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1-day training
Artificial Intelligence

Events

vous avez a project on the base of the module processor, the phytec teams on your case, you develop on the series

Use artificial intelligence for your projects! The training starts with the basic terms of AI and provides you with the necessary knowledge and skills with which you can set up your own image classifier as an exemplary AI application. The training focuses on deep learning in the field of image processing. (Previous knowledge of Python is an advantage, but not a requirement.)

Training objectives: 
After the lecture you will have an overview of the variety of methods of artificial intelligence and will recognize how you can use AI yourself.

Who is the training for?
Developer, who are / should be responsible for AI solutions in your company
Project manager, who want to find out more about the possibilities of AI and basically want to have an overview of the structure of an AI project. What is behind / in an AI solution?
Enthusiasts, who want to participate in the latest technology trends.
AI beginners without a corporate background

Speaker: Dr. Jan Werth, M.Sc. - data scientist
Dr. Jan Werth is an expert in the field of machine learning and deep learning with a longstanding background in communications technology and digital signal processing. At PHYTEC he heads the AI ​​competence center.

Training package:
+ All-day catering
+ Training documents

Here in Mainz: € 189 per person plus VAT.
Robert-Koch-Str. 39 55129 Mainz

At your company: 2.800, - € (plus VAT.)

Welcome and introduction to the guestse

Overview and explanation of an AI process

  • Necessary steps and sequence of an AI process

Technical discussions - coffee & snacks

Explanation of "deep learning"

  • Mathematical background and network structure

  • Explanation of important parameters

  • Correct evaluation of the results

Lunch break - project discussions

Overview of the roadmap from NXP

  • What is an eIQ and why should you use it?

  • Possibilities to use eIQ on Phytec hardware

  • Demonstration of a sample application

Data and signal preparation for a successful AI

  • Important questions

  • Instructions for action

Break - project talks

The tools for an AI project

  • Azure - DSVMs

  • jupyter notebooks

  • Etc

Embedded hardware and AI

Upon request
Explanation of code examples
and / or ethical discussion