Application to Add Data Science Elective Course

Eligible elective courses should have as their main theme a minimum of two components of the data science pipeline and incorporate a minimum of three of the stated learning objectives for the data science minor. To add a course as an elective for the Data Science Minor, complete and submit the form below. See below for additional information about the Data Science pipeline and learning objectives.

Data Science Pipeline

Students in the Minor in Data Science Program will be introduced to the “Data Science Pipeline”, which consists of the following five phases:

• Data Collection – Applying automated, manual, and hybrid approaches to elicit, sense, simulate or otherwise capture data.
• Data Cleaning – Transforming raw, noisy, incomplete, or otherwise dirty data into forms that can support further analysis.
• Exploratory Analysis – Using visualization, statistics, and other techniques to examine new data and identify possible opportunities for analysis.
• Statistical & Computational Analysis – Applying computational, mathematical, or statistical techniques and models to make sense of and extract knowledge from data.
• Presentation – Using visual, oral, and written approaches to communicate analysis processes, observations, and results.

Data Science Learning Objectives

1. Employ methods to collect, store, and retrieve data in various formats.
2. Explore data with visualization and analysis tools to build understanding and gain insights.
3. Formulate new research questions and identify appropriate analysis techniques when confronted with new data or challenges
4. Apply appropriate computational, mathematical, or statistical techniques and models to address data-driven inquiries.
5. Write an efficient and well-documented code to further enhance the data analytics process.
6. Clearly communicate concepts, analytic findings, and results in both written and oral form to a diverse audience.
7. Effectively and respectfully function within a collaborative working environment.
8. Consider ethics and privacy issues related to data collection, use, and presentation.