Natural Language Processing (NLP) Training in Sintra

This instructor-led, live training in Sintra (online or onsite) is designed for senior management professionals who wish to understand what LLMs are, explore their potential impact on business operations, and evaluate the practical uses of AI tools such as ChatGPT, Microsoft Copilot, or Grok for real-world tasks like content creation, data summarization, and decision support.

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

• Understand what LLMs are and how tools like ChatGPT and Copilot function.
• Use prompt techniques to get practical, reliable results from LLMs.
• Evaluate real use cases such as email drafting, summarizing documents, and productivity automation.
• Identify investment opportunities and strategic applications for AI adoption.

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

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.

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.

Mistral AI serves as an open-source AI platform, empowering teams to construct and embed conversational assistants within both enterprise operations and customer-facing processes.

This instructor-led training, available online or onsite, is tailored for beginner to intermediate-level product managers, full-stack developers, and integration engineers looking to design, integrate, and productize conversational assistants using Mistral's connectors and integrations.

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

• Connecting Mistral conversational models with enterprise and SaaS connectors.
• Implementing retrieval-augmented generation (RAG) to ensure grounded responses.
• Creating UX patterns for both internal and external chat assistants.
• Deploying assistants into product workflows to address real-world use cases.

Course Format

• Interactive lectures and discussions.
• Practical integration exercises.
• Live laboratory sessions for developing conversational assistants.

Course Customization Options

• For customized training requirements, please contact us to make arrangements.

This instructor-led, live training in Sintra (online or onsite) is aimed at intermediate-level urban planners, city administrators, and smart city solution developers who wish to implement Small Language Models (SLMs) in smart city projects to improve urban living.

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

• Understand the application of SLMs in smart cities.
• Integrate SLMs with urban data sets for enhanced decision-making.
• Develop strategies for deploying SLMs in urban management systems.
• Assess the impact of SLMs on urban planning and smart city solutions.

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 Sintra (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 facilitates stateful, multi-actor workflows driven by Large Language Models (LLMs), offering precise control over execution paths and state persistence. In the healthcare sector, these capabilities are vital for ensuring compliance, interoperability, and the development of decision-support systems that align with clinical workflows.

This instructor-led, live training (available online or onsite) targets intermediate to advanced professionals looking to design, implement, and manage LangGraph-based healthcare solutions while navigating regulatory, ethical, and operational challenges.

Upon completing this training, participants will be able to:

• Design healthcare-specific LangGraph workflows that prioritise compliance and auditability.
• Integrate LangGraph applications with medical ontologies and standards (such as FHIR, SNOMED CT, and ICD).
• Apply best practices for reliability, traceability, and explainability in sensitive environments.
• Deploy, monitor, and validate LangGraph applications within healthcare production settings.

Format of the Course

• Interactive lectures and discussions.
• Hands-on exercises using real-world case studies.
• Implementation practice in a live-lab environment.

Course Customization Options

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

This instructor-led live training in Sintra (online or onsite) is designed for intermediate professionals seeking to deepen their understanding of conversational agents and apply LangChain to real-world scenarios.

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

• Understand the fundamentals of LangChain and its application in building conversational agents.
• Develop and deploy conversational agents using LangChain.
• Integrate conversational agents with APIs and external services.
• Apply Natural Language Processing (NLP) techniques to improve the performance of conversational agents.

This instructor-led, live training in Sintra (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 Sintra (online or onsite) is aimed at advanced-level professionals who wish to implement secure and efficient AI-driven workflows using Ollama.

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

• Deploy and configure Ollama for private AI processing.
• Integrate AI models into secure enterprise workflows.
• Optimize AI performance while maintaining data privacy.
• Automate business processes with on-premise AI capabilities.
• Ensure compliance with enterprise security and governance policies.

Le Chat Enterprise is a private ChatOps solution that provides secure, customizable, and governed conversational AI capabilities for organizations, with support for RBAC, SSO, connectors, and enterprise app integrations.

This instructor-led, live training (online or onsite) is aimed at intermediate-level product managers, IT leads, solution engineers, and security/compliance teams who wish to deploy, configure, and govern Le Chat Enterprise in enterprise environments.

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

• Set up and configure Le Chat Enterprise for secure deployments.
• Enable RBAC, SSO, and compliance-driven controls.
• Integrate Le Chat with enterprise applications and data stores.
• Design and implement governance and admin playbooks for ChatOps.

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.

This instructor-led, live training in Sintra (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.

This instructor-led, live training in Sintra (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 Sintra (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 in Sintra (online or onsite) is aimed at data scientists, machine learning practitioners, and NLP researchers and enthusiasts who wish to effectively utilize Hugging Face for NLP tasks.

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

• Utilize a Hugging Face Transformer model, and fine-tune it on a specific dataset.
• Gain the ability to independently address common NLP challenges.
• Create and share your model demos effectively.
• Streamline the optimization of your models for production.
• Employ Hugging Face Transformers for solving a wide range of machine learning problems.

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.

In this instructor-led, live training in Sintra, 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