers and AI researchers who wish to develop energy-efficient AI solutions with small language models that are both powerful and environmentally friendly. By the end of this training, participants will be able to:
  • Understand the impact of AI on energy consumption and the environment.
  • Apply model compression and optimization techniques to reduce the size and energy usage of AI models.
  • Utilize energy-efficient hardware and software frameworks for AI deployment.
  • Implement best practices for sustainable AI development.
  • Advocate for and contribute to sustainable practices in the AI industry.
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Advanced LLMs for NLP Tasks

 21 Hours
This instructor-led, live training in Setúbal (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.
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Fine-Tuning for Natural Language Processing (NLP)

 21 Hours
This instructor-led, live training in Setúbal (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.
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Exploring Generative Pre-trained Transformers (GPT): From GPT-3 to GPT-4

 14 Hours
This instructor-led, live training in (online or onsite) is aimed at data scientists, machine learning engineers, NLP researchers, and AI enthusiasts who wish to understand the inner workings of GPT models, explore the capabilities of GPT-3 and GPT-4, and learn how to leverage these models for their NLP tasks. By the end of this training, participants will be able to:
  • Understand the key concepts and principles behind Generative Pre-trained Transformers.
  • Comprehend the architecture and training process of GPT models.
  • Utilize GPT-3 for tasks such as text generation, completion, and translation.
  • Explore the latest advancements in GPT-4 and its potential applications.
  • Apply GPT models to their own NLP projects and tasks.
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Introduction to Large Language Models (LLMs)

 14 Hours
This instructor-led, live training in Setúbal (online or onsite) is aimed at beginner-level to intermediate-level developers who wish to use Large Language Models for various natural language tasks. By the end of this training, participants will be able to:
  • Set up a development environment that includes a popular LLM.
  • Create a basic LLM and fine-tune it on a custom dataset.
  • Use LLMs for different natural language tasks such as text summarization, question answering, text generation, and more.
  • Debug and evaluate LLMs using tools such as TensorBoard, PyTorch Lightning, and Hugging Face Datasets.
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NLP: Natural Language Processing with R

 21 Hours
It is estimated that unstructured data accounts for more than 90 percent of all data, much of it in the form of text. Blog posts, tweets, social media, and other digital publications continuously add to this growing body of data. This instructor-led, live course centers around extracting insights and meaning from this data. Utilizing the R Language and Natural Language Processing (NLP) libraries, we combine concepts and techniques from computer science, artificial intelligence, and computational linguistics to algorithmically understand the meaning behind text data. Data samples are available in various languages per customer requirements. By the end of this training participants will be able to prepare data sets (large and small) from disparate sources, then apply the right algorithms to analyze and report on its significance. Format of the Course
  • Part lecture, part discussion, heavy hands-on practice, occasional tests to gauge understanding
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Natural Language Processing (NLP) with Python

 28 Hours
This course introduces linguists or programmers to NLP in Python. During this course we will mostly use nltk.org (Natural Language Tool Kit), but also we will use other libraries relevant and useful for NLP. At the moment we can conduct this course in Python 2.x or Python 3.x. Examples are in English or Mandarin (普通话). Other languages can be also made available if agreed before booking.
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Artificial Intelligence (AI) Overview

 7 Hours
This course has been created for managers, solutions architects, innovation officers, CTOs, software architects and anyone who is interested in an overview of applied artificial intelligence and the nearest forecast for its development.
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AI Awareness for Telecom

 14 Hours
AI is a collection of technologies for building intelligent systems capable of understanding data and the activities surrounding the data to make "intelligent decisions". For Telecom providers, building applications and services that make use of AI could open the door for improved operations and servicing in areas such as maintenance and network optimization. In this course we examine the various technologies that make up AI and the skill sets required to put them to use. Throughout the course, we examine AI's specific applications within the Telecom industry. Audience
  • Network engineers
  • Network operations personnel
  • Telecom technical managers
Format of the course
  • Part lecture, part discussion, hands-on exercises
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Artificial Intelligence - the most applied stuff - Data Analysis + Distributed AI + NLP

 21 Hours
This course is intended for developers and data scientists who want to understand and implement artificial intelligence in their applications. Special focus is placed on data analytics, distributed AI, and natural language processing.
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Building Chatbots in Python

 21 Hours
ChatBots are computer programs that automatically simulate human responses via chat interfaces. ChatBots help organizations maximize their operations efficiency by providing easier and faster options for their user interactions. In this instructor-led, live training, participants will learn how to build chatbots in Python. By the end of this training, participants will be able to:
  • Understand the fundamentals of building chatbots
  • Build, test, deploy, and troubleshoot various chatbots using Python
Audience
  • Developers
Format of the course
  • Part lecture, part discussion, exercises and heavy hands-on practice
Note
  • To request a customized training for this course, please contact us to arrange.
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Deep Learning for NLP (Natural Language Processing)

 28 Hours
In this instructor-led, live training in Setúbal, participants will learn to use Python libraries for NLP as they create an application that processes a set of pictures and generates captions.  By the end of this training, participants will be able to:
  • Design and code DL for NLP using Python libraries.
  • Create Python code that reads a substantially huge collection of pictures and generates keywords.
  • Create Python Code that generates captions from the detected keywords.
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Natural Language Processing (NLP) - AI/Robotics

 21 Hours
This classroom based training session will explore NLP techniques in conjunction with the application of AI and Robotics in business. Delegates will undertake computer based examples and case study solving exercises using Python
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Natural Language Processing (NLP) with Deep Dive in Python and NLTK

 35 Hours
By the end of the training the delegates are expected to be sufficiently equipped with the essential python concepts and should be able to sufficiently use NLTK to implement most of the NLP and ML based operations. The training is aimed at giving not just an executional knowledge but also the logical and operational knowledge of the technology therein.
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Natural Language Processing (NLP) with Python spaCy

 14 Hours
This instructor-led, live training (online or onsite) is aimed at 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/
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NLP with Python and TextBlob

 14 Hours
This instructor-led, live training in Setúbal (online or onsite) is aimed at data scientists and developers who wish to use TextBlob to implement and simplify NLP tasks, such as sentiment analysis, spelling corrections, text classification modeling, etc. By the end of this training, participants will be able to:
  • Set up the necessary development environment to start implementing NLP tasks with TextBlob.
  • Understand the features, architecture, and advantages of TextBlob.
  • Learn how to build text classification systems using TextBlob.
  • Perform common NLP tasks (Tokenization, WordNet, Sentiment analysis, Spelling correction, etc.)
  • Execute advanced implementations with simple APIs and a few lines of codes.
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Text Summarization with Python

 14 Hours
In Python Machine Learning, the Text Summarization feature is able to read the input text and produce a text summary. This capability is available from the command-line or as a Python API/Library. One exciting application is the rapid creation of executive summaries; this is particularly useful for organizations that need to review large bodies of text data before generating reports and presentations. In this instructor-led, live training, participants will learn to use Python to create a simple application that auto-generates a summary of input text. By the end of this training, participants will be able to:
  • Use a command-line tool that summarizes text.
  • Design and create Text Summarization code using Python libraries.
  • Evaluate three Python summarization libraries: sumy 0.7.0, pysummarization 1.0.4, readless 1.0.17
Audience
  • Developers
  • Data Scientists
Format of the course
  • Part lecture, part discussion, exercises and heavy hands-on practice
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Natural Language Processing (NLP) with TensorFlow

 35 Hours
TensorFlow™ is an open source software library for numerical computation using data flow graphs. SyntaxNet is a neural-network Natural Language Processing framework for TensorFlow. Word2Vec is used for learning vector representations of words, called "word embeddings". Word2vec is a particularly computationally-efficient predictive model for learning word embeddings from raw text. It comes in two flavors, the Continuous Bag-of-Words model (CBOW) and the Skip-Gram model (Chapter 3.1 and 3.2 in Mikolov et al.). Used in tandem, SyntaxNet and Word2Vec allows users to generate Learned Embedding models from Natural Language input. Audience This course is targeted at Developers and engineers who intend to work with SyntaxNet and Word2Vec models in their TensorFlow graphs. After completing this course, delegates will:
  • understand TensorFlow’s structure and deployment mechanisms
  • be able to carry out installation / production environment / architecture tasks and configuration
  • be able to assess code quality, perform debugging, monitoring
  • be able to implement advanced production like training models, embedding terms, building graphs and logging
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Testimonials (5)

prompts engineering part

Michal - GE HealthCare

Course - Generative AI with Large Language Models (LLMs)

Hunter is fabulous, very engaging, extremely knowledgeable and personable. Very well done.

Rick Johnson - Laramie County Community College

Course - Artificial Intelligence (AI) Overview

Organization, adhering to the proposed agenda, the trainer's vast knowledge in this subject

Ali Kattan - TWPI

Course - Natural Language Processing with TensorFlow

This is one of the best hands-on with exercises programming courses I have ever taken.

Laura Kahn

Course - Artificial Intelligence - the most applied stuff - Data Analysis + Distributed AI + NLP

I did like the exercises.

Office for National Statistics

Course - Natural Language Processing with Python

Provisional Upcoming Courses (Contact Us For More Information)

LLMs for Speech Recognition and Synthesis

2025-06-23 09:30
14 hours
Hotel Melia Setubal

Google Gemini AI for Transformative Customer Service

2025-07-07 09:30
14 hours
Hotel Melia Setubal

LlamaIndex: Developing LLM Powered Applications

2025-07-21 09:30
42 hours
Hotel Melia Setubal

Large Language Models Meta AI

2025-08-04 09:30
21 hours
Hotel Melia Setubal

LLMs for Virtual Reality (VR) and Augmented Reality (AR)

2025-08-18 09:30
14 hours
Hotel Melia Setubal

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