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

AI-powered predictive maintenance leverages machine learning and data analytics to forecast equipment failures and optimize maintenance schedules. This approach transforms reactive maintenance models into proactive strategies, enhancing uptime, reducing costs, and extending asset longevity. This instructor-led, live training (online or onsite) is designed for intermediate-level professionals who wish to implement AI-driven predictive maintenance solutions in industrial settings, including those relevant for government operations. 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 government or other specific needs, 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 for government and private sector entities.

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.
• Extensive 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 methods to detect defects, anomalies, and deviations in production processes.

This instructor-led, live training (available online or on-site) is designed for quality professionals at beginner to intermediate levels who seek to implement 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.
• Employ machine learning and computer vision techniques to identify defects.
• Develop simple AI models for anomaly detection and yield forecasting.

Format of the Course

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

Course Customization Options for Government

• To request a customized training tailored to the needs of your agency, please contact us to arrange.

Artificial Intelligence (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 wish to apply AI-driven tools to enhance logistics performance, forecast demand accurately, and automate warehouse and transport operations for government and private sector entities. By the end of this training, participants will be able to: - Understand how AI is applied across various logistics and supply chain activities. - Utilize machine learning models for demand forecasting and inventory control. - Analyze routes and optimize transportation 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 applications - Hands-on implementation in a live-lab environment **Course Customization Options:** - To request a customized training for government or organizational needs, 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 for government and private sector applications. 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 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 (online or onsite) is designed for intermediate-level cross-functional teams who aim to collaboratively implement AI use cases aligned 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 scope practical AI use cases from operations, quality, or maintenance.
• Collaborate effectively across roles to develop machine learning solutions.
• Manage, clean, and analyze diverse industrial datasets.
• Present a functional 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 for Government

• 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 rapid development of intelligent bots for government.

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 fundamentals of intelligent bots
• Learn how to develop intelligent bots using cloud applications for government
• Gain proficiency in using the Microsoft Bot Framework, the Bot Builder SDK, and the Azure Bot Service
• Comprehend the design principles of bots through bot patterns
• Create their first intelligent bot using Microsoft Azure

Audience

• Developers
• Hobbyists
• Engineers
• IT Professionals

Format of the Course

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

A chatbot or bot serves as a digital assistant designed to automate user interactions across various messaging platforms, enabling tasks to be completed more efficiently without requiring direct human-to-human communication. In this instructor-led, live training, participants will gain the skills necessary to begin developing bots 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 comprehensive process involved in bot development - Examine the various tools and platforms utilized in building bots - Construct a sample chatbot for Facebook Messenger - Develop a sample chatbot using Microsoft Bot Framework **Audience** - Developers interested in creating their own bots for government or private sector use **Format of the Course** - Part lecture, part discussion, with exercises and extensive hands-on practice

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 designed for intermediate-level professionals who wish to build, deploy, and optimize digital twin models using real-time data and AI-based insights for government applications. 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. - Extensive 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.

Edge AI involves 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 designed for 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 for government operations. 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. - Extensive 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.

Industrial computer vision with artificial intelligence (AI) is revolutionizing how manufacturers and quality assurance (QA) teams identify surface defects, verify part conformity, and automate visual inspection processes.

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

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

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

Format of the Course

• Interactive lecture and discussion, focusing on practical applications for government.
• Extensive exercises and practice sessions to reinforce learning.
• Hands-on implementation in a live-lab environment, simulating real-world scenarios for government use.

Course Customization Options

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

A Smart Robot is an Artificial Intelligence (AI) system capable of learning from its environment and experiences, enhancing its capabilities through accumulated knowledge. These robots can collaborate with humans, working alongside them and adapting to human behaviors. They are adept at both manual tasks and cognitive functions. In addition to physical robots, Smart Robots can also exist as software applications, operating within a computer without any physical interaction. This instructor-led training provides participants with an in-depth understanding of the technologies, frameworks, and techniques required for programming mechanical Smart Robots. Participants will apply this knowledge to complete their own Smart Robot projects. The course is structured into four sections, each comprising three days of lectures, discussions, and hands-on robot development in a live laboratory environment. Each section concludes with a practical project to reinforce the skills learned. The target hardware for this training will be simulated in 3D using 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 fundamental concepts in robotic technologies. - Manage the interaction between software and hardware in a robotic system. - Implement the software components essential for Smart Robots. - Build and operate a simulated mechanical Smart Robot capable of seeing, sensing, processing, grasping, navigating, and interacting with humans through voice commands. - Enhance a Smart Robot's capabilities to perform complex tasks using Deep Learning techniques. - 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 tailor any aspect of this course (such as programming language or robot model) to specific needs for government projects, please contact us to arrange customization.