Foundations of AI Privacy and Blockchain

Most AI practitioners can run a model. Fewer can select the right one for the problem at hand, trace the causal story behind their data, and design systems that genuinely empower the people they affect. This course closes that gap, delivering the technical depth and ethical judgment that separate thoughtful AI expertise from surface-level familiarity. You'll classify machine learning types and apply XGBoost and CNNs to regression and classification tasks, running working Python code throughout. You'll build causal models using Bayesian networks and the DoWhy framework, integrate knowledge graphs for structured reasoning, and generate language and analyze sentiment with transformer models including GPT-2 and BERT. Then you'll program competitive AI agents using minimax algorithms and cooperative swarms with particle optimization before applying a rigorous ethics arc covering bias mitigation, privacy trade-offs, impossibility theorems, Value-Sensitive Design, and the Capability Approach. By the end of this course, you'll be able to select, build, and ethically evaluate AI systems across a range of real-world domains, equipped with both the technical skills and the principled design frameworks to ensure your work genuinely enhances human capability.

Data is one of the most valuable assets your organization holds, and it is also one of its greatest liabilities. Every customer record, employee file, and behavioral data point creates legal, ethical, and operational obligations, and the consequences of getting privacy wrong range from regulatory sanctions to permanent damage to the trust your customers place in you. In this course, you'll identify what counts as personal data across your organization, classify it by sensitivity, and map every third party that touches it. You'll assess data processing risks using a structured probability-and-impact framework, draft internal privacy policies and external notices that meet regulatory requirements, and build training programs that turn your workforce into active privacy advocates. You'll then apply privacy-by-design principles across the full data lifecycle, from obtaining consent and collecting data securely to archiving and destroying records responsibly when their usefulness ends. By the end of this course, you'll be equipped to design, implement, and maintain a comprehensive privacy program that protects your customers, your employees, and your organization's long-term reputation.