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Responsible AI for Developers

Fairness & Bias - Polski

Google Cloud Training

Questo corso introduce i concetti di AI responsabile e i principi dell'AI. Tratta le tecniche per identificare sostanzialmente l'equità e i bias e mitigare i bias nelle pratiche di AI/ML. Illustra metodi e strumenti pratici per implementare le best practice dell'AI responsabile utilizzando gli strumenti open source e i prodotti Google Cloud.

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What's inside

Syllabus

Wprowadzenie do szkolenia
W tej części przedstawiamy cele i strukturę szkolenia.
Wprowadzenie do odpowiedzialnej AI
Ta część zawiera omówienie różnych tematów związanych z odpowiedzialną AI oraz informacje o zasadach Google dotyczących AI. Przedstawia też studia przypadków związane z odpowiedzialną AI w usługach Google.
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Traffic lights

Read about what's good
what should give you pause
and possible dealbreakers
Explores responsible AI concepts and principles, making it relevant to those seeking to implement ethical AI practices in their work
Taught by Google Cloud Training, who are recognized for their expertise in AI and cloud computing
Provides techniques for identifying and mitigating biases in AI practices, which is crucial for developing fair and unbiased AI systems
Covers both theoretical foundations and practical implementation methods, ensuring a well-rounded understanding of responsible AI
Emphasizes the importance of responsible AI in the development and deployment of AI systems, making it highly relevant to practitioners in the field

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Reviews summary

Formazione pratica in ai responsabile

Secondo gli studenti, questo corso è molto utile per sviluppare competenze sull'Intelligenza Artificiale responsabile. Si concentra sull'introduzione di concetti e principi dell'IA, inclusa l'identificazione e la mitigazione di equità e bias nelle pratiche di AI/ML. Il corso illustra metodi e strumenti pratici per implementare le migliori pratiche dell'IA responsabile, utilizzando sia strumenti open source che prodotti Google Cloud. È particolarmente rilevante per gli sviluppatori che cercano una formazione concreta su come affrontare le sfide etiche e tecniche nel campo dell'IA.
Fornisce competenze utili e applicabili nell'IA responsabile.
"Un corso molto utile per sviluppare competenze sull'IA responsabile."

Activities

Be better prepared before your course. Deepen your understanding during and after it. Supplement your coursework and achieve mastery of the topics covered in Responsible AI for Developers: Fairness & Bias - Polski with these activities:
Partecipa a un hackathon incentrato sull'AI responsabile
Impegnati in una sfida pratica e collaborativa per risolvere problemi del mondo reale utilizzando l'AI responsabile.
Show steps
  • Cerca un hackathon incentrato sull'AI responsabile
  • Forma un team e sviluppa una soluzione innovativa
Segui i tutorial su TensorFlow per l'AI responsabile
Fornisce una guida passo passo per l'implementazione di tecniche AI responsabili utilizzando TensorFlow.
Browse courses on TensorFlow
Show steps
  • Completa il tutorial di base sull'AI responsabile
  • Segui i tutorial su argomenti specifici di interesse, come l'equità o l'interpretabilità
Show all two activities

Career center

Learners who complete Responsible AI for Developers: Fairness & Bias - Polski will develop knowledge and skills that may be useful to these careers:

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Course image
Level
Intermediate
Via
Coursera
Institution
Google Cloud
Instructor
Google Cloud Training
Language
Italiano
Transcript
Polski
Traffic lights
Read about what's good
what should give you pause
and possible dealbreakers
Explores responsible AI concepts and principles, making it relevant to those seeking to implement ethical AI practices in their work
Taught by Google Cloud Training, who are recognized for their expertise in AI and cloud computing
Provides techniques for identifying and mitigating biases in AI practices, which is crucial for developing fair and unbiased AI systems
Covers both theoretical foundations and practical implementation methods, ensuring a well-rounded understanding of responsible AI
Emphasizes the importance of responsible AI in the development and deployment of AI systems, making it highly relevant to practitioners in the field
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