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Google Cloud Training

Questo corso introduce i concetti di interpretabilità e la trasparenza dell'AI. Parla dell'importanza della trasparenza dell'AI per sviluppatori ed engineer. Illustra metodi e strumenti pratici per aiutare a raggiungere interpretabilità e trasparenza sia nei dati che nei modelli di AI.

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What's inside

Syllabus

Introduzione al corso
Questo modulo introduce la struttura e gli obiettivi del corso.
Interpretabilità e trasparenza dell'AI
Questo modulo è incentrato su interpretabilità e trasparenza nell'AI. Fornisce varie tecniche e strumenti per aiutare a raggiungere interpretabilità e trasparenza sia nei dati che nei modelli di AI.
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Riepilogo del corso
Questo modulo fornisce un riepilogo dell'intero corso coprendo i concetti, gli strumenti e le tecnologie più importanti.
Risorse del corso
Link PDF per gli studenti a tutti i moduli

Good to know

Know what's good
, what to watch for
, and possible dealbreakers
Il corso illustra i concetti di interpretabilità e trasparenza dell'AI, argomenti fondamentali per sviluppatori e tecnici del settore
Il corso offre metodi e strumenti per raggiungere trasparenza e interpretabilità in dati e modelli di AI
Il corso è erogato da Google Cloud Training, esperti riconosciuti nel campo dell'intelligenza artificiale

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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: Interpretability & Transparency - Italiano with these activities:
Review basic machine learning concepts
Refresh your understanding of machine learning before the course begins to ensure that you are prepared for success.
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  • Read through your notes or study materials from previous courses in machine learning.
  • Do practice questions to test your understanding of the fundamental concepts.
  • Attend a workshop or online tutorial on machine learning.
Rivedi i concetti fondamentali di machine learning
Una solida comprensione dei concetti fondamentali del machine learning ti aiuterà a comprendere meglio i concetti di interpretabilità e trasparenza dell'AI.
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  • Rivedi i materiali del tuo corso precedente di machine learning.
  • Completa gli esercizi di ripasso forniti.
  • Partecipa a un workshop di ripasso di machine learning.
Follow tutorials on interpretability and transparency in AI
Supplement your learning with tutorials to gain a deeper understanding of interpretability and transparency in AI.
Browse courses on Interpretability
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  • Search for online tutorials on interpretability and transparency in AI.
  • Follow the tutorials and complete the exercises provided.
  • Take notes and record your learnings.
Four other activities
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Practice interpreting AI models
Develop your skills in interpreting AI models to gain a better understanding of their predictions and limitations.
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  • Find a dataset and create a simple AI model.
  • Use interpretability techniques to analyze the model's predictions.
  • Write a report summarizing your findings.
Develop a tool or resource to explain interpretability and transparency in AI
Demonstrate your understanding by creating a tool or resource that can help others learn about interpretability and transparency in AI.
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  • Brainstorm ideas for a tool or resource that could help explain interpretability and transparency in AI.
  • Develop a plan for creating your tool or resource.
  • Create your tool or resource.
  • Share your tool or resource with others.
Participate in a hackathon or competition on interpretability or transparency in AI
Challenge yourself and test your skills by participating in a hackathon or competition focused on interpretability or transparency in AI.
Browse courses on Interpretability
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  • Find a hackathon or competition that aligns with your interests.
  • Form a team or work independently.
  • Develop a solution to the challenge.
  • Present your solution and compete against other participants.
Contribute to an open-source project on interpretability or transparency in AI
Contribute to the development of interpretability and transparency in AI by participating in open-source projects.
Browse courses on Interpretability
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  • Find an open-source project that aligns with your interests.
  • Review the project's documentation and codebase.
  • Identify an area where you can contribute.
  • Submit a pull request with your contribution.

Career center

Learners who complete Responsible AI for Developers: Interpretability & Transparency - Italiano will develop knowledge and skills that may be useful to these careers:

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