Artificial Intelligence (AI) in Automotive Training Course

This instructor-led, live training in the UK (online or onsite) is aimed at mostly engneers who wish to use Autosar to design automotive components.

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

• Install and configure Autosar.
• Set up a workflow.
• Navigate smoothly in the Autosar environment.
• Work efficiently.

In this instructor-led, live training in the UK (online or onsite), participants will learn to configure DEM as they step through the creation and customization of a sample AUTOSTAR (AUTomotiveOpen System ARchitecture) application.

This instructor-led, live training in the UK (online or onsite) is aimed at automotive engineers who wish to use AUTOSAR to design automotive motor controllers.

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

• Understand AUTOSAR architecture and methodology.
• Learn how to design motor controllers using AUTOSAR.

This instructor-led, live training in the UK (online or onsite) is aimed at advanced-level software developers who wish to gain deeper knowledge and understanding of AUTOSAR RTE systems, and master the skills required to develop and implement complex AUTOSAR RTE systems in their organization. It will cover advanced topics such as RTE design patterns, configuration, generation, testing, and debugging techniques, and various AUTOSAR RTE components.

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

• Analyze RTE requirements and design efficient RTE solutions for complex automotive applications.
• Develop and integrate AUTOSAR RTE components, such as software components, communication interfaces, and service interfaces.
• Optimize RTE performance by configuring RTE parameters, implementing custom RTE extensions, and applying best practices.
• Troubleshoot common RTE issues and implement effective debugging techniques.
• Utilize advanced RTE features, such as multicore support, security mechanisms, and distributed systems.

A two day course covering all principles related to AUTomotiveOpen System Architecture RunTime Environment, the most famous industrial standard for automotive software development; the course contains both basic topics and advanced topics which is very useful for automotive professionals

This instructor-led, live training in the UK (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

This instructor-led, live training in (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.

This instructor-led, live training in the UK (online or onsite) is aimed at biologists who wish to understand how AlphaFold works and use AlphaFold models as guides in their experimental studies.

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

• Understand the basic principles of AlphaFold.
• Learn how AlphaFold works.
• Learn how to interpret AlphaFold predictions and results.

This instructor-led, live training in the UK (online or onsite) is aimed at intermediate-level developers, data scientists, and AI practitioners who wish to leverage TensorFlow Lite for Edge AI applications.

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

• Understand the fundamentals of TensorFlow Lite and its role in Edge AI.
• Develop and optimize AI models using TensorFlow Lite.
• Deploy TensorFlow Lite models on various edge devices.
• Utilize tools and techniques for model conversion and optimization.
• Implement practical Edge AI applications using TensorFlow Lite.

This instructor-led, live training in the UK (online or onsite) is aimed at developers who wish to use TensorFlow Lite to deploy deep learning models on embedded devices.

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

• Install and configure Tensorflow Lite on an embedded device.
• Understand the concepts and components underlying TensorFlow Lite.
• Convert existing models to TensorFlow Lite format for execution on embedded devices.
• Work within the limitations of small devices and TensorFlow Lite, while learning how to expand the scope of operations that can be run.
• Deploy a deep learning model on an embedded device running Linux.

This instructor-led, live training in the UK (online or onsite) is aimed at developers who wish to use TensorFlow Lite to develop mobile applications with deep learning capabilities.

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

• Install and configure TensorFlow Lite.
• Understand the principles behind TensorFlow, machine learning and deep learning.
• Load TensorFlow Models onto an Android device.
• Enable deep learning and machine learning functionality such as computer vision and natural language recognition in a mobile application.

This instructor-led, live training in (online or onsite) is aimed at developers who wish to use TensorFlow Lite to develop iOS mobile applications with deep learning capabilities.

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

• Install and configure TensorFlow Lite.
• Understand the principles behind TensorFlow and machine learning on mobile devices.
• Load TensorFlow Models onto an iOS device.
• Run an iOS application capable of detecting and classifying an object captured through the device's camera.

This instructor-led, live training in the UK (online or onsite) is aimed at engineers who wish to write, load and run machine learning models on very small embedded devices.

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

• Install TensorFlow Lite.
• Load machine learning models onto an embedded device to enable it to detect speech, classify images, etc.
• Add AI to hardware devices without relying on network connectivity.

This instructor-led, live training in the UK (online or onsite) is aimed at researchers and developers who wish to use Chainer to build and train neural networks in Python while making the code easy to debug.

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

• Set up the necessary development environment to start developing neural network models.
• Define and implement neural network models using a comprehensible source code.
• Execute examples and modify existing algorithms to optimize deep learning training models while leveraging GPUs for high performance.

This instructor-led, live training in the UK (online or onsite) is aimed at developers or data scientists who wish to use Horovod to run distributed deep learning trainings and scale it up to run across multiple GPUs in parallel.

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

• Set up the necessary development environment to start running deep learning trainings.
• Install and configure Horovod to train models with TensorFlow, Keras, PyTorch, and Apache MXNet.
• Scale deep learning training with Horovod to run on multiple GPUs.