The goals and learning outcomes of the Data Science program at St. Bonaventure University:

Goal 1. Students will be able to compare methods for responsibly extracting knowledge from various forms of data.
    a) Students will be able to discriminate between different types of data.
    b) Students will be able to name and classify different statistical and computational approaches for analyzing large datasets.
    c) Students will be able to explain the pros and cons of different approaches to knowledge extraction – particularly in terms of fairness, accountability, transparency, and ethics.

Goal 2. Students will be able to produce and clearly explain data-driven conclusions developed using their skills in programming, machine learning, statistics, and visualization.
    a) Students will be able to explain all the steps involved in completing a data science project.
    b) Students will be able to collect and clean data to prepare it for knowledge extraction.
    c) Students will be able to select and apply industry-standard methods and tools to produce data-driven conclusions using their skills in programming, machine learning, and statistics.
    d) Students will be able to explain how each tool works in theory to accurately  interpret output.
    e) Students will demonstrate proficiency in using data visualization tools and techniques to effectively communicate insights derived from data analysis.
    f) Students will apply their skills to real-world projects that aim to solve complex problems across various domains, while emphasizing fairness, accountability, transparency, and ethics.

Goal 3. Students will be able to survey and assess changes in this rapidly evolving field that quickly antiquates any fixed set of skills.
    a) Students will locate and reflect on recent data science projects and research.
    b) Students will formulate personal plans for ongoing research and learning.