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Clemson, South Carolina, United States
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Data Visualization Project
MBA 8080
This experience is designed for graduate-level students in a Data Visualization course at Clemson University. By the time they begin the project, students will have completed 12 weeks of a 16-week course focused on applied data storytelling using Tableau. Students will bring the following capabilities: Intermediate-level Tableau skills (including dashboards and stories) Intermediate understanding of data visualization principles and best practices Basic data cleansing and preparation skills (primarily using Tableau Prep) Introductory knowledge of how people interpret visual information Intermediate storytelling skills for business audiences All visualizations will be created using Tableau , and the final project will take the form of a narrated data story presentation designed to communicate insights clearly and persuasively.
Capstone Data Science Project
DSA 8670
The learners in this experience are completing their final semester in a Masters of Science in Data Science and Analytics. Their technical skills include: Data Acquisition, Wrangling, and Cleansing Statistisical Analysis including Supervised and Unsupervised models such as regression, monte carlo, and cluster analysis. Machine Learning Python & R Programming SQL Database and NoSQL They are capable of completing a project - from scratch - that includes processing and cleansing data, identifying and applying the appropriate analysis techniques, and delivering and communicating resutls.
End of Course Data Visualization Project
MBA 8080
These learners are MBA students who will have completed 12 weeks of a 16-week course on data visualization. They will have knowledge and skills including: Intermediate-level Tableau skill. Intermediate-level understanding of data visualization best practices. Beginner-level data cleansing skills. Basic understanding of human visual and cognitive processing. Intermediate-level skill in data storytelling.
Capstone Data Science Project
DSA 8670
The learners in this experience are completing their final semester in a Masters of Science in Data Science and Analytics. Their technical skills include: Data Acquisition, Wrangling, and Cleansing Statistisical Analysis including Supervised and Unsupervised models such as regression, monte carlo, and cluster analysis. Machine Learning Python & R Programming SQL Database and NoSQL They are capable of completing a project - from scratch - that includes processing and cleansing data, identifying and applying the appropriate analysis techniques, and delivering and communicating resutls.