Date | Topic | Lab |
---|---|---|

Mon Sep 25 | cm001: Introduction to computing for the social sciences | |

Wed Sep 27 | cm002: Visualizations and the grammar of graphics | lab01: Software setup |

Mon Oct 2 | cm003: Data transformation | |

Wed Oct 4 | cm004: Exploratory data analysis | lab02: R basics |

Mon Oct 9 | cm005: Data wrangling: tidy data | |

Wed Oct 11 | cm006: Data wrangling: relational data and factors | lab03: Graphing tips for `ggplot2` (and life) |

Mon Oct 16 | cm007: Pipes and functions | |

Wed Oct 18 | cm008: Vectors and iteration | lab04: The shell |

Mon Oct 23 | cm009: Debugging and defensive programming | |

Wed Oct 25 | cm010: R Markdown | lab05: |

Mon Oct 30 | cm011: Statistical learning: basics and linear regression | |

Wed Nov 1 | cm012: Statistical learning: classification | lab06: |

Mon Nov 6 | cm013: Statistical learning: resampling methods | |

Wed Nov 8 | cm014: Distributed learning | lab07: AWS |

Mon Nov 13 | cm015: Getting data from the web: API access | |

Wed Nov 15 | cm016: Getting data from the web: scraping | lab08: |

Mon Nov 20 | cm017: Text analysis: fundamentals and sentiment analysis | |

Wed Nov 22 | cm018: Text analysis: classification and topic modeling | lab09: |

Mon Nov 27 | cm019: Interactivity in R | |

Wed Nov 29 | cm020: Shiny applications | lab10: |

- Homework 01: Edit README.md
- Homework 02: Exploring and visualizing data
- Homework 03: Wrangling and visualizing data
- Homework 04: Programming in R
- Homework 05: Generating reproducible research
- Homework 06: Statistical learning
- Homework 07: Resampling methods and distributed learning
- Homework 08: Collecting and analyzing data from the web
- Homework 09: Analyzing text data
- Homework 10: Build a Shiny application

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