9 courses with the subject SDT, each shown exactly as we captured it from the college's catalog, with every element we hold. Where the wording looks broken, that is our reading of the catalog, not the college's text.
SDT 100Intro Data Sci & Analytics with AI (Data Analytics)3
Credit(s) This course introduces students to fundamental data science concepts and their applications in business. Students will learn descriptive and inferential statistics using tools like Excel and Power BI, along with an introduction to AI tools. The focus is on understanding how to analyze and interpret data to make informed business decisions, with practical applications that do not require deep technical knowledge.
Credit(s) A problem- and project-driven course that considers the implications of data and marketing recommendations from data. Data clearing. misrepresentation of data, data mining, and other assorted topics are incorporated in the curriculum. This course prepares students for an internship.
Credit(s) Designed to develop students’ understanding of the methods and algorithms of data analytics and how to answer questions about real-world problems. The course is project-based and includes topics as clustering, classification, and network analysis.
SCS 250 and SDT 200 or permission of instructor. Writing Intensive Course.
SDT 300Capstone (Data Analytics)4
Credit(s) This is a capstone seminar for the Data Analytics major. Students work collaboratively on cumulative research projects based on all of their previously learned techniques and internship experiences. Emphasis is on producing research reports and collective problem solving.
SDT 500Leveraging Business Analytics & AI (Data Analytics)3
Credit(s) This course focuses on analyzing data with statistics, supervised learning, and artificial intelligence (AI), including clustering and neural networks, and designing visualizations for business decisions. Topics include Hypothesis testing, confidence intervals, distributions, regression, correlations, and AI-driven predictions using current technology and software.
Credit(s) This course prepares students to use statistical techniques to analyze data and design decision-making models, incorporating artificial intelligence (AI). Topics covered include linear regression, multiple regression, time series and models, forecasting, ANOVA calculations, factor analysis, heteroskedasticity, kurtosis, and financial modelling. Students will apply these concepts to multiple business domains including retail, supply chain, HR, finance, and more.
Credit(s) This course will cover data mining techniques and topics used for collecting large amounts of data and detecting patterns to predict possible outcomes to business scenarios using artificial intelligence (AI). Basic machine-learning concepts including clustering, entropy, dimensionality, Bayes Theorem, text analysis, and classification will be discussed. The applications and usage of Big Data in real-world scenarios will be detailed at length.
SDT 503Bus Intell & Data Visualization (Data Analytics)3
Credit(s) This course will cover business intelligence, data visualizations, and unique data models to aid in both basic and complex business data-driven decisions, enhanced by artificial intelligence (AI). Unique and complex variables will be incorporated into designs. Students will design visualizations and dashboards to represent real-world scenarios and convey complex data scenarios at all levels of an organization to improve both operational and executive data interpretation.
