Machine Learning for Robotics Training Course

This instructor-led, live training in New Zealand (online or on-site) is designed for data scientists and software engineers who wish to use AdaBoost to develop boosting algorithms for machine learning with Python.

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

• Set up the necessary development environment to begin building machine learning models with AdaBoost.
• Understand the ensemble learning approach and how to implement adaptive boosting.
• Learn how to build AdaBoost models to enhance machine learning algorithms in Python.
• Apply hyperparameter tuning to improve the accuracy and performance of AdaBoost models.

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

This instructor-led, live training (available online or on-site) is designed for intermediate to advanced-level professionals who wish to apply advanced drone and photogrammetry workflows—including geodetic controls and high-precision mapping techniques—to complex infrastructure projects.

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

• Apply 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.
• Analyse photogrammetry data using GIS software for structural health monitoring, deformation detection, and compliance tracking.

Course Format

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

Course Customisation Options

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

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

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

• Understand the fundamentals of aerial robotics.
• Model and design UAVs and quadrotors.
• Gain an understanding of the basics of flight control and motion planning.
• Learn how to utilise different 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 online or on-site) is tailored for intermediate-level developers and technical professionals who wish to design, program, and test unmanned aerial vehicles (UAVs) using ArduPilot.

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

• Set up a complete development environment for ArduPilot.
• Configure firmware, middleware, and MAVLink APIs for UAV control.
• Use SITL simulation to safely test and debug drone behaviour.
• 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.
• Extensive exercises and practical sessions.
• Hands-on implementation in a live lab environment.

Course Customisation Options

• This training is based on the open-source autopilot software ArduPilot. To request a customised version of this course, please contact us to arrange.

This instructor-led, live training in New Zealand (delivered online or on-site) is designed for data scientists, as well as less technical professionals, who wish to use Auto-Keras to automate the selection and optimisation of machine learning models.

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

• Automate the process of training highly efficient machine learning models.
• Automatically search for the best parameters for deep learning models.
• Build highly accurate machine learning models.
• Apply machine learning to solve real-world business challenges.

This instructor-led, live training (online or on-site) is designed for technical participants with a background in machine learning who wish to optimise models for detecting complex patterns in big data using AutoML frameworks.

This instructor-led, live training in New Zealand (online or onsite) is aimed at data scientists and data analysts who wish to automate, evaluate and manage predictive models using DataRobot's machine learning capabilities.

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

• Load datasets into DataRobot to analyse, assess and perform quality checks on data.
• Build and train models to identify key variables and meet prediction targets.
• Interpret models to generate valuable insights that support business decision-making.
• Monitor and manage models to maintain optimised prediction performance.

This instructor-led, live training in New Zealand (available online or on-site) is designed for anyone wishing to understand the fundamentals of Unmanned Aerial Systems (UAS) and apply drone technology in planning, operations, management, and analysis across various industries.

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

• Acquire foundational knowledge of UAVs and drones.
• Understand drone classifications and use cases to identify suitable UAVs that meet diverse needs.
• Evaluate delivery options and regulatory requirements for the effective operation of drones.
• Appreciate the risks and ethical considerations associated with drone technology.
• Explore future applications and capabilities of UAVs, including their integration with other emerging technologies.

This instructor-led, live training in New Zealand (online or on-site) is designed for beginner to intermediate-level participants who wish to learn how to use drones and photogrammetry techniques for infrastructure supervision in construction projects.

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

• Understand the fundamentals of drones and photogrammetry.
• Develop and execute drone flight plans for construction sites.
• Perform photogrammetry tracking and create detailed maps and 3D models.
• Use photogrammetry data for infrastructure supervision and issue detection.
• Apply drone technology to improve construction site safety and efficiency.

This instructor-led, live training in New Zealand (available online or on-site) is designed for agriculture technicians, researchers, and engineers who wish to apply aerial robotics to enhance data collection and analysis in agriculture.

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

• Understand drone technology and the associated regulations.
• Deploy drones to acquire, process, and analyse crop data to improve farming and agricultural practices.

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

This instructor-led, live training (available online or on-site) is designed for beginner 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 CAA and local drone regulations.
• Implement best practices for efficient and safe drone operations.
• Prepare for certification/licensing through theoretical and practical training.

Course Format

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

Course Customisation Options

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

Practical Rapid Prototyping for Robotics with ROS 2 & Docker is a hands-on course designed to assist developers in building, testing, and deploying robotic applications with greater efficiency. Participants will learn how to containerise robotics environments, integrate ROS 2 packages, and prototype modular robotic systems using Docker to ensure reproducibility and scalability. The course places strong emphasis on agility, version control, and collaborative practices tailored for early-stage development and innovation teams.

This instructor-led, live training (available online or on-site) is aimed at beginner to intermediate-level participants who wish to accelerate their 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 behaviour before hardware deployment.
• Collaborate effectively using containerised robotics projects.
• Apply continuous integration and deployment concepts within robotics pipelines.

Format of the Course

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

Course Customisation Options

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

This instructor-led, live training in New Zealand (online or on-site) is designed for data scientists and software engineers who wish to harness Random Forest to build machine learning models for large-scale datasets.

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

• Set up the required development environment to begin building machine learning models using Random Forest.
• Understand the benefits of Random Forest and how to apply it to solve classification and regression problems.
• Learn how to manage large datasets and interpret the output of multiple decision trees within the Random Forest framework.
• Evaluate and optimise machine learning model performance through hyperparameter tuning.

In this instructor-led, live training in New Zealand, participants will learn how to begin using ROS for their robotics projects through the use of robotics visualisation and simulation tools.

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

• Understand the fundamentals of ROS.
• Learn how to create a basic robotics project using ROS.
• Learn how to use various robotics tools, including simulation and visualisation tools.

This instructor-led, live training in New Zealand (available online or on-site) is designed for beginner to intermediate-level, and potentially advanced-level, robotics developers who wish to learn how to use ROS to program mobile robots using Python.

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

• Set up a development environment that includes ROS, Python, and a mobile robot platform.
• Create and run ROS nodes, topics, services, and actions using Python.
• Use ROS tools and utilities to monitor and debug ROS applications.
• Use ROS packages and libraries to perform common tasks for mobile robots.
• Integrate ROS with other frameworks and tools.
• Troubleshoot and debug ROS applications.