Natural Language Processing (NLP) Training in Sintra

This instructor-led, live training in Sintra (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.

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.

This instructor-led live training in Sintra (online or on-site) is targeted at intermediate-level data scientists seeking to acquire a comprehensive grasp and practical skills in both Large Language Models (LLMs) and Reinforcement Learning (RL).

By the conclusion of this training, participants will be capable of:

• Understanding the structure and operation of transformer models.
• Optimizing and fine-tuning LLMs for specific tasks and use cases.
• Grasping the core principles and methodologies of reinforcement learning.
• Learning how reinforcement learning techniques can boost LLM performance.

This instructor-led, live training in Sintra (online or onsite) is aimed at intermediate-level content creators, marketers, and educational technologists who wish to harness the power of LLMs for generating high-quality, diverse, and engaging content across various domains.

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

• Understand the capabilities of LLMs and their application in content generation.
• Set up and use LLMs for generating various types of content.
• Apply best practices for prompting and fine-tuning LLMs to produce desired outputs.
• Evaluate the quality of AI-generated content and refine it for specific audiences.
• Explore advanced techniques for creative and multi-modal content generation with LLMs.

This instructor-led, live training in Sintra (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.

This instructor-led, live training in Sintra (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.

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.

Ollama is a platform that enables running and fine-tuning large language and multimodal models locally.

This instructor-led, live training (online or onsite) is aimed at advanced-level ML engineers, AI researchers, and product developers who wish to build and deploy multimodal applications with Ollama.

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

• Set up and run multimodal models with Ollama.
• Integrate text, image, and audio inputs for real-world applications.
• Build document understanding and visual QA systems.
• Develop multimodal agents capable of reasoning across modalities.

Format of the Course

• Interactive lecture and discussion.
• Hands-on practice with real multimodal datasets.
• Live-lab implementation of multimodal pipelines using Ollama.

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) 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 instructor-led, live training in Sintra (online or onsite) is designed for advanced-level data engineers and DevOps professionals seeking to leverage LangChain’s capabilities through integration with various cloud services.

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

• Integrate LangChain with major cloud platforms, including AWS, Azure, and Google Cloud.
• Utilize cloud-based APIs and services to enhance LangChain-powered applications.
• Scale and deploy conversational agents to the cloud for real-time interaction.
• Implement monitoring and security best practices in cloud environments.

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 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.

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.

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

Upon completing this training, participants will be capable of:

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

This instructor-led live training in Sintra, offered online or onsite, targets intermediate to advanced AI developers, architects, and product managers. The course focuses on identifying and mitigating risks associated with LLM-powered applications, including prompt injection, data leakage, and unfiltered outputs. Participants will learn to implement security controls such as input validation, human-in-the-loop oversight, and output guardrails.

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

• Understand the core vulnerabilities of LLM-based systems.
• Apply secure design principles to LLM app architecture.
• Use tools such as Guardrails AI and LangChain for validation, filtering, and safety.
• Integrate techniques like sandboxing, red teaming, and human-in-the-loop review into production-grade pipelines.

This instructor-led, live training in Sintra (online or onsite) is designed for intermediate-level software developers and AI engineers who wish to integrate Claude AI into their applications, build AI-powered chatbots, and enhance software functionality with AI-driven automation.

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

• Use the Claude AI API to integrate AI into applications.
• Develop AI-driven chatbots and virtual assistants.
• Enhance applications with AI-powered automation and NLP.
• Optimize and fine-tune Claude AI models for different use cases.

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.

LangGraph is a framework designed for composing graph-structured LLM workflows that support branching, tool use, memory, and controllable execution.

This instructor-led, live training (online or onsite) is aimed at intermediate-level engineers and product teams who wish to combine LangGraph’s graph logic with LLM agent loops to build dynamic, context-aware applications such as customer support agents, decision trees, and information retrieval systems.

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

• Design graph-based workflows that coordinate LLM agents, tools, and memory.
• Implement conditional routing, retries, and fallbacks for robust execution.
• Integrate retrieval, APIs, and structured outputs into agent loops.
• Evaluate, monitor, and harden agent behavior for reliability and safety.

Format of the Course

• Interactive lecture and facilitated discussion.
• Guided labs and code walkthroughs in a sandbox environment.
• Scenario-based design exercises and peer reviews.

Course Customization Options

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

This technical course explores how to leverage Large Language Models (LLMs) to enhance code quality, minimize technical debt, and automate documentation processes within software teams.

Delivered as an instructor-led live training (available online or on-site), this programme is designed for intermediate to advanced software professionals eager to utilise LLMs, such as GPT, to analyse, refactor, and document complex or legacy codebases more efficiently.

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

• Utilise LLMs to elucidate code structures, dependencies, and logic within unfamiliar repositories.
• Spot and refactor anti-patterns to boost code readability.
• Automate the creation and upkeep of in-line comments, README files, and API documentation.
• Seamlessly integrate LLM-driven insights into existing CI/CD and code review workflows.

Course Format

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

Customisation Options

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

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.

Speech recognition and transcription using AI involves converting spoken language into written text through machine learning models and natural language processing systems.

This instructor-led, live training (online or onsite) is aimed at intermediate-level professionals who wish to implement, evaluate, and optimize AI-powered speech-to-text solutions for real-world use cases.

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

• Understand how modern speech recognition models are trained and deployed.
• Evaluate open-source and commercial APIs for speech-to-text transcription.
• Handle multilingual and domain-specific transcription challenges.
• Build simple transcription workflows for different audio sources.

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) 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.

Mistral Medium 3 is a high-performance, multimodal large language model engineered for robust, production-grade deployment within enterprise settings.

This instructor-led training, available either online or on-site, is tailored for AI/ML engineers, platform architects, and MLOps teams at intermediate to advanced levels. The course focuses on deploying, optimizing, and securing Mistral Medium 3 for specific enterprise applications.

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

• Deploy Mistral Medium 3 via API or self-hosted solutions.
• Enhance inference performance while managing costs.
• Develop and implement multimodal use cases using Mistral Medium 3.
• Apply security and compliance best practices suitable for enterprise environments.

Course Format

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

Course Customization Options

• For customized training arrangements, please contact us directly.

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.

This instructor-led, live training in Sintra (online or onsite) is aimed at beginner-level, intermediate-level, or advanced-level AI professionals who wish to use MCP to connect AI assistants with external tools, data, and enterprise services.

By the end of this training, participants will be able to: explain MCP concepts, identify key architecture components, set up a basic integration, and apply security good practices.

This instructor-led, live training in Sintra (online or onsite) is aimed at intermediate-level enterprise architects who wish to use Model Context Protocol to design secure, scalable, and governable agent integration platforms for enterprise environments.

By the end of this training, participants will be able to: explain MCP architecture and enterprise patterns, design secure integration platforms, apply governance and access controls, and evaluate deployment and scaling options.

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.