The primary goal of AC1 is to teach students data literacy: the ability to access, transform, use, and interpret data, ethically and effectively, to inform decision-making. This is a practical, hands-on course that will teach students to ask and answer questions about data through spreadsheets, SQL databases, and data visualization tools. The skills and problem solving mindset they learn will be highly applicable to any major or career.
This is an interdisciplinary course combining concepts from data science, computer science, and statistics. It is not a comprehensive introductory course in any of those fields. AC1 prepares students for more comprehensive courses on Python programming and data science in Python. Students who do not take more courses on the subject will still have a useful understanding of widely-used data science tools and techniques, which they can continue to use and build upon.
Daily learning objectives follow seven overarching themes in achieving data literacy.
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Data Transformation (DT): Understanding and proper usage of basic relational algebra operators (e.g. filter, aggregation, join).
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Ethics and Fairness (E): Identifying ethical considerations in the collection, analysis, and presentation of data (e.g. privacy, fairness, disclosure).
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Modeling (M): Intuitive understanding of statistical models and variance; practical ability to use core modeling techniques (e.g. linear and logistic regression).
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Problem Solving (PS): Solving large problems by breaking them into smaller pieces, anticipating results, and troubleshooting when results are not expected.
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Programming Readiness (PR): Ability to write and fix problems in formal language syntax; understanding of fundamental programming constructs (e.g. conditionals, functions).
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Storytelling (S): Posing research questions, using the correct data analysis, interpreting the results, and presenting the conclusions.
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Visualization (V): Choosing, creating, interpreting, and critiquing data visualizations.
Students will see these learning objectives in their textbook. To further help them make and retain connections across different units, you should make an effort to connect course concepts to these overarching themes whenever possible.