Explores machine learning security, including model stealing, altering outputs, adversarial conditions, and privacy challenges, emphasizing the importance of addressing biases in machine learning models.
Explores asymmetric cryptography basics, including encryption, signatures, and Diffie-Hellman, along with advanced topics like RSA and quantum computing implications.
