Covers foundations and applications of NLP with a focus on the most popular form of unstructured data - text. Convert source texts into structure-preserving analytical form and then apply information theory, NLP tools, and vector-based methods to explore language models, topic models, sentiment analyses, and GenAI techniques. Focus is on unsupervised methods to explore cognitive patterns in texts, with real-world examples and demonstrations.

Provides healthcare domain knowledge, healthcare data understanding, and data science methodologies to solve problems. Understand data types, models, and sources, including electronic health record data; health outcomes, quality, risk, and safety data; and unstructured data, such as clinical text data; biomedical sensor data; and biomedical image data. Querying with SQL, data visualization with Tableau, and analysis and prediction with Python.

Provides a foundation in discrete mathematics, data structures, algorithmic design and implementation, computational complexity, parallel computing, and data integrity and consistency. Case studies and exercises will be drawn from real-world examples (e.g., bioinformatics, public health, marketing, and security).

Provides an in-depth exploration of probabilistic and statistical methods used to understand, quantify, and manage uncertainty. Learn foundational concepts in probability and statistics, simulation techniques, and modern approaches to parameter estimation, decision theory, and hypothesis testing. Topics include parametric and nonparametric methods, Bayesian and frequentist paradigms, and applications of uncertainty in real-world problems. 

Genomics Foundations introduces core concepts in modern genomics and human genetics underlying computational biology and public health genomics. The course integrates key biological principles with quantitative reasoning and hands-on use of real genomics data and databases.

Trends in hardware and software for Big Data Systems and applications. Cover principles driving data infrastructures, which enabled the training of AI models on datasets (speech, sounds, images, video, languages) and may extend to structured data (text, images, time series). AI and machine learning practitioners build and deploy data science projects on Amazon Web Services unifying data science, data engineering, and application development.

This course examines environmental policy using economic analysis. The first half introduces core environmental economics concepts, including microeconomic review, market failures, and cost-benefit tools for evaluating policy and pollution levels, along with common policy solutions. The second half explores real-world challenges in policy implementation, such as unintended incentives, economy-wide effects, and strategic interactions between regulators and polluters.

This course focuses on making students more effective at identifying and designing AI use cases to create novel AI-powered products and services. Students will work with a variety of AI technologies across several projects. They will gain a deep understanding of design considerations for incorporating AI into products in ways that create value for users and businesses.

Research origins of gun violence in American society, in conjunction with engaging with various stakeholders to propose sensible solutions to this problem. Assigned to Baltimore, Richmond, or Washington, DC & will participate in a visit to their locale to gain insights from politicians, policymakers, public safety professionals, & members of the public on the policies & programs that have been implemented to mitigate the prob. of gun violence.

What does it mean to prioritize equity in policy? Equity must be operationalized & incorporated into all policy stages: agenda setting, design, implementation, & evaluation. Consider frameworks & tools for centering equity in policy design: engage disadvantaged communities; evaluate degree current policies promote equity, examine policy histories & differential impacts; surface apparent tradeoffs in elevating equity over other analytic concerns.