AI for the Industry – Best Practice Workshop

Get to know more about Data Science and applied AI with industrial scope.

Participate in our Workshop and learn more about…

  • AI applications in the Industry
  • Application fields of Machine & Deep Learning
  • Business case modeling & identification of AI solutions
  • How-to strategy to build sustainable AI Roadmap by yourself



Join our Workshop

AI for the Industry – Best Practice Workshop

Get to know more about Data Science and applied AI with industrial scope.

Participate in our free Workshop and learn more about…

  • AI applications in the Industry
  • Application fields of Machine & Deep Learning
  • Business case modeling & identification of AI solutions
  • How-to strategy to build sustainable AI Roadmap by yourself



Join our Workshop

Testimonials

Durch die Teilnahme an dem gut strukturierten Webinar von innoSEP kann ich mir jetzt das Potential von KI im Umfeld der produzierenden Industrie sehr viel besser vorstellen. Es hat mir insbesondere aufgezeigt, dass bei einer KI-Implementierung die Integration von Fachwissen essentiell für Erfolg ist und der gezielte Einsatz von KI-Modellen ein wesentlicher Bestandteil des gesamten Projektablaufs sein sollte.

Andrea Rave

Oemeta Chemische Werke GmbH

Ansätze wie bei innoSEP ermöglichen es KI über „No-Code“ für kleine und mittelständische Unternehmen nutzbar zu machen und bieten so einen wichtigen Beitrag zum Erkenntnisgewinn in diesen Unternehmen.

Siebo Stamm

Lauscher Präzisionstechnik GmbH

Man hat einen guten Eindruck erhalten, welche Prozesse hinter einer KI-Lösung stehen und welche Vorbereitungen getroffen werden sollten, um KI-Lösungen im Unternehmen gewinnbringend zu implementieren.

Dipl.-Ing. Omar El Dsoki

Test Engineer / Projektmanagement, Automobilindustrie

  • Best practice examples for the application of artificial intelligence in industrial environment

    • 1/2 day
    • From 3 participants

  • Target group:

    • Executives
    • Project and department heads
    • Digitization managers

  • Requirement:

    It is beneficial to have theoretical knowledge in the use of machine and deep learning. First ideas for use cases are beneficiary.

  • Goals:

    You know the complexity and potential applications of machine and deep learning as a part of Artificial Intelligence. You know the potentials, obstacles and requirements of suitable AI applications in the industrial environment and you can identify your own use cases as a business case in your daily work. With the gained knowledge you can asses that feasibility, obstacles and value proposition of the identified pportunity. You can build roadmaps to successfully implement an AI application for the digitalization and optimization of your business processes.

  • Inhalte:

    • Introduction and overview of the methods of AI (machine and deep learning)
    • Established use cases for the use of AI in the industrial environment and their
    • added value
    • How to develop AI solutions guidance
    • Obstacles and requirements for implementation
    • Data Science vs. AI technology
    • Innovative business models in the context of AI solutions
    • Identification of a business case

    Technical assessment

    Business assessment

    Realization

    “How-to-start”

Book Best Practice Online Workshop

Would you like to expand your knowledge through us? Then register now for our online workshop!

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