Machine Learning for Robotics Training Course

This instructor-led, live training in Uzbekistan (available online or on-site) is designed for data scientists and software engineers who wish to use AdaBoost to build 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 start building machine learning models using AdaBoost.
• Understand the ensemble learning approach and learn 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 indispensable tools for high-precision infrastructure supervision. By combining advanced geodesy principles, real-time modeling, and high-accuracy drone mapping, professionals can enhance their insights, accuracy, and productivity in construction environments.

This instructor-led, live training (available online or onsite) is designed for intermediate to advanced professionals who aim to implement advanced drone and photogrammetry workflows, including geodetic controls and high-precision mapping techniques, in complex infrastructure projects.

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

• Apply advanced photogrammetric methods such as 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 terrains and infrastructure geometries.
• Analyze photogrammetry data using GIS software to monitor structural health, deformation, and compliance.

Format of the Course

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

Course Customization Options

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

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

By the end of 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 a comprehensive open-source autopilot software suite designed for drones, rovers, and various unmanned vehicles. It offers sophisticated capabilities including autonomous navigation, real-time interaction with ground stations, and seamless integration with robotics middleware such as ROS2.

This instructor-led training session, available either online or in person, targets intermediate developers and technical experts looking to design, program, and test unmanned aerial vehicles (UAVs) utilizing the ArduPilot platform.

Upon completing this training, participants will gain the ability to:

• Establish a fully functional development environment for ArduPilot.
• Configure firmware, middleware, and MAVLink APIs to control UAVs.
• Utilize SITL simulation to safely test and debug drone operations.
• Enhance ArduPilot capabilities with ROS2 and connect it to external sensors or tools.
• Create autonomous flight logic and execute complete UAV missions from start to finish.

Course Format

• Engaging lectures and interactive discussions.
• Extensive hands-on exercises and practice sessions.
• Practical implementation within a live-lab environment.

Customization Options

• This program focuses on the open-source ArduPilot autopilot software. For tailored training needs, please reach out to us to arrange a customized session.

This instructor-led, live training in Uzbekistan (available online or on-site) is tailored for data scientists as well as less technical professionals who wish to leverage 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 optimal parameters for deep learning models.
• Construct highly accurate machine learning models.
• Harness the power of machine learning to address real-world business challenges.

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

This instructor-led, live training in Uzbekistan (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 in 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 (available online or onsite) is designed for anyone interested in understanding the basics of UAS and applying 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 their uses to identify suitable UAVs for various needs.
• Assess delivery options and regulatory frameworks for efficient drone operations.
• Recognize the risks and ethical considerations associated with drone technology.
• Explore future applications and potential integrations of UAVs with other technologies.

This instructor-led, live training in Uzbekistan (online or onsite) is tailored for beginner to intermediate participants aiming 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 Uzbekistan (online or onsite) is designed for agriculture technicians, researchers, and engineers who aim to utilize aerial robotics to optimize data collection and analysis in agriculture.

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

• Gain a comprehensive understanding of drone technology and its regulatory framework.
• Deploy drones to collect, process, and analyze crop data to enhance 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.

Course Format

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

Course Customisation Options

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

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 emphasises agility, version control, and collaborative 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 behaviour before hardware deployment.
• Collaborate effectively using containerised 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 Customisation Options

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

This instructor-led, live training in Uzbekistan (available online or on-site) is designed for data scientists and software engineers who wish to use Random Forest to develop machine learning algorithms for large-scale datasets.

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

• Set up the necessary development environment to begin building machine learning models using Random Forest.
• Understand the advantages of Random Forest and learn how to apply it to solve classification and regression problems.
• Acquire skills in handling large datasets and interpreting multiple decision trees within the Random Forest framework.
• Evaluate and optimize machine learning model performance by fine-tuning hyperparameters.

In this instructor-led, live training in Uzbekistan, participants will learn how to utilize ROS for their robotics projects by employing various robotics visualization and simulation tools.

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

• Grasp the fundamental concepts of ROS.
• Develop a basic robotics project using ROS.
• Utilize various tools for robotics, including simulation and visualization tools.

This instructor-led, live training (online or onsite) is tailored for beginner to intermediate, and potentially advanced-level robotics developers who wish to learn how to program mobile robots using ROS and 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.
• Leverage ROS packages and libraries to perform common mobile robot tasks.
• Integrate ROS with other frameworks and tools.
• Troubleshoot and debug ROS applications effectively.