Smart Robotics in Manufacturing: AI for Perception, Planning, and Control Training Course

AI-powered predictive maintenance leverages machine learning and data analytics to predict equipment failures and optimize maintenance schedules. It shifts the focus from reactive maintenance models to proactive strategies, enhancing uptime, reducing costs, and extending asset longevity.

This instructor-led, live training (available online or on-site) is designed for intermediate-level professionals who aim to implement AI-driven predictive maintenance solutions in industrial settings.

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

• Grasp how predictive maintenance differs from reactive and preventive approaches.
• Gather and organize machine data for AI-driven analysis.
• Utilize machine learning models to identify anomalies and predict equipment failures.
• Develop comprehensive workflows from sensor data collection to actionable insights.

Format of the Course

• Interactive lectures and discussions.
• Practical exercises and case studies.
• Live demonstrations and practical data workflows.

Course Customization Options

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

AI for Process Optimization involves the use of machine learning and data analytics to improve efficiency, quality, and productivity in manufacturing processes.

This instructor-led, live training (available online or on-site) is designed for intermediate-level manufacturing professionals who want to leverage AI techniques to enhance operations, minimize downtime, and support ongoing improvement initiatives.

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

• Grasp AI concepts pertinent to manufacturing optimization.
• Gather and prepare production data for analysis.
• Implement machine learning models to identify bottlenecks and predict failures.
• Visualize and interpret results to inform data-driven decisions.

Format of the Course

• Interactive lectures and discussions.
• Numerous exercises and practice sessions.
• 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 involves the application of computer vision and machine learning techniques to detect defects, anomalies, and deviations in production processes.

This instructor-led, live training (available both online and on-site) is designed for quality professionals at beginner to intermediate levels who are interested in leveraging AI tools to automate inspections and enhance product quality in manufacturing settings.

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

• Comprehend how AI is utilized in industrial quality control.
• Gather and label image or sensor data from production lines.
• Utilize machine learning and computer vision to identify defects.
• Create simple AI models for anomaly detection and yield forecasting.

Format of the Course

• Interactive lectures and discussions.
• Numerous exercises and practical activities.
• 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 involves the use of predictive analytics, machine learning, and automation to optimize inventory management, routing, and demand forecasting.

This instructor-led, live training (available online or onsite) is designed for intermediate-level supply chain professionals who want to leverage AI-driven tools to enhance logistics performance, accurately forecast demand, and automate warehouse and transport operations.

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

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

Format of the Course

• Interactive lectures and discussions.
• Extensive exercises and practical activities.
• 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 involves the application of artificial intelligence to automate, monitor, and optimize industrial operations in real-time.

This instructor-led, live training (available online or on-site) is designed for beginner-level decision-makers and technical leads who wish to gain a strategic and practical introduction to leveraging AI in smart factory settings.

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

• Grasp the fundamental principles of AI and machine learning.
• Identify key applications of AI in manufacturing and automation.
• Explore how AI can support predictive maintenance, quality control, and process optimization.
• Assess the steps required to launch AI-driven initiatives.

Format of the Course

• Interactive lectures and discussions.
• 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 practical, project-focused approach to applying machine learning, computer vision, and data analytics to address real-world industrial challenges using actual or simulated datasets.

This instructor-led, live training (available online or on-site) is designed for intermediate-level cross-functional teams who want to collaboratively implement AI use cases that align with their operational goals and gain hands-on experience working with industrial data pipelines.

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

• Identify and define practical AI use cases from operations, quality, or maintenance areas.
• Collaborate effectively across different roles to develop machine learning solutions.
• Manage, clean, and analyze a variety of industrial datasets.
• Present a functional prototype of an AI-enabled solution based on a chosen use case.

Format of the Course

• Interactive lectures and discussions.
• Group 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.

The Azure Bot Service integrates the capabilities of the Microsoft Bot Framework and Azure Functions to facilitate the quick development of intelligent bots.

In this instructor-led, live training, participants will learn how to efficiently create an intelligent bot using Microsoft Azure.

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

• Understand the basics of intelligent bots
• Learn how to develop intelligent bots using cloud applications
• Grasp the use of the Microsoft Bot Framework, the Bot Builder SDK, and the Azure Bot Service
• Comprehend how to design bots using bot patterns
• Create their first intelligent bot using Microsoft Azure

Audience

• Developers
• Hobbyists
• Engineers
• IT Professionals

Format of the course

• Part lecture, part discussion, exercises, and extensive hands-on practice

A bot or chatbot acts as a digital assistant designed to automate user interactions across various messaging platforms, enabling tasks to be completed more efficiently without the need for human-to-human communication.

In this instructor-led, live training, participants will gain insights into developing a bot by working through the creation of sample chatbots using specialized development tools and frameworks.

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

• Understand the diverse applications and uses of bots
• Grasp the entire process involved in bot development
• Explore the different tools and platforms used for building bots
• Create a sample chatbot for Facebook Messenger
• Develop a sample chatbot using Microsoft Bot Framework

Audience

• Developers interested in creating their own bot

Format of the course

• Combination of lecture, discussion, exercises, and extensive hands-on practice

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

This instructor-led, live training (available online or onsite) is designed for intermediate-level professionals who aim 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:

• Grasp the architecture and components of digital twins.
• Utilize 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 sessions.
• Extensive exercises and practice activities.
• Hands-on implementation in a live-lab environment.

Course Customization Options

• For a customized training session for this course, please contact us to arrange.

Edge AI involves deploying artificial intelligence models directly on devices and machines at the network's edge, enabling real-time decision-making with minimal delay.

This instructor-led, live training (available online or onsite) is designed for advanced embedded and IoT professionals who aim to implement AI-powered logic and control systems in manufacturing settings where speed, reliability, and offline operation are crucial.

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

• Grasp the architecture and advantages of edge AI systems.
• Develop and optimize AI models for deployment on embedded devices.
• Utilize tools such as 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.
• Extensive exercises and practice sessions.
• Hands-on implementation in a live-lab environment.

Course Customization Options

• For customized training for this course, please contact us to arrange.

Industrial computer vision with AI is revolutionizing the way manufacturers and quality assurance teams identify surface defects, verify part compliance, and automate visual inspection processes.

This instructor-led, live training (available both online and on-site) is designed for intermediate to advanced QA teams, automation engineers, and developers who want to create and implement computer vision systems for defect detection and inspection using AI techniques.

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

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

Format of the Course

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

Course Customization Options

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

A Smart Robot is an Artificial Intelligence (AI) system that can learn from its environment and experiences, enhancing its capabilities based on the acquired knowledge. These robots can collaborate with humans, working alongside them and learning from their behavior. They are capable of performing not only manual tasks but also cognitive ones. In addition to physical robots, Smart Robots can be purely software-based, residing in a computer as an application without any moving parts or physical interaction with the world.

In this instructor-led, live training, participants will explore various technologies, frameworks, and techniques for programming different types of mechanical Smart Robots. They will then apply this knowledge to complete their own Smart Robot projects.

The course is divided into four sections, each consisting of three days of lectures, discussions, and hands-on robot development in a live lab environment. Each section will conclude with a practical, hands-on project to allow participants to practice and demonstrate their newly acquired skills.

The target hardware for this course will be simulated in 3D through simulation software. The ROS (Robot Operating System) open-source framework, along with C++ and Python, will be used for programming the robots.

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

• Understand the key concepts used in robotic technologies
• Manage the interaction between software and hardware in a robotic system effectively
• Implement the software components that underpin Smart Robots
• Build and operate a simulated mechanical Smart Robot capable of seeing, sensing, processing, grasping, navigating, and interacting with humans through voice
• Extend a Smart Robot's ability to perform complex tasks using Deep Learning
• Test and troubleshoot a Smart Robot in realistic scenarios

Audience

• Developers
• Engineers

Format of the course

• Part lecture, part discussion, exercises, and extensive hands-on practice

Note

• To customize any aspect of this course (programming language, robot model, etc.), please contact us to arrange.