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Responsible AI for Developers: Privacy & Safety
Google via Google Cloud Skills Boost
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Overview
"Responsible AI for Developers: Privacy & Safety" is a focused course designed for software developers, machine learning engineers, and data professionals who build and deploy AI systems. This course provides essential guidance on embedding privacy, safety, and responsibility into AI development workflows from the ground up. Participants will learn core concepts of responsible AI, including differential privacy, data minimization, secure model training, and techniques for preventing data leakage. The course also explores AI safety challenges such as hallucinations, adversarial attacks, and...
Syllabus
- Course Introduction
- Course Introduction
- AI Privacy
- Overview of AI Privacy
- Privacy in Training Data: De-identification techniques
- Privacy in Training Data: Randomization techniques
- Privacy in Machine Learning Training: DP-SGD
- Privacy in Machine Learning Training: Federated Learning
- System Security on Google Cloud
- System Security on Gen AI
- Lab: Differential Privacy in Machine Learning with TensorFlow Privacy
- Differential Privacy in Machine Learning with TensorFlow Privacy
- Module 1: Quiz
- AI Safety
- Overview of AI Safety
- Safety Evaluation
- Harms Prevention
- Model Traing for Safety: Instruction Fine-tuning
- Model Traing for Safety: RLHF
- Safety in Google Cloud GenAI
- Lab: Safeguarding with Vertex AI Gemini API
- Safeguarding with Vertex AI Gemini API
- Module 2: Quiz
- Course Summary
- Course Summary
- Reading
- Course Resources
- Module 0: Course Introduction
- Module 1: AI Privacy
- Module 2: AI Safety
- Module 3: Course Summary
- Your Next Steps
- Course Badge
Instructor
Google Cloud
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