Every AI model carries ethical risk, every blockchain carries an attack surface, and every customer record carries a privacy obligation. This Specialization builds AI ethics, blockchain security, and data privacy skills together: apply machine learning algorithms like XGBoost and CNNs alongside causal models and transformer-based NLP, run STRIDE threat modeling to harden smart contracts and wallets against real-world crypto attacks, and build a privacy program spanning data inventories, consent, and secure destruction. You'll leave equipped to design AI systems, blockchain architectures, and data programs that are technically sound, secure, and genuinely trustworthy.
Applied Learning Project
Through hands-on projects, you'll train XGBoost and CNN models for regression and classification, build a causal model with Bayesian networks and DoWhy, apply STRIDE threat modeling to a blockchain data flow diagram, audit a smart contract for vulnerabilities, and draft a privacy risk assessment and breach response plan, applying these skills to authentic security, ethics, and compliance scenarios.
