Presented by: Ava Meredith, Seattle Central College UC Berkeley’s Data 8 The Foundations of Data Science: Inferential Thinking, Computational Thinking, and Real-World Relevance Presented by: Ava Meredith, Seattle Central College

What is Data 8? Data 8 is a popular introductory Data Science class at UC Berkeley Designed to be accessible to a broad range of students without the typical prerequisites for a data science class Data 8's unique model: inferential thinking, computational thinking, and real-world relevance Focus on social issues in data analysis All materials for the course are available for free online under a CC license.

The Data 8 Teaching Philosophy Represents a shift from traditional teaching each of the individual concepts in a course. Introductory courses in statistics, computer science, writing, and ethics (among others) combined into a single introductory course.

Data 8 Goals Diversity Equity Pedagogical Clarity Scalability Depth No computational barrier to entry

Core Concepts Critical thinking Don't take your data for granted Use the combination of CS + Stats as a feature, not a bug Focus on hands on work Determine if your inference is sound Experiment Know the right statistical tools for the job

Learn about data limitations Quantify and understand uncertainty in data Turn your data analysis into a decision Think of ways that you could be wrong Consider edge-cases

Focus on main ideas (shield the students from non essential topics) Use the data science module rather than many package APIs Use JupyterHub (no need for students to setup environment)

Observation and Visualization

Abstract cleaning data by providing pre-collected/cleaned data Provide further resources Aim the course for anybody, not just statistics or CS majors.

Intersections of Topics Intersectionality is a feature, not a bug Connect CS and statistics concepts Use interactivity to let people explore

Topics covered Programming fundamentals Statistics, sampling, and hypothesis testing Inference, prediction, and models Comparing distributions

Connector courses Connector courses offer the ways in which data science is applied in a domain knowledge field

Tech Stack Managing course content - Jupyter notebooks Programming language - Python 3 Primary data object and functions - Use of data analytics packages in Python (Data 8 wraps several) Handling the Python environment - Python dev environment managed with miniconda

Next Steps View the course online http://data8.org/ Free online textbook: https://www.inferentialthinking.com/chapters/intro Data Science Academic Resource Kit: https://data.berkeley.edu/education/ark