Machine Learning for Robotics Training Course

This instructor-led, live training in Norway (available online or on-site) is designed for data scientists and software engineers who wish to employ AdaBoost to create boosting algorithms for machine learning using Python.

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

• Establish the necessary development environment to initiate the creation of machine learning models with AdaBoost.
• Comprehend the ensemble learning approach and how to execute adaptive boosting.
• Learn the process of constructing AdaBoost models to enhance machine learning algorithms in Python.
• Utilize hyperparameter tuning to improve the accuracy and performance of AdaBoost models.

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

This instructor-led live training, available both online and onsite, is designed for intermediate to advanced professionals seeking to implement sophisticated drone and photogrammetry workflows. The course covers geodetic controls and high-precision mapping techniques tailored for 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 suitable for large-scale infrastructure sites.
• Design precision flight missions customized for complex terrain and infrastructure geometry.
• Analyze photogrammetry data using GIS software to monitor structural health, track deformation, and ensure compliance.

Format of the Course

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

Course Customization Options

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

This instructor-led live training in Norway (online or onsite) is designed for engineers and developers interested in designing, developing, and testing aerial vehicles through the exploration of various aerial robotics concepts and tools.

Upon completing this training, participants will be able to:

• Understand the fundamentals of aerial robotics.
• Model and design UAVs and quadrotors.
• Learn the basics of flight control and motion planning.
• Learn how to use 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 including autonomous navigation, real-time communication with ground stations, and integration with robotics middleware such as ROS2.

This instructor-led live training (available online or onsite) targets intermediate-level developers and technical professionals who want to design, program, and test unmanned aerial vehicles (UAVs) using ArduPilot.

Upon completing 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.

Format of the Course

• Interactive lecture and discussion.
• Ample exercises and practice opportunities.
• Hands-on implementation in a live-lab environment.

Course Customization Options

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

This instructor-led live training in Norway (online or on-site) is intended for data scientists and those with less technical expertise who wish to employ Auto-Keras to automate the process of selecting and optimizing 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.
• Use the power of machine learning to solve real-world business problems.

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

This instructor-led live training in Norway (online or onsite) is designed for data scientists and 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:

• Import datasets into DataRobot to analyze, evaluate, and perform quality checks.
• Construct 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 optimized prediction performance.

This instructor-led live training in Norway (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 Norway (online or on-site) is designed for participants at a beginner to intermediate level who want to learn how to utilize drones and photogrammetry techniques for infrastructure supervision within construction projects.

Upon completing this training, participants will be able to:

• Grasp the core concepts of drones and photogrammetry.
• Create and implement drone flight plans for construction sites.
• Conduct photogrammetry tracking to produce detailed maps and 3D models.
• Leverage photogrammetry data for infrastructure supervision and issue identification.
• Utilize drone technology to enhance safety and efficiency at construction sites.

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

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

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

The Evo Max 4T is a professional-grade unmanned aerial vehicle engineered for sophisticated aerial tasks, infrastructure inspections, and comprehensive data acquisition.

This instructor-led training program, available either online or on-site, targets operators with beginner to intermediate skills who aim to utilize the Evo Max 4T safely and effectively for professional purposes while preparing for official certification.

Upon completing this training, participants will be equipped to:

• Grasp the technical specifications and operational mechanics of the Evo Max 4T.
• Execute rigorous safety protocols during aerial missions.
• Adhere to current AAC guidelines and local drone regulations.
• Apply industry best practices to ensure efficient and secure drone operations.
• Prepare for certification and licensing through a combination of theoretical study and practical application.

Course Format

• Interactive lectures and group discussions.
• Practical training using drone hardware and simulation software.
• Real-world flight exercises and scenario-based operations.

Customization Options

• To arrange tailored training for this course, please reach out to us for further details.

Practical Rapid Prototyping for Robotics with ROS 2 & Docker is a hands-on course designed to assist developers in efficiently building, testing, and deploying robotic applications. Participants will learn how to containerize robotics environments, integrate ROS 2 packages, and prototype modular robotic systems using Docker to ensure 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 (available online or onsite) is targeted at beginner to intermediate-level participants who wish to accelerate their robotics development workflows by leveraging 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.

Course Format

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

This instructor-led, live training in Norway (online or onsite) is aimed at data scientists and software engineers who wish to use Random Forest to build machine learning algorithms for large datasets.

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

• Set up the necessary development environment to start building machine learning models with Random Forest.
• Understand the advantages of Random Forest and how to implement it to resolve classification and regression problems.
• Learn how to handle large datasets and interpret multiple decision trees in Random Forest.
• Evaluate and optimize machine learning model performance by tuning the hyperparameters.

In this instructor-led live training in Norway, 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 Norway (online or onsite) is aimed at 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.

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.
• Troubleshooting and debugging ROS applications.