Pearson – AI Security and Responsible AI Practices

Pearson – AI Security and Responsible AI Practices
English | Tutorial | Size: 1.28 GB

Ethical development and responsible deployment of AI and ML systems.

Learn the latest technology in AI and ML security to safeguard against AI attackers and ensure data integrity and user privacy.
Navigate privacy and ethical considerations to gain insights into responsible AI practices and address ethical consideration.
Explore emerging trends and future directions in AI, ML, security, ethics, and privacy focusing on key concepts including threats, vulnerabilities, and attack vectors.
Recognize and understand the privacy aspects of AI and ML, including data protection, anonymization, and regulatory compliance

Get the essential skills to protect your AI system against cyber attacks. Explore how generative AI and LLMs can be harnessed to secure your projects and organizations against AI cyber threats. Develop secure and ethical systems while being mindful of privacy concerns with real-life examples that we use on a daily-basis with ChatGPT, GitHub Co-pilot, DALL-E, Midjourney, DreamStudio (Stable Diffusion), and others. Gain a solid foundation in AI and ML principles and be better prepared to develop secure and ethical systems while being mindful of privacy concerns. Authors Omar Santos and Dr. Petar Radanliev are industry experts to guide and boost your AI security knowledge.

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