Data Science (DS) Courses
DS 1001. Data Science and AI for All. (1-0) 1 Credit Hour.
The course is designed for students from all academic backgrounds to develop interests in data science and artificial intelligence. Introduction to the concept of analyzing data culled from a variety of sources, and understanding the methods of aggregating data, forming coherent queries, and building machine learning models to derive insights from data. Topics may include Python programming using Jupyter Notebook, R programming, text analysis, database, data analytics, and data visualization. (Same as DDTI 1001. Credit cannot be earned for both DDTI 1001 and DS 1001.). Course Fee: LRDS $12.50.
DS 3023. Statistical Analysis for Data Science. (3-0) 3 Credit Hours.
Prerequisite: MAT 1073 or the equivalent. Introduction to the scientific method; principles of sampling and experimentation; scales of measurement; exploratory data analysis; basic probability; models for discrete and continuous data; simple simulations and inferences based on resampling; fundamentals of hypothesis testing and confidence intervals; analysis of variance and linear regression model; tensors and matrices. The course will emphasize data analysis and interpretation and effective communication of results through reports or presentations within data science contexts. (Same as DDTI 3023. Credit cannot be earned for both DDTI 3023 and DS 3023.). Course Fee: LRDS $37.50.
DS 4003. Introduction to Data Science. (3-0) 3 Credit Hours.
Prerequisite: MAT 1073 or the equivalent; students may not enroll without 30 credit hours completed. An introduction to foundational data science knowledge and life cycle. Focus areas on data visualization, data curation, ethics, and tools available for analysis will be covered. (Same as DDTI 4003. Credit cannot be earned for both DDTI 4003 and DS 4003.). Course Fee: LRDS $37.50; DL01 $75.
DS 4013. Programming for Data Science. (3-0) 3 Credit Hours.
Prerequisite: MAT 1073 or the equivalent.
An introduction to data-driven programming emphasizing problem solving and critical thinking. Topics will focus on foundational computer programming concepts and skills. (Same as DDTI 4013. Credit cannot be earned for both DDTI 4013 and DS 4013.). Course Fees: LRDS $37.50; DL01 $75.
DS 4023. Data Organization and Visualization. (3-0) 3 Credit Hours.
Prerequisites: DS 3023, DS 4003, and DS 4013 or the equivalents.
This course focuses on programming concepts, file input/output, and recursion that are involved in integrating, loading, processing, and transforming data from external sources for exploratory data analysis and visualization using data science software packages and APIs. (Same as DDTI 4023. Credit cannot be earned for both DDTI 4023 and DS 4023.). Course Fees: LRDS $37.50; DL01 $75.
DS 4033. Data Mining and Machine Learning. (3-0) 3 Credit Hours.
Prerequisites: Completion of or concurrent enrollment in DS 4023.
This course utilizes fundamental data science concepts to introduce in-depth analysis, data mining, machine learning, and artificial intelligence. Topics may include clustering, classification, evaluation metrics, supervised and unsupervised learning, search algorithms, intelligent agents, and AI applications in select areas. (Same as DDTI 4033. Credit cannot be earned for both DDTI 4033 and DS 4033.). Course fee: DL01 $75; LRDS $37.50.
DS 4043. Generative Artificial Intelligence. (3-0) 3 Credit Hours.
Prerequisite: DS 4033 or instructor consent. This course covers the transformer architecture and fundamental topics such as tokenization,
context windows, embeddings, etc. Students will learn to use various APIs, host language models locally, and explore the trade-offs between various state-of-the-art open-source models. Coursework will touch upon fine-tuning, prompt engineering, mitigating hallucinations, and alignment. (Same as DDTI 4043. Credit cannot be earned for both DDTI 4043 and DS 4043.). Course Fee: DL01 $75.
