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Responsible AI for Developers

Fairness & Bias - Português

Google Cloud Training

Neste curso, apresentamos conceitos de IA responsável e princípios de IA. Ele contém técnicas para identificar e reduzir o viés e aplicar a imparcialidade nas práticas de ML/IA. Vamos abordar ferramentas e métodos práticos para implementar as práticas recomendadas de IA responsável usando produtos do Google Cloud e ferramentas de código aberto.

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What's inside

Syllabus

Introdução ao curso
Neste módulo, você vai conhecer a estrutura e os objetivos do curso.
Introdução à IA responsável
Neste módulo, teremos uma visão geral da IA responsável e vamos abordar os subtópicos desse tema e os princípios de IA do Google. Também veremos casos de estudo reais da IA responsável nos produtos do Google.
Read more
Viés e imparcialidade da IA
Neste módulo, vamos nos concentrar na imparcialidade e no viés da IA. Abordaremos várias técnicas e ferramentas para identificar e reduzir o viés usando dados e modelagem.
Resumo do curso
Neste módulo, fornecemos um resumo de todo o curso abordando os conceitos, as ferramentas e as tecnologias mais importantes.
Recursos do curso
Links para todos os módulos no PDF do estudante

Good to know

Know what's good
, what to watch for
, and possible dealbreakers
Fornece uma base sólida para iniciantes no campo de IA responsável
Traz estudos de caso da própria Google para ilustrar princípios da IA responsável
Inclui um módulo para resumir os principais conceitos, ferramentas e tecnologias abordadas
Não menciona explicitamente os pré-requisitos necessários

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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: Fairness & Bias - Português with these activities:
Revise the principles of artificial intelligence
Familiarize yourself with the fundamental concepts of AI, including its history, different types, and applications, to enhance your understanding of the course materials.
Browse courses on Artificial Intelligence
Show steps
  • Read introductory articles or books on AI
  • Watch video tutorials or online lectures on AI concepts
  • Review your notes or materials from previous courses related to AI
Compile resources on responsible AI practices
Enhance your knowledge and stay up-to-date by collecting and organizing relevant resources, such as articles, whitepapers, and industry reports, that provide insights into responsible AI practices.
Browse courses on Responsible AI
Show steps
  • Identify credible sources of information on responsible AI
  • Gather and review resources on AI ethics, best practices, and guidelines
  • Categorize and organize the resources for easy access
Attend industry events and conferences on responsible AI
Engage with professionals in the field of responsible AI by attending industry events and conferences, allowing you to learn about the latest developments and connect with experts in the field.
Browse courses on Responsible AI
Show steps
  • Identify relevant industry events and conferences
  • Prepare for the event by researching speakers and topics
  • Actively participate in discussions and networking sessions
Three other activities
Expand to see all activities and additional details
Show all six activities
Explore case studies of responsible AI implementations
Gain practical insights into real-world applications of responsible AI by examining case studies that demonstrate how organizations have implemented AI with ethical considerations.
Browse courses on Responsible AI
Show steps
  • Identify case studies of responsible AI implementations
  • Analyze the approaches and techniques used to ensure fairness and mitigate bias
  • Evaluate the outcomes and impact of these responsible AI implementations
Identify and mitigate bias in AI models
Strengthen your understanding of bias in AI models by practicing techniques for identifying and mitigating bias using data analysis and model evaluation methods.
Browse courses on AI Bias
Show steps
  • Review different types of bias in AI models
  • Analyze datasets for potential sources of bias
  • Apply bias mitigation techniques such as data sampling and算法调整
  • Evaluate the effectiveness of bias mitigation strategies
Develop an AI solution with responsible AI principles
Apply the principles of responsible AI to design and develop an AI solution that addresses real-world problems while considering ethical and societal implications.
Browse courses on Responsible AI
Show steps
  • Define the problem and identify the AI solution
  • Gather and prepare data responsibly
  • Develop the AI model with bias mitigation techniques
  • Evaluate and validate the AI solution for fairness and accuracy
  • Deploy the AI solution and monitor its impact

Career center

Learners who complete Responsible AI for Developers: Fairness & Bias - Português 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
Session
August 5, 2024 - September 16, 2024
Language
pt-BR
Good to know
Fornece uma base sólida para iniciantes no campo de IA responsável
Traz estudos de caso da própria Google para ilustrar princípios da IA responsável
Inclui um módulo para resumir os principais conceitos, ferramentas e tecnologias abordadas
Não menciona explicitamente os pré-requisitos necessários
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