UC Berkeley: Foundations of Data Science — Spring 2016

 Data Science An overview of data science

• Wed Jan 20 1 Why Data Science? Lab 01

• Fri Jan 22 2 Cause and Effect Homework 01

 Tables Using Python to manipulate information

• Mon Jan 25 1 Expressions

• Wed Jan 27 2 Sequences Lab 02

• Fri Jan 29 3 Data Sets Homework 02

• Mon Feb 01 4 Tables

• Wed Feb 03 5 Functions Lab 03

• Fri Feb 05 6 Categories Homework 03

 Visualization Interpreting and exploring data through visualizations

• Mon Feb 08 1 Charts

• Wed Feb 10 2 Histograms Lab 04

 Sampling Understanding the behavior of random selection

• Fri Feb 12 1 Sampling Homework 04

• Wed Feb 17 2 Iteration Lab 05

• Fri Feb 19 3 Estimation and Means Homework 05

• Mon Feb 22 4 Variability

 Prediction Making predictions from data

• Wed Feb 24 1 Correlation Project 1

• Fri Feb 26 2 Explorations: Privacy

• Mon Feb 29 3 Regression

• Wed Mar 02 4 Prediction

• Fri Mar 04 5 Explorations: Design and Critique

• Mon Mar 07 6 Errors

• Wed Mar 09 7 Multiple Regression Lab 08

• Fri Mar 11 8 Classification Homework 06

• Mon Mar 14 9 Explorations: Machine Learning

• Wed Mar 16 10 Midterm Lab 09

• Fri Mar 18 11 Feature Selection

 Inference Reasoning about populations by computing over samples

• Mon Mar 28 1 Confidence Intervals Project 2

• Wed Mar 30 2 Percentiles Lab 10

• Fri Apr 01 3 Distance Between Distributions Homework 07

• Mon Apr 04 4 Hypothesis Testing

• Wed Apr 06 5 Hypothesis Testing II

• Fri Apr 08 6 Permutation Tests

• Mon Apr 11 7 Implementing Permutation Tests

• Wed Apr 13 8 A/B Testing Lab 12

• Fri Apr 15 9 Regression Inference Homework 08

• Mon Apr 18 10 Slope Inference Project 3

• Wed Apr 20 11 Regression Diagnostics Lab 13

 Probability Making assumptions and exploring their consequences

• Fri Apr 22 1 Probability

• Mon Apr 25 2 Conditional Probability

 Conclusion

• Wed Apr 27 1 Statistics Lab 14

• Fri Apr 29 2 Conclusion