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

AI-driven predictive maintenance leverages machine learning and data analytics to anticipate equipment failures and optimize maintenance schedules. It shifts reactive maintenance models toward proactive strategies, enhancing uptime, reducing costs, and extending asset lifespan.

This instructor-led, live training (available online or onsite) is designed for intermediate-level professionals seeking to implement AI-driven predictive maintenance solutions within industrial settings.

Upon completing this training, participants will be able to:

• Distinguish predictive maintenance from reactive and preventive strategies.
• Gather and structure machine data for AI analysis.
• Utilize machine learning models to detect anomalies and predict failures.
• Deploy end-to-end workflows transforming sensor data into actionable insights.

Course Format

• Interactive lectures and discussions.
• Practical exercises and case studies.
• Live demonstrations and real-world data workflows.

Customization Options

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

Artificial Intelligence for Process Optimization involves utilizing machine learning and data analytics to boost efficiency, enhance product quality, and increase throughput within manufacturing environments.

This instructor-led training, available either online or onsite, is designed for manufacturing professionals with intermediate experience who aim to implement AI strategies to streamline operations, minimize downtime, and foster continuous improvement.

Upon completing this course, participants will be equipped to:

• Grasp AI concepts pertinent to manufacturing optimization.
• Gather and ready production data for analytical review.
• Utilize machine learning models to detect bottlenecks and forecast equipment failures.
• Visualize and interpret outcomes to facilitate evidence-based decision-making.

Course Format

• Engaging lectures coupled with interactive discussions.
• Numerous practical exercises and drills.
• Practical implementation within a live laboratory environment.

Customization Opportunities

• For tailored training options for this course, please reach out to us to arrange details.

AI-driven Quality Control leverages computer vision and machine learning to identify defects, anomalies, and deviations within production processes.

This instructor-led training, available either online or onsite, is designed for quality professionals ranging from beginner to intermediate levels who aim to utilize AI tools to automate inspections and enhance product quality in manufacturing settings.

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

• Comprehend the application of AI in industrial quality control.
• Gather and annotate image or sensor data generated by production lines.
• Apply machine learning and computer vision techniques to detect defects.
• Construct basic AI models for anomaly detection and yield forecasting.

Course Format

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

Customization Options

• For inquiries regarding customized training for this course, please contact us to make arrangements.

AI for Supply Chain and Manufacturing Logistics involves leveraging predictive analytics, machine learning, and automation to refine inventory management, route planning, and demand forecasting.

This instructor-led training, available online or on-site, is designed for intermediate-level supply chain professionals seeking to utilize AI-driven tools to improve logistics efficiency, enhance demand forecasting accuracy, and automate warehouse and transport operations.

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

• Grasp the application of AI across logistics and supply chain activities.
• Apply 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.

Course Format

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

Customization Options

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

Artificial Intelligence (AI) in smart factories involves applying AI technologies 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 who want to gain a strategic and practical introduction to leveraging AI within smart factory environments.

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

• Grasp the core principles of AI and machine learning.
• Identify key AI applications 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 adopts a hands-on, project-centric methodology to apply machine learning, computer vision, and data analytics for resolving real-world industrial challenges using actual or simulated datasets.

This instructor-led, live training (available online or onsite) targets intermediate-level cross-functional teams seeking to collaboratively implement AI use cases that align with their operational objectives and gain practical experience with industrial data pipelines.

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

• Identifying and defining practical AI use cases within operations, quality assurance, or maintenance.
• Collaborating across various roles to develop machine learning solutions.
• Managing, cleaning, and analyzing diverse industrial datasets.
• Presenting a functional prototype of an AI-enabled solution based on a chosen use case.

Course Format

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

Customization Options

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

Azure Bot Service integrates the capabilities of the Microsoft Bot Framework and Azure Functions, offering a robust platform for rapidly constructing intelligent bots.

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

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

Grasp the fundamental concepts underlying intelligent bots.

Construct intelligent bots utilizing cloud-based applications.

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

Implement established bot design patterns in real-world scenarios.

Create and deploy their first intelligent bot using Microsoft Azure.

Audience

This course is tailored for developers, hobbyists, engineers, and IT professionals with an interest in bot development.

Format of the course

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

A bot, or chatbot, functions as a digital assistant designed to automate user interactions across various messaging platforms, enabling faster task completion without requiring direct human intervention.

During this instructor-led live training, participants will learn how to begin building bots by walking through the creation of sample chatbots using industry-standard development tools and frameworks.

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

• Comprehending the diverse uses and applications of bots
• Gaining insight into the end-to-end bot development process
• Exploring the range of tools and platforms utilized in bot construction
• Developing a sample chatbot for Facebook Messenger
• Constructing a sample chatbot using 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 replicas of physical systems, augmented by real-time data feeds and AI-powered intelligence.

This instructor-led live training, available either online or onsite, is designed for intermediate-level professionals seeking to build, deploy, and optimize digital twin models leveraging real-time data and AI-driven insights.

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

• Grasp the architecture and key 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 analysis and anomaly detection.

Course Format

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

Customization Options

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

Edge AI involves deploying artificial intelligence models directly onto devices and machinery 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 seeking to implement AI-driven logic and control systems in manufacturing settings where speed, reliability, and offline operation are essential.

Upon completing this training, participants will be able to:

• Grasp the architecture and advantages of edge AI systems.
• Construct 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 lectures and discussions.
• Extensive exercises and practice sessions.
• Hands-on implementation in a live laboratory environment.

Course Customization Options

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

Artificial intelligence is revolutionizing industrial computer vision, enabling manufacturers and quality assurance teams to identify surface flaws, verify part compliance, and automate visual inspection workflows.

This instructor-led live training, available online or on-site, targets intermediate to advanced quality assurance teams, automation engineers, and developers aiming to design and implement AI-based computer vision systems for defect detection and inspection.

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

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

Course Format

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

Customization Options

• To request a customized training session 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.