Curso de Smart Robotics in Manufacturing: AI for Perception, Planning, and Control

AI-powered predictive maintenance applies machine learning and data analytics to forecast equipment failures and optimize maintenance schedules. It transforms reactive maintenance models into proactive strategies, enabling better uptime, cost reduction, and asset longevity.

This instructor-led, live training (online or onsite) is aimed at intermediate-level professionals who wish to implement AI-driven predictive maintenance solutions in industrial environments.

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

• Understand how predictive maintenance differs from reactive and preventive maintenance strategies.
• Collect and structure machine data for AI-powered analysis.
• Apply machine learning models to detect anomalies and predict failures.
• Implement end-to-end workflows from sensor data to actionable insights.

Format of the Course

• Interactive lecture and discussion.
• Hands-on exercises and case studies.
• Live demonstration and practical data workflows.

Course Customization Options

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

AI for Process Optimization is the application of machine learning and data analytics to enhance efficiency, quality, and throughput in manufacturing operations.

This instructor-led, live training (online or onsite) is aimed at intermediate-level manufacturing professionals who wish to apply AI techniques to streamline operations, reduce downtime, and support continuous improvement initiatives.

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

• Understand AI concepts relevant to manufacturing optimization.
• Collect and prepare production data for analysis.
• Apply machine learning models to identify bottlenecks and predict failures.
• Visualize and interpret results to support data-driven decisions.

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.

AI for Quality Control is the use of computer vision and machine learning techniques to identify defects, anomalies, and deviations in production processes.

This instructor-led, live training (online or onsite) is aimed at beginner-level to intermediate-level quality professionals who wish to apply AI tools to automate inspections and improve product quality in manufacturing environments.

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

• Understand how AI is applied in industrial quality control.
• Collect and label image or sensor data from production lines.
• Use machine learning and computer vision to detect defects.
• Develop simple AI models for anomaly detection and yield forecasting.

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.

AI in Supply Chain and Manufacturing Logistics is the application of predictive analytics, machine learning, and automation to optimize inventory, routing, and demand forecasting.

This instructor-led, live training (online or onsite) is aimed at intermediate-level supply chain professionals who wish to apply AI-driven tools to enhance logistics performance, forecast demand accurately, and automate warehouse and transport operations.

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

• Understand how AI is applied across logistics and supply chain activities.
• Use machine learning models for demand forecasting and inventory control.
• Analyze routes and optimize transport using AI-based techniques.
• Automate decision-making in warehouses and fulfillment processes.

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.

AI in Smart Factories is the application of artificial intelligence to automate, monitor, and optimize industrial operations in real time.

This instructor-led, live training (online or onsite) is aimed at beginner-level decision-makers and technical leads who wish to gain a strategic and practical introduction to how AI can be leveraged in smart factory environments.

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

• Understand the core principles of AI and machine learning.
• Identify key AI use cases in manufacturing and automation.
• Explore how AI supports predictive maintenance, quality control, and process optimization.
• Evaluate the steps involved in launching AI-driven initiatives.

Format of the Course

• Interactive lecture and discussion.
• Real-world case studies and group exercises.
• Strategic frameworks and implementation guidance.

Course Customization Options

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

AI Use Case Implementation is a hands-on, project-driven approach to applying machine learning, computer vision, and data analytics to solve real-world industrial challenges using actual or simulated datasets.

This instructor-led, live training (online or onsite) is aimed at intermediate-level cross-functional teams who wish to collaboratively implement AI use cases aligned with their operational goals and gain experience working with industrial data pipelines.

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

• Select and scope practical AI use cases from operations, quality, or maintenance.
• Work collaboratively across roles to develop machine learning solutions.
• Handle, clean, and analyze diverse industrial datasets.
• Present a working prototype of an AI-enabled solution based on a selected use case.

Format of the Course

• Interactive lecture and discussion.
• Group-based exercises and project work.
• Hands-on implementation in a live-lab environment.

Course Customization Options

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

O Serviço de Bot do Azure combina o poder das funções do Microsoft Bot Framework e do Azure para permitir o rápido desenvolvimento de bots inteligentes.

Neste treinamento ao vivo conduzido por instrutor, os participantes aprenderão como criar facilmente um bot inteligente usando o Microsoft Azure

No final deste treinamento, os participantes serão capazes de:

• Aprender os fundamentos dos bots inteligentes
• Aprender como criar bots inteligentes usando aplicações em nuvem
• Compreender como usar o Microsoft Bot Framework, o Bot Builder SDK e o Serviço de Bot do Azure
• Entender como projetar bots usando padrões de bot
• Desenvolver seu primeiro bot inteligente usando Microsoft Azure

Público

• Desenvolvedores
• Hobbyistas
• Engenheiros
• Profissionais de TI

Formato do curso

• Parte palestra, parte discussão, exercícios e prática intensiva

Um bot ou chatbot é como um assistente de computador que é usado para automatizar as interacções do utilizador em várias plataformas de mensagens e fazer as coisas mais rapidamente sem a necessidade de os utilizadores falarem com outro humano.

Neste treinamento ao vivo conduzido por instrutor, os participantes aprenderão como começar a desenvolver um bot à medida que avançam na criação de chatbots de amostra usando ferramentas e estruturas de desenvolvimento de bots.

Ao final deste treinamento, os participantes serão capazes de:

• Compreender os diferentes usos e aplicações de bots
• Compreender o processo completo no desenvolvimento de bots
• Explore as diferentes ferramentas e plataformas usadas na construção de bots
• Construir um chatbot de amostra para Facebook Messenger
• Crie um chatbot de amostra usando Microsoft Bot Framework

Público-alvo

• Desenvolvedores interessados em criar seu próprio bot

Formato do curso

• Parte palestra, parte discussão, exercícios e prática prática pesada

Digital Twins are virtual replicas of physical systems enhanced by real-time data and AI-driven intelligence.

This instructor-led, live training (online or onsite) is aimed at intermediate-level professionals who wish to build, deploy, and optimize digital twin models using real-time data and AI-based insights.

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

• Understand the architecture and components of digital twins.
• Use simulation tools to model complex systems and environments.
• Integrate real-time data streams into virtual models.
• Apply AI techniques for predictive behavior and anomaly detection.

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.

Edge AI is the deployment of artificial intelligence models directly on devices and machines at the edge of the network, enabling real-time decision-making with minimal latency.

This instructor-led, live training (online or onsite) is aimed at advanced-level embedded and IoT professionals who wish to deploy AI-powered logic and control systems in manufacturing environments where speed, reliability, and offline operation are critical.

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

• Understand the architecture and benefits of edge AI systems.
• Build and optimize AI models for deployment on embedded devices.
• Use tools like TensorFlow Lite and OpenVINO for low-latency inference.
• Integrate edge intelligence with sensors, actuators, and industrial protocols.

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.

Industrial computer vision with AI is transforming how manufacturers and QA teams detect surface defects, verify part conformity, and automate visual inspection processes.

This instructor-led, live training (online or onsite) is aimed at intermediate-level to advanced-level QA teams, automation engineers, and developers who wish to design and implement computer vision systems for defect detection and inspection using AI techniques.

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

• Understand the architecture and components of industrial vision systems.
• Build AI models for visual defect detection using deep learning.
• Integrate real-time inspection pipelines with industrial cameras and devices.
• Deploy and optimize AI-powered inspection systems for production environments.

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.

Este treinamento ao vivo conduzido por instrutor em Portugal (no local ou remoto) é destinado a engenheiros que desejam aprender sobre a aplicabilidade da inteligência artificial a sistemas mecatrônicos.

No final deste treinamento, os participantes serão capazes de:

• Obter uma visão geral da inteligência artificial, aprendizado de máquina e inteligência computacional.
• Compreender os conceitos de redes neurais e diferentes métodos de aprendizagem.
• Escolher abordagens de inteligência artificial de forma eficaz para problemas da vida real.
• Implementar aplicações de IA na engenharia mecatrónica.

Este treinamento ao vivo conduzido por instrutor em Portugal (no local ou remoto) é destinado a participantes de nível intermediário que desejam aprimorar suas habilidades em projetar, programar e implantar sistemas robóticos inteligentes para automação e além.

No final deste treinamento, os participantes serão capazes de:

• Compreender os princípios de Physical AI e suas aplicações em robótica e automação.
• Conceber e programar sistemas robóticos inteligentes para ambientes dinâmicos.
• Implementar modelos de IA para tomada de decisão autónoma em robôs.
• Tirar partido de ferramentas de simulação para testes e otimização robótica.
• Abordar desafios como a fusão de sensores, o processamento em tempo real e a eficiência energética.

Um robô inteligente é um sistema Artificial Intelligence (AI) que pode aprender com o seu ambiente e a sua experiência e desenvolver as suas capacidades com base nesse conhecimento. Os robôs inteligentes Smart Robots podem colaborar com os seres humanos, trabalhando ao seu lado e aprendendo com o seu comportamento. Além disso, têm capacidade para realizar não só trabalho manual, mas também tarefas cognitivas. Para além dos robôs físicos, os Smart Robots também podem ser puramente baseados em software, residindo num computador como uma aplicação de software sem partes móveis ou interação física com o mundo.

Neste treinamento ao vivo conduzido por instrutor, os participantes aprenderão as diferentes tecnologias, estruturas e técnicas para programar diferentes tipos de Smart Robots mecânicos e, em seguida, aplicarão esse conhecimento para concluir seus próprios projetos de robôs inteligentes.

O curso está dividido em 4 secções, cada uma consistindo em três dias de palestras, discussões e desenvolvimento de robôs práticos num ambiente de laboratório ao vivo. Cada secção será concluída com um projeto prático para permitir aos participantes praticar e demonstrar os conhecimentos adquiridos.

O hardware alvo para este curso será simulado em 3D através de software de simulação. A estrutura de código aberto ROS (Robot Operating System), C++ e Python será usada para programar os robôs.

No final desta formação, os participantes serão capazes de:

• Compreender os principais conceitos utilizados nas tecnologias robóticas
• Compreender e gerir a interação entre software e hardware num sistema robótico
• Compreender e implementar os componentes de software que sustentam Smart Robots
• Construir e operar um Robô Inteligente mecânico simulado que pode ver, sentir, processar, agarrar, navegar e interagir com humanos através da voz
• Alargar a capacidade de um Robô Inteligente para executar tarefas complexas através de Deep Learning
• Testar e resolver problemas de um Robô Inteligente em cenários realistas

Público

• Programadores
• Engenheiros

Formato do curso

• Parte palestra, parte discussão, exercícios e prática prática pesada

Nota

• Para personalizar qualquer parte deste curso (linguagem de programação, modelo de robô, etc.), contacte-nos para combinar.