Introduction to core data science concepts and skills, including computing environments, visualization, modeling, and bias analysis. Think like a Data Scientist as you engage through lectures, discussions, labs, and guest …
Train your own LLM for a custom task. Learn about the LLM lifecycle from architecture, to pre-training, to supervised finetuning, to deployment, to model editing/updating, including discussing LLM limitations. End …
Students will learn the fundamentals of product management. Topics include identifying unmet needs, understanding markets, implementing product development frameworks and processes, building businesses, and working with multi-functional teams. The application …
Fundamentals of data mining and machine learning within a common statistical framework. Topics include boosting, ensembles, Support Vector Machines, model-based clustering, forecasting, neural networks, recommender systems, market basket analysis, and …
Comprehensive introduction to predictive modeling, a cornerstone of data science and machine learning. Learn the fundamental concepts, techniques, and tools used to build models while emphasizing both theoretical understanding and …
Students will develop a detailed understanding of the legal aspects of public employment law, and the short and long-term impact of recruiting and retaining talented employees. Emphasis will be placed …
This course will center on exposing students to contemporary pipelines for data analysis through a series of steadily escalating use cases. The course will begin with simple local database construction …
The course explores government contracting, how the government procures products and services, and opportunities created through government regulation. Pre-requisite: STS 1500 or ENGR 1020 or ENGR 2595-Engineering Foundations II.
This course exposes students to foundational knowledge in each of the four high level domain areas of data science (Value, Design, Analytics, Systems). This includes an emphasis on ethical issues …
The data science project course will allow students to take the knowledge gained in each of the four required courses and apply them to a data driven problem. Students will …