We have up to 2 lots available for free training for a LIVE INSTRUCTOR-LED training event delivered ONLINE. It covers the same scope and content as a scheduled in-person class and delivers comparable learning outcomes.
The training is called the Essential Edge AI with Renesas RZ/V2L.
It is designed for engineers who need a practical understanding of deploying trained Neural Network models to constrained edge devices and includes creation and deployment of AI models with Renesas RZ/V2L high precision AI MPUs. From principles and procedures, to important rules and helpful tricks, the course enables attendees to appreciate the system’s perspective of embedding a deep learning model inference into an application and how to connect it to other parts of the system to make it useful.
The enrolled trainee would receive a receive a FREE Renesas RZ/V2L platform for prototyping AI applications, Thanks to our course partners: Renesas, Avnet and Farnell.
Who should attend?
Deep Learning practitioners who have a trained model and wish to deploy the model for an application in one or more of the following constrained edge device types - Linux based single board computers (x64 or ARM), Neural Network Accelerators or 32-bit Microcontrollers (such as a Cortex-M4)
Please note that the course does not delve into details of how to train a deep learning model or the basics of different neural network architectures. These details are covered in the Practical Deep Learning course. This course does not discuss the inference of large models (such as natural language processing) which are likely to run on Cloud servers.
Attendees should be familiar with and have experience of working with neural network models or completion of Practical Deep Learning training. Specifically, you should have:
- An understanding of different types of neural network models
- Use of Keras APIs to create and train models
- An understanding of metrics needed to evaluate a trained model
- Some background knowledge about edge devices, such as Linux based single board computers (x64 or ARM), Neural Network Accelerators or 32-bit Microcontrollers (such as a Cortex-M4)
- Attendees should also have good working knowledge of Python and C or C++ programming language.
How To Express Your Interest
If you are interested in this training, please provide some background on your current job, credentials, background and experience. You can leave a comment below or message me privately at @rscasny.