Machine Learning for Robotics Training Course

This instructor-led live training in Taiwan (available online or onsite) is designed for data scientists and software engineers who wish to use AdaBoost to build boosting algorithms for machine learning with Python.

Upon completing this training, participants will be able to:

• Configure the necessary development environment to begin building machine learning models with AdaBoost.
• Grasp the concept of ensemble learning and learn how to implement adaptive boosting.
• Acquire the skills to construct AdaBoost models that enhance machine learning algorithms in Python.
• Apply hyperparameter tuning to improve the accuracy and overall performance of AdaBoost models.

Drones and photogrammetry have become indispensable tools for high-precision infrastructure supervision. By integrating advanced geodesy principles, real-time modeling, and high-accuracy drone mapping, professionals can achieve greater insight, precision, and productivity in construction environments.

This instructor-led live training (available online or onsite) targets intermediate to advanced-level professionals seeking to apply sophisticated drone and photogrammetry workflows—including geodetic controls and high-precision mapping techniques—to complex infrastructure projects.

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

• Implement advanced photogrammetric methods, including RTK/PPK workflows and ground control calibration.
• Integrate geodetic reference systems and projections for large-scale infrastructure sites.
• Design precision flight missions tailored to complex terrain and infrastructure geometry.
• Analyze photogrammetry data using GIS software to monitor structural health, deformation, and compliance.

Course Format

• Interactive lectures and discussions.
• Advanced exercises and real-world case studies.
• Hands-on implementation with drone data and modeling tools.

Customization Options

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

This instructor-led, live training in Taiwan (online or onsite) is designed for engineers and developers who wish to design, develop, and test aerial vehicles by exploring various aerial robotics concepts and tools.

Upon completing this training, participants will be able to:

• Grasp the fundamental principles of aerial robotics.
• Model and design UAVs and quadrotors.
• Gain knowledge about the fundamentals of flight control and motion planning.
• Learn to utilize various simulation tools for aerial robotics.

ArduPilot is an open-source autopilot software suite designed for drones, rovers, and other unmanned vehicles. It offers advanced capabilities such as autonomous navigation, real-time communication with ground stations, and seamless integration with robotics middleware like ROS2.

This instructor-led live training, available either online or onsite, is tailored for intermediate-level developers and technical professionals looking to design, program, and test unmanned aerial vehicles (UAVs) using ArduPilot.

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

• Establish a complete development environment for ArduPilot.
• Configure firmware, middleware, and MAVLink APIs for UAV control.
• Utilize SITL simulation to safely test and debug drone behavior.
• Extend ArduPilot with ROS2 and integrate it with external tools or sensors.
• Develop autonomous flight logic and execute end-to-end UAV missions.

Course Format

• Interactive lectures and discussions.
• Ample exercises and practice opportunities.
• Hands-on implementation within a live lab environment.

Course Customization Options

• This training is based on the open-source autopilot software ArduPilot. For customized training arrangements, please contact us.

This instructor-led live training in Taiwan (online or onsite) is tailored for data scientists and non-technical professionals who wish to utilize Auto-Keras to automate the process of selecting and optimizing a machine learning model.

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

• Automate the training of highly efficient machine learning models.
• Automatically identify the optimal parameters for deep learning models.
• Construct highly accurate machine learning models.
• Leverage machine learning capabilities to address real-world business challenges.

This instructor-led live training in Taiwan (online or on-site) is designed for data scientists and data analysts who wish to automate, evaluate, and manage predictive models using DataRobot's machine learning capabilities.

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

• Import datasets into DataRobot to analyze, evaluate, and perform quality checks.
• Develop and train models to identify key variables and achieve prediction objectives.
• Interpret models to generate valuable insights that support business decision-making.
• Monitor and manage models to ensure optimal prediction performance.

This instructor-led live training in Taiwan (online or onsite) is aimed at anyone who wishes to understand the basics of UAS and apply drone technology in planning, operations, management, and analysis for various industries.

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

• Gain fundamental knowledge of UAVs and drones.
• Learn about drone classifications and uses to find suitable UAVs that address different needs.
• Evaluate delivery options and regulations for the convenient operation of drones.
• Understand the risks and ethics of using drone technology.
• Explore future uses and capabilities of UAVs including integration with other technologies.

This instructor-led live training in Taiwan (online or onsite) is tailored for beginner to intermediate-level participants who wish to learn how to utilize drones and photogrammetry techniques for infrastructure supervision in construction projects.

Upon completing this training, participants will be able to:

• Grasp the fundamental concepts of drones and photogrammetry.
• Formulate and execute drone flight plans for construction sites.
• Conduct photogrammetry tracking and generate detailed maps and 3D models.
• Leverage photogrammetry data for infrastructure supervision and issue detection.
• Utilize drone technology to enhance construction site safety and operational efficiency.

This instructor-led, live training in Taiwan (online or onsite) is designed for agricultural technicians, researchers, and engineers who aim to leverage aerial robotics to optimize data collection and analysis in agriculture.

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

• Understand drone technology and the regulations surrounding its use.
• Deploy drones to acquire, process, and analyze crop data to improve farming and agricultural methods.

The Evo Max 4T is a professional-grade drone designed for advanced aerial operations, inspections, and data collection.

This instructor-led, live training (online or onsite) is aimed at beginner-level to intermediate-level operators who wish to safely and effectively use the Evo Max 4T for professional applications and prepare for official certification.

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

• Understand the technical specifications and operation of the Evo Max 4T drone.
• Apply operational safety procedures in aerial activities.
• Comply with current AAC and local drone regulations.
• Implement best practices for efficient and safe drone operations.
• Prepare for certification/licensing through theoretical and practical training.

Format of the Course

• Interactive lecture and discussion.
• Hands-on practice with drone equipment and simulators.
• Practical exercises and real flight scenarios.

Course Customization Options

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

This instructor-led, live training (available online or onsite) is designed for developers who wish to employ Google’s ML Kit to develop machine learning models optimized for mobile device processing.

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

• Establish the necessary development environment to commence creating machine learning features for mobile applications.
• Integrate new machine learning technologies into Android and iOS applications utilizing ML Kit APIs.
• Enhance and optimize existing applications using the ML Kit SDK for on-device processing and deployment.

Practical Rapid Prototyping for Robotics with ROS 2 & Docker is a hands-on course designed to help developers build, test, and deploy robotic applications efficiently. Participants will learn how to containerize robotics environments, integrate ROS 2 packages, and prototype modular robotic systems using Docker for reproducibility and scalability. The course emphasizes agility, version control, and collaboration practices suitable for early-stage development and innovation teams.

This instructor-led, live training (online or onsite) is aimed at beginner-level to intermediate-level participants who wish to accelerate robotics development workflows using ROS 2 and Docker.

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

• Set up a ROS 2 development environment within Docker containers.
• Develop and test robotic prototypes in modular, reproducible setups.
• Use simulation tools to validate system behavior before hardware deployment.
• Collaborate effectively using containerized robotics projects.
• Apply continuous integration and deployment concepts in robotics pipelines.

Format of the Course

• Interactive lectures and demonstrations.
• Hands-on exercises with ROS 2 and Docker environments.
• Mini-projects focused on real-world robotic applications.

Course Customization Options

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

This instructor-led, live training in Taiwan (online or onsite) is designed for data scientists and software engineers who wish to utilize Random Forest for developing machine learning algorithms tailored for large datasets.

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

• Establish the necessary development environment to commence building machine learning models with Random Forest.
• Comprehend the advantages of Random Forest and apply it to solve classification and regression problems.
• Learn techniques for handling large datasets and interpreting the multiple decision trees inherent in Random Forest.
• Evaluate and optimize machine learning model performance by fine-tuning hyperparameters.

During this instructor-led live training in Taiwan, participants will learn how to start using ROS for their robotics projects through the use of robotics visualization and simulation tools.

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

• Understand the basics of ROS.
• Learn how to create a basic robotics project using ROS.
• Learn how to use different tools for robotics including simulation and visualization tools.

This instructor-led, live training in Taiwan (online or onsite) targets beginner-level to intermediate-level, and potentially advanced-level robotics developers who wish to learn how to use ROS to program mobile robots using Python.

Upon completing this training, participants will be able to:

• Establish a development environment that includes ROS, Python, and a mobile robot platform.
• Create and execute ROS nodes, topics, services, and actions using Python.
• Leverage ROS tools and utilities to monitor and debug ROS applications.
• Utilize ROS packages and libraries to accomplish common tasks for mobile robots.
• Integrate ROS with other frameworks and tools.
• Perform troubleshooting and debugging of ROS applications.