Machine Learning for Roboticsのトレーニングコース

Aerial Robotics is the technology that deals with the designing and modeling of drones, also known as Unmanned Aerial Vehicles (UAVs) and quadrotors. It solves the challenge of autonomous and intelligent flight for various industrial applications.

This instructor-led, live training (online or onsite) is aimed at engineers and developers who wish to design, develop, and test aerial vehicles through exploring various aerial robotics concepts and tools.

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

• Understand the basics of aerial robotics.
• Model and design UAVs and quadrotors.
• Learn about the basics of flight control and motion planning.
• Learn how to use different simulation tools for aerial robotics.

Format of the Course

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

Course Customization Options

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

Drones (also known as unmanned aerial vehicles or UAVs) are unmanned devices that fly autonomously to complete various tasks in many fields and industries. Drone technology's efficiency and technical capabilities make it useful in many practical applications, such as rescue missions and terrain mapping for agriculture.

This instructor-led, live training (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.

Format of the Course

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

Course Customization Options

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

Drones, or unmanned aerial vehicles (UAVs), are becoming prominent devices for optimizing farming and agricultural methods. Drone technology provides efficient solutions to agricultural needs, such as reduced time and costs in acquiring crop data, and better sustainability.

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

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

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

Format of the Course

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

Course Customization Options

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

ArduPilot is an open source, unmanned vehicle Autopilot Software Suite for controlling drones.

This instructor-led, live training (online or onsite) is aimed at developers and technical persons who wish to design and develop an unmanned drone.

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

• Setup a suitable development environment.
• Select and apply the right tools for programming a drone.
• Understand and configure the firmware, middleware and API stack.
• Test and debug their code using drone simulation software.

Format of the course

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

Course Customization Options

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

ROS stands for Robot Operating System. It is an open source framework that is used to aid in the development of advanced robots.

In this instructor-led, live training, 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.

Format of the course

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

ROS (Robot Operating System) is a framework that provides tools and libraries for developing robotic applications. Python is one of the supported programming languages in ROS. A mobile robot is a robot that can move autonomously or semi-autonomously in an environment.

This instructor-led, live training (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.

Format of the Course

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

Course Customization Options

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

The Azure Bot Service combines the power of the Microsoft Bot Framework and Azure functions to enable rapid development of intelligent bots.

In this instructor-led, live training, participants will learn how to easily create an intelligent bot using Microsoft Azure

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

• Learn the fundamentals of intelligent bots
• Learn how to create intelligent bots using cloud applications
• Understand how to use the Microsoft Bot Framework, the Bot Builder SDK, and the Azure Bot Service
• Understand how to design bots using bot patterns
• Develop their first intelligent bot using Microsoft Azure

Audience

• Developers
• Hobbyists
• Engineers
• IT Professionals

Format of the course

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

A bot or chatbot is like a computer assistant that is used to automate user interactions on various messaging platforms and get things done faster without the need for users to speak to another human.

In this instructor-led, live training, participants will learn how to get started in developing a bot as they step through the creation of sample chatbots using bot development tools and frameworks.

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

• Understand the different uses and applications of bots
• Understand the complete process in developing bots
• Explore the different tools and platforms used in building bots
• Build a sample chatbot for Facebook Messenger
• Build a sample chatbot using Microsoft Bot Framework

Audience

• Developers interested in creating their own bot

Format of the course

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

Mechatronics (a.k.a. mechatronic engineering) is a combination of mechanical, electronics and computer science.

This instructor-led, live training (online or onsite) is aimed at engineers who wish to learn about the applicability of artificial intelligence to mechatronic systems.

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

• Gain an overview of artificial intelligence, machine learning, and computational intelligence.
• Understand the concepts of neural networks and different learning methods.
• Choose artificial intelligence approaches effectively for real-life problems.
• Implement AI applications in mechatronic engineering.

Format of the Course

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

Course Customization Options

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

A Smart Robot is an Artificial Intelligence (AI) system that can learn from its environment and its experience and build on its capabilities based on that knowledge. Smart Robots can collaborate with humans, working along-side them and learning from their behavior. Furthermore, they have the capacity for not only manual labor, but cognitive tasks as well. In addition to physical robots, Smart Robots can also be purely software based, residing in a computer as a software application with no moving parts or physical interaction with the world.

In this instructor-led, live training, participants will learn the different technologies, frameworks and techniques for programming different types of mechanical Smart Robots, then apply this knowledge to complete their own Smart Robot projects.

The course is divided into 4 sections, each consisting of three days of lectures, discussions, and hands-on robot development in a live lab environment. Each section will conclude with a practical hands-on project to allow participants to practice and demonstrate their acquired knowledge.

The target hardware for this course will be simulated in 3D through simulation software. The ROS (Robot Operating System) open-source framework, C++ and Python will be used for programming the robots.

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

• Understand the key concepts used in robotic technologies
• Understand and manage the interaction between software and hardware in a robotic system
• Understand and implement the software components that underpin Smart Robots
• Build and operate a simulated mechanical Smart Robot that can see, sense, process, grasp, navigate, and interact with humans through voice
• Extend a Smart Robot's ability to perform complex tasks through Deep Learning
• Test and troubleshoot a Smart Robot in realistic scenarios

Audience

• Developers
• Engineers

Format of the course

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

Note

• To customize any part of this course (programming language, robot model, etc.) please contact us to arrange.

H2O AutoML is an artificial intelligence platform that automates the process of building, selecting and optimizing large numbers of machine learning models.

This instructor-led, live training (online or onsite) is aimed at data scientists who wish to use H2O AutoML to automate the process of building and selecting the best machine learning algorithm and parameters.

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

• Automate the machine learning workflow.
• Automatically train and tune many machine learning models within a specified time range.
• Train stacked ensembles to arrive at highly predictive ensemble models.

Format of the Course

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

Course Customization Options

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

Auto-sklearn is a Python package built around the scikit-learn machine learning library. It automatically searches for the right learning algorithm for a new machine learning dataset and optimizes its parameters.

This instructor-led, live training (online or onsite) is aimed at machine learning practitioners who wish to use Auto-sklearn to automate the process of selecting and optimizing a machine learning model.

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

• Automate the process of training highly efficient machine learning models.
• Build highly accurate machine learning models while bypassing the more tedious tasks of selecting, training and testing different models.
• Use the power of machine learning to solve real-world business problems.

Format of the Course

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

Course Customization Options

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

Auto-Keras (Also known as Autokeras or Auto Keras) is an open source Python library for automated machine learning (AutoML).

This instructor-led, live training (online or onsite) is aimed at data scientists as well as less technical persons who wish to use Auto-Keras to automate the process of selecting and optimizing a machine learning model.

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.

Format of the Course

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

Course Customization Options

• To request a customized training for this course, please contact us to arrange.
• To learn more about Auto-Keras, please visit: https://autokeras.com/

Stable Diffusion is a powerful deep learning model that can generate detailed images based on text descriptions. 

This instructor-led, live training (online or onsite) is aimed at intermediate to advanced-level data scientists, machine learning engineers, deep learning researchers, and computer vision experts who wish to expand their knowledge and skills in deep learning for text-to-image generation.

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

• Understand advanced deep learning architectures and techniques for text-to-image generation.
• Implement complex models and optimizations for high-quality image synthesis.
• Optimize performance and scalability for large datasets and complex models.
• Tune hyperparameters for better model performance and generalization.
• Integrate Stable Diffusion with other deep learning frameworks and tools.

Format of the Course

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

Course Customization Options

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

Stable Diffusion is a powerful deep learning model that can generate detailed images based on text descriptions. 

This instructor-led, live training (online or onsite) is aimed at data scientists, machine learning engineers, and computer vision researchers who wish to leverage Stable Diffusion to generate high-quality images for a variety of use cases.

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

• Understand the principles of Stable Diffusion and how it works for image generation.
• Build and train Stable Diffusion models for image generation tasks.
• Apply Stable Diffusion to various image generation scenarios, such as inpainting, outpainting, and image-to-image translation.
• Optimize the performance and stability of Stable Diffusion models.

Format of the Course

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

Course Customization Options

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