Learning Outcomes
Each class will touch on several of the following learning outcomes, with the entire program delivering competencies in all areas.
Numbers in parentheses refer to the St. John Fisher College College-wide learning goals to which each outcome is linked.
Real-World
- Identify important real-world problems, and have the ability to plan and execute data analysis to explore those problems. (1, 5, 6)
- Implement and evaluate the use of analytic models on sample and real-world data. (1, 5, 6)
Planning
- Apply behavioral research methods to data science problems, where appropriate. (1, 5, 6)
- Work collaboratively in teams. (1,2)
- Plan, carry out, and report on a real-world data science project. (6)
Implementation
- Explain the structure of databases, design and implement database systems, and have facility in accessing appropriate data from database systems. (1, 5)
- Work with multiple types of data, using appropriate tools. (1)
- Understand, develop, use, and evaluate machine-learning approaches to exploring and analyzing data. (1, 5, 6)
- Plan, carry out, and report on a real-world data science project. (6)
Communication
- Communicate the results of data analyses, both orally and in writing, using appropriate tools. (3)
- Use information for decision making, problem solving, and ongoing learning. (1, 3, 6)
- Explain regulatory and ethical issues surrounding the acquisition and use of data. (4)
Numbers in parentheses refer to the St. John Fisher College College-wide learning goals to which these outcomes are linked.