Join the Secure & Private AI online course by Udacity & explore how to extend PyTorch with various tool crucial in training AI models that maintain user privacy
With the need for accessing personal data increasing, it is essential for you to excel in protecting user privacy. While there are umpteen privacy use cases unsolved, in recent years, privacy-preserving technologies have developed. The Secure and Private AI certification course introduces you to three groundbreaking privacy-preserving technologies, including differential privacy, federated learning, and encrypted computation.
You will also master the usage of OpenMined's PySyft and deep learning tools such as PyTorch. These offer distributed and cryptographic technologies for safely training Artificial Intelligence (AI) based models on distributed private data. You can also participate in Facebook’s Secure and Private AI Scholarship Challenge. It will help you enrol in the Secure and Private AI training and win the Deep Learning or Computer Vision Nanodegree programme scholarship.
Secure and Private AI programme from Facebook is an advanced-level free course. It runs for nearly two months and provides rich learning content, interactive quizzes, a self-paced learning approach, and industry professionals’ mentorship. Besides, you will learn by doing exercises.
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Data scientists, start-ups, and enterprises utilising ML and Deep Learning to solve user problems and access user data while maintaining their privacy can opt for the Secure and Private AI programme.
Secure and Private AI online course is an advanced-level study. To get the most out of your learning experience, you must have beginner-level expertise in Machine Learning, Deep Learning, any one of the Deep Learning frameworks (like PyTorch), and Python.
However, no academic or professional background in advanced mathematics or cryptography is required.
As you complete the Secure and Private AI syllabus, you will learn:
Step 1 – Go to access the Secure and Private AI official course page.
Step 2 – Now press on ‘START FREE COURSE’. It will lead you to a signup page.
Step 3 – Here, sign up/sign in using your Facebook or Google ID. Or provide your first & last name, password, and email address to create an Udacity profile. You can log in with your existing Udacity credentials as well. If you have an organisation email address, proceed to sign in with that by clicking on ‘Sign in with your organisation’. This concludes your enrollment.
Secure and Private AI online programmes have no application form. A Udacity signup page requests your name (first and last), email ID, and password for signing up. Signing in requires your Udacity credentials- an email ID and password.
Over the past few years, private data usage has increased significantly, posing a challenge for data scientists and enterprises to protect and maintain users' privacy. The Secure and Private AI course will equip you with expertise in privacy-preserving technologies of differential privacy, federated learning, and encrypted computation. Your skills will enable you to create smarter and socially responsible AI models.
Mr Andrew Trask Research Scientist Freelancer
Ph.D
The curriculum focuses on differential privacy, federated learning, and encrypted computation.
You must possess beginner-level expertise in Python, Machine Learning, Deep Learning, and any Deep Learning framework like PyTorch.
The Secure and Private AI course doesn’t require prior know-how in advanced mathematics and cryptography.
The course takes roughly two months to complete. It follows a self-paced training approach.
Brochure has been downloaded.
