1. 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

2. 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.

3. 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.

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

5. 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

6. 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

7. 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)

8. Observation and Visualization

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

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

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

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

13. 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

14. Next Steps View the course online http://data8.org/
Free online textbook:
Data Science Academic Resource Kit: