CODE: W7129G
LENGTH: 0.5 day(s)
PRICE: Free
This course will give you an overview on the concept of AI privacy, which helps in building trust in AI, and explains how open source tools from IBM can help both assess the privacy risk of AI-based solutions, and help them adhere to any relevant privacy requirements. Learners will start off with an overview of the AI Privacy concept, and then do a deep dive into three IBM open source tool kits: AI Privacy Toolkit, Differential Privacy Library and Adversarial Robustness Toolbox which help assess and create machine learning models that preserve the privacy of their training data and comply with relevant data protection regulations.
In this course you will learn:
Analytics Leaders, Data Science Leaders, Practicing Data Scientists, Machine Learning Engineers, AI specialists. Anyone with an interest in AI Trust and Privacy having the prerequisite knowledge required.
Students should have a basic understanding of:
Setting up and setting the scene with IBM Watson Studio
Gathering and accessing data for the team with IBM Watson Studio
Prototyping with IBM Watson Studio Collaborative Notebooks