TRUSTWORTHY ARTIFICIAL INTELLIGENCE

Name: TRUSTWORTHY ARTIFICIAL INTELLIGENCE
Availability: OutOfStock

COMPSCI/ECE 763

과목 설명

Explore security and privacy aspects of trustworthy artificial intelligence. Three core subjects will be considered: differential privacy and algorithmic fairness; adversarial machine learning; and end-to-end trustworthy systems. A selection of more advanced topics may be covered such as additional notions of privacy, language-based security, and robust optimization. Knowledge of probability/statistics (such as MATH 431), cryptography (such as MATH 435), security (such asCOMP SCI 642), and modern machine learning (such asM E/COMP SCI/E C E 539or540) is required.

선수과목

Graduate/professional standing

충족 요건

This course does not satisfy any prerequisites.

학점

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개설 시기

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평점

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변화 계산 불가

수료율

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변화 계산 불가

A 비율

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변화 계산 불가

학급 규모

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과거 데이터 대비 변화 없음

데이터 없음

강사 (2026 Summr)

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유사 과목

INTRODUCTORY ARTIFICIAL INTELLIGENCE (AI) AND DATA ETHICS

PHILOS 244

Introduction to contemporary moral and political issues in Artificial Intelligence (AI) and Data Ethics, integrating urgent problems, controversies, and continuously updated case studies. Introduces basic technical concepts such as the bias/variance tradeoff, the reference class problem, and inductive risk. Covers topics such as data and privacy, the impacts of automation on society, and the use of algorithms in medicine and criminal law.

INTRODUCTION TO CRYPTOGRAPHY

COMPSCI/ECE/MATH 435

Cryptography is the art and science of transmitting digital information in a secure manner. Provides an introduction to its technical aspects.

GENERATIVE ARTIFICIAL INTELLIGENCE: STRATEGIC APPLICATION, EVALUATION, AND CRITIQUE

LIS 408

Introductory exploration of generative artificial intelligence (AI) from a strategic information studies perspective, such as emphasizing values of privacy, data stewardship, and UX. Topics include societal, legal, policy, and ethical issues related to generative AI, and practicing the ability to evaluate, plan for, and securely work with these digital technologies. Focus on the strategies, skills and self-sufficiency necessary to evaluate, implement, and critique various and evolving AI tools.

ADVANCED COMPUTER SECURITY AND PRIVACY

COMPSCI/ECE 782

Security and privacy issues in software, networks, and hardware systems. Security vulnerabilities, privacy threats, threats modeling, and mitigation strategies. Privacy issues related to user interaction with devices, online systems, and networks. In addition, a selection of more advanced topics will be covered. Possible examples include applied cryptography in the context of systems, security and privacy policies, user authentication, and cyber-physical systems. Builds on prior experiences with one or more of the following: networking, security, modern machine learning, embedded systems, and mobile computing.

GENERATIVE ARTIFICIAL INTELLIGENCE FOR ENGINEERING APPLICATIONS

EPD 522

Comprehensive coverage of AI-powered chatbots, from understanding generative AI fundamentals to developing sophisticated chatbot applications. Hands-on experience with generative AI tools. Explore retrieval-augmented generation (RAG) techniques. Examine critical aspects such as security, privacy, and memory models. Knowledge of Python [such asCOMP SCI 220orE P D 455] strongly recommended.