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Explainable AI (XAI) for Ethical AI Development

 14 時間
This instructor-led, live training in 日本 (online or onsite) is aimed at intermediate-level professionals who wish to apply Explainable AI techniques to ensure fairness, transparency, and ethical AI systems. By the end of this training, participants will be able to:
  • Understand the role of XAI in ethical AI systems.
  • Implement XAI techniques to detect and mitigate bias in AI models.
  • Ensure transparency in AI model decision-making processes.
  • Align AI development with ethical and regulatory standards.
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Explainability in Deep Learning: Demystifying Black-Box Models

 21 時間
This instructor-led, live training in 日本 (online or onsite) is aimed at advanced-level professionals who wish to explore state-of-the-art XAI techniques for deep learning models, with a focus on building interpretable AI systems. By the end of this training, participants will be able to:
  • Understand the challenges of explainability in deep learning.
  • Implement advanced XAI techniques for neural networks.
  • Interpret decisions made by deep learning models.
  • Evaluate the trade-offs between performance and transparency.
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Advanced Techniques in Explainable AI (XAI)

 21 時間
This instructor-led, live training in 日本 (online or onsite) is aimed at advanced-level professionals who wish to enhance their understanding of XAI techniques for complex AI models. By the end of this training, participants will be able to:
  • Implement state-of-the-art XAI techniques in AI models.
  • Interpret deep learning models and their decisions.
  • Apply advanced model-agnostic and model-specific explainability methods.
  • Address challenges related to AI transparency in complex systems.
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Explainable AI (XAI) for Transparency in AI Models

 21 時間
This instructor-led, live training in 日本 (online or onsite) is aimed at intermediate-level to advanced-level professionals who wish to implement transparent AI systems in real-world applications. By the end of this training, participants will be able to:
  • Understand the importance of transparency in AI models.
  • Implement advanced XAI techniques to interpret complex models.
  • Enhance model transparency using SHAP, LIME, and other tools.
  • Address ethical concerns and fairness in AI models.
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Introduction to Explainable AI (XAI) for Beginners

 14 時間
This instructor-led, live training in 日本 (online or onsite) is aimed at beginner-level professionals who wish to learn the basics of Explainable AI and its role in developing responsible AI systems. By the end of this training, participants will be able to:
  • Understand the fundamental concepts of Explainable AI.
  • Explore the importance of transparency and interpretability in AI models.
  • Learn basic techniques for making AI models explainable.
  • Apply XAI techniques to simple machine learning models.
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Upcoming Courses

Explainability in Deep Learning: Demystifying Black-Box Models

2025-05-19 10:00
21 時間
Online
¥ 683316 ~ (オンライン)

Explainable AI (XAI) for Transparency in AI Models

2025-06-02 10:00
21 時間
Online
¥ 683316 ~ (オンライン)

Explainable AI (XAI) for Ethical AI Development

2025-06-16 10:00
14 時間
Online
¥ 455544 ~ (オンライン)

Introduction to Explainable AI (XAI) for Beginners

2025-06-30 10:00
14 時間
Online
¥ 455544 ~ (オンライン)

Introduction to Explainable AI (XAI) for Beginners

2025-07-14 10:00
14 時間
Online
¥ 455544 ~ (オンライン)

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