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

AI-driven predictive maintenance leverages machine learning and advanced data analytics to anticipate equipment failures and optimize maintenance scheduling. This approach shifts traditional reactive models toward proactive strategies, resulting in improved operational uptime, reduced costs, and extended asset lifespan.

This instructor-led training, available either online or onsite, is designed for intermediate-level professionals seeking to deploy AI-enhanced predictive maintenance solutions within industrial settings.

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

• Differentiating predictive maintenance from reactive and preventive maintenance approaches.
• Gathering and organizing machine data for AI-based analysis.
• Utilizing machine learning models to identify anomalies and forecast potential failures.
• Implementing comprehensive workflows that transform sensor data into actionable insights.

Course Format

• Engaging lectures and interactive discussions.
• Practical exercises and real-world case studies.
• Live demonstrations and hands-on data workflow practice.

Customization Options

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

AI for Process Optimization involves leveraging machine learning and data analytics to boost efficiency, quality, and throughput within manufacturing environments.

This instructor-led training, available online or onsite, is designed for intermediate-level manufacturing professionals seeking to utilize AI techniques to streamline operations, minimize downtime, and drive continuous improvement.

Upon completing this training, participants will be capable of:

• Grasping AI concepts pertinent to manufacturing optimization.
• Gathering and preparing production data for analysis.
• Deploying machine learning models to detect bottlenecks and forecast failures.
• Visualizing and interpreting outcomes to facilitate data-driven decision-making.

Course Format

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

Customization Options

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

AI for Quality Control involves leveraging computer vision and machine learning techniques to detect defects, anomalies, and deviations within production processes.

This instructor-led live training, available online or onsite, is designed for beginner to intermediate quality professionals seeking to apply AI tools to automate inspections and enhance product quality in manufacturing settings.

Upon completing this training, participants will be able to:

• Grasp how AI is utilized in industrial quality control.
• Gather and annotate image or sensor data from production lines.
• Apply machine learning and computer vision methods to identify defects.
• Build simple AI models for anomaly detection and yield forecasting.

Course Format

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

Course Customization Options

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

Artificial Intelligence in Supply Chain and Manufacturing Logistics involves utilizing predictive analytics, machine learning, and automation to enhance inventory management, optimize routing, and improve demand forecasting.

This instructor-led live training, available online or onsite, is designed for intermediate-level supply chain professionals seeking to leverage AI-driven tools to boost logistics performance, achieve accurate demand forecasting, and automate warehouse and transportation operations.

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

• Grasp how AI is integrated into logistics and supply chain activities.
• Apply machine learning models for demand forecasting and inventory control.
• Analyze routes and optimize transport processes using AI techniques.
• Automate decision-making within warehouses and fulfillment workflows.

Course Format

• Interactive lectures and group discussions.
• Extensive exercises and practical application.
• Hands-on implementation within 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 applying artificial intelligence to automate, monitor, and optimize industrial operations in real time.

This instructor-led live training, available online or onsite, is designed for beginner-level decision-makers and technical leads seeking a strategic and practical introduction to leveraging AI in smart factory environments.

Upon completing this training, participants will be able to:

• Comprehend the fundamental principles of AI and machine learning.
• Recognize key AI use cases in manufacturing and automation.
• Explore how AI facilitates predictive maintenance, quality control, and process optimization.
• Assess the steps required to launch AI-driven initiatives.

Course Format

• Interactive lectures and discussions.
• Real-world case studies and group exercises.
• Strategic frameworks and implementation guidance.

Course Customization Options

• For customized training requests, please contact us to arrange.

The implementation of AI use cases employs a project-focused, practical methodology to apply machine learning, computer vision, and data analytics for addressing real-world industrial challenges using authentic or simulated datasets.

This live training, led by an instructor (available online or in-person), targets intermediate-level cross-functional teams seeking to collaboratively implement AI initiatives aligned with their operational objectives and acquire experience working with industrial data pipelines.

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

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

Course Format

• Interactive lectures and discussions.
• Collaborative exercises and project work in groups.
• Hands-on implementation within a live laboratory environment.

Customization Options

• To arrange customized training for this course, please reach out to us.

Azure Bot Service unites the strengths of the Microsoft Bot Framework and Azure Functions, delivering a robust platform for the rapid creation of intelligent bots.

In this instructor-led live training, attendees will discover efficient methods for developing intelligent bots using Microsoft Azure.

Upon completing the training, participants will be capable of:

Grasping the fundamental concepts behind intelligent bots.

Constructing intelligent bots utilizing cloud-based applications.

Acquiring practical expertise in the Microsoft Bot Framework, the Bot Builder SDK, and Azure Bot Service.

Applying recognized bot design patterns in real-world contexts.

Creating and deploying their initial intelligent bot using Microsoft Azure.

Audience

This course is tailored for developers, hobbyists, engineers, and IT professionals keen on bot development.

Format of the course

The training integrates lectures and discussions with exercises, placing a strong emphasis on hands-on practice.

A bot, or chatbot, functions as a virtual assistant designed to automate user interactions across various messaging platforms, enabling tasks to be completed more efficiently without requiring direct communication with a human agent.

In this instructor-led live training, participants will learn the fundamentals of bot development by creating sample chatbots using established development tools and frameworks.

Upon completing this training, participants will be able to:

• Identify various use cases and applications for bots
• Grasp the end-to-end process of bot development
• Examine the diverse tools and platforms available for building bots
• Construct a sample chatbot for Facebook Messenger
• Develop a sample chatbot utilizing the Microsoft Bot Framework

Audience

• Developers who wish to create their own bots

Course Format

• A combination of lectures, discussions, exercises, and extensive hands-on practice

Digital Twins serve as virtual copies of physical assets, augmented with real-time data and AI-powered analytics.

This guided, live training session (available online or in-person) is designed for mid-level professionals seeking to create, implement, and refine digital twin models by leveraging real-time information and AI-driven insights.

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

• Grasping the architecture and key elements of digital twins.
• Employing simulation tools to model complex systems and environments.
• Integrating real-time data flows into virtual representations.
• Applying AI methods for predictive analysis and anomaly identification.

Course Format

• Interactive lectures and discussions.
• Numerous exercises and practical activities.
• Practical implementation within a live lab environment.

Customization Opportunities

• For inquiries regarding tailored training for this course, please reach out to us to make arrangements.

Edge AI involves deploying artificial intelligence models directly onto devices and machines located at the network's edge, facilitating real-time decision-making with minimal latency.

This instructor-led live training, available online or onsite, is designed for advanced embedded and IoT professionals aiming to implement AI-driven logic and control systems in manufacturing settings where speed, reliability, and offline capability are essential.

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

• Grasp the architecture and advantages of edge AI systems.
• Create and optimize AI models for deployment on embedded hardware.
• Utilize tools such as TensorFlow Lite and OpenVINO for low-latency inference.
• Integrate edge intelligence with sensors, actuators, and industrial protocols.

Course Format

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

Customization Options

• To request customized training for this course, please contact us to make arrangements.

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

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

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

• Grasping the architecture and core components of industrial vision systems.
• Developing AI models for visual defect detection through deep learning.
• Integrating real-time inspection pipelines with industrial cameras and hardware.
• Deploying and optimizing AI-driven inspection systems for production environments.

Format of the Course

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

Course Customization Options

• To request customized training for this course, please contact us to make arrangements.

A Smart Robot is an Artificial Intelligence (AI) system that can learn from its environment and its experience and build on its capabilities based on that knowledge. Smart Robots can collaborate with humans, working along-side them and learning from their behavior. Furthermore, they have the capacity for not only manual labor, but cognitive tasks as well. In addition to physical robots, Smart Robots can also be purely software based, residing in a computer as a software application with no moving parts or physical interaction with the world.

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

The course is divided into 4 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 acquired knowledge.

The target hardware for this course will be simulated in 3D through simulation software. The ROS (Robot Operating System) open-source framework, 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
• Understand and manage the interaction between software and hardware in a robotic system
• Understand and implement the software components that underpin Smart Robots
• Build and operate a simulated mechanical Smart Robot that can see, sense, process, grasp, navigate, and interact with humans through voice
• Extend a Smart Robot's ability to perform complex tasks through Deep Learning
• Test and troubleshoot a Smart Robot in realistic scenarios

Audience

• Developers
• Engineers

Format of the course

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

Note

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