The Latest Infos
At present, the presence training cannot be offered. If you are interested in an online training, please contact us.
Contact Person
NGNI, Anne Halbich, Team, IIoT
Anne Halbich
Business Unit INNO
+49 30 3463-7346
Maschinellem Lernen und Edge-KI
PhonlamaiPhoto

Machine Learning on the Edge Training

Image processing and analysis in the Industry 4.0 environment

The Challenge

With increasing digitalization, companies manage a steadily growing stock of data in many areas of their operational business. This includes, for example, access information to websites, sales figures or even sensor information recorded by machines in production. These data volumes pose an increasing challenge in the industrial environment, since they must first be transferred to appropriate computers before they can be analysed. This can be difficult in terms of bandwidth and occurring signal failures. As a result, the context and meaning of this information can only be captured inadequately and with a high level of effort by employees.

The solution

The trend is moving away from centralized evaluation to decentralized processing of data at the point of collection. This architecture, known as Edge Computing or Edge-AI (Artificial Intelligence), allows the network nodes collecting data to perform on-site analyses, and only the interpretations of the situation and states are forwarded. This core information can also be transmitted with limited bandwidth. The course provides general basics of machine learning and AI-supported image processing.

After the seminar, you will...

  • Know how to understand basic machine learning procedures.

  • Know how to implement simple Edge-AI procedures.

  • Understand Edge-AI challenges.

  • Be able to define application requirements for machine learning approaches.

This seminar offers you an introduction into...

  • Selected Edge-AI topics.

  • Selected topics like Edge-AI.

  • The Edge Computing Paradigm.

The target groups are...

  • Product Managers

  • Project leaders

  • Analysts

  • Developers of machine learning solutions

Course Data

Duration: 1 day (09:00 am - 17:00 pm)

Language: German or English (slides in English)

Location: Fraunhofer FOKUS, Berlin

Requirements: none

Course fee: 900,00 Euro (incl. lunch and drinks during breaks)

The Latest Infos

At present, the presence training cannot be offered. If you are interested in an online training, please contact us.

Registration

                               
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Please confirm that you have read and agreed to our below-mentioned data privacy protection policies as well as to our general terms and conditionges.

Please confirm that you have read and agreed to our below-mentioned data privacy protection policies as well as to our general terms and conditionges.


Privacy enhancement

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As part of the registration for “Time Sensitive Networking” we require the following compulsory information:

  • Title,
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Additionally you can provide us following optional information:

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We collect the required data in order to identify you as participant of the event, to check the provided information for plausibility, to reserve a place for the participant in the event and to establish a contract with you. We also want to supply the participant with information during and after the event, offer the participant an optimal participation and allow us to plan and execute a smooth running event.

We need the payment data to collect the participation fees.

Collecting the voluntary information allows us to plan and conduct the event according to the interests of the participants in an age-appropriate fashion.

We process the data based on your enquiry and for the declared purposes as prescribed by Article 6 para. 1, page 1, lit. b GDPR to perform the contractual obligations toward the participants and meet the conditions precedent to entering into the contract.

We will store the personal data collected in context with the event until the end of the regular limitation period of three (3) years following the end of the year of the event. We will then delete the data unless we are obligated by law to store the data for a longer period according to compulsory safekeeping and documentation obligations pursuant to Article 6 para. 1, page 1 lit. c GDPR and in particular according to § 147 AO [General German Fiscal Code]) or unless you have agreed to a longer data storage according to Article 6 para. 1, page 1 lit. a GDPR. In case of longer data storage, we shall process the data solely to the extent mandated by law or according to your permission. As for all else, the further processing of the data shall be barred.

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