{"id":23525922,"url":"https://github.com/hughparsonage/ccds","last_synced_at":"2026-02-27T17:47:08.806Z","repository":{"id":81368211,"uuid":"73159999","full_name":"HughParsonage/CCDS","owner":"HughParsonage","description":"For the collective campus data science course","archived":false,"fork":false,"pushed_at":"2017-01-20T02:58:44.000Z","size":10713,"stargazers_count":0,"open_issues_count":7,"forks_count":0,"subscribers_count":4,"default_branch":"master","last_synced_at":"2025-11-07T05:02:50.830Z","etag":null,"topics":[],"latest_commit_sha":null,"homepage":null,"language":"HTML","has_issues":true,"has_wiki":null,"has_pages":null,"mirror_url":null,"source_name":null,"license":null,"status":null,"scm":"git","pull_requests_enabled":true,"icon_url":"https://github.com/HughParsonage.png","metadata":{"files":{"readme":"README.md","changelog":null,"contributing":null,"funding":null,"license":null,"code_of_conduct":null,"threat_model":null,"audit":null,"citation":null,"codeowners":null,"security":null,"support":null,"governance":null,"roadmap":null,"authors":null,"dei":null,"publiccode":null,"codemeta":null}},"created_at":"2016-11-08T07:20:47.000Z","updated_at":"2019-10-01T10:16:15.000Z","dependencies_parsed_at":"2023-03-13T20:08:58.821Z","dependency_job_id":null,"html_url":"https://github.com/HughParsonage/CCDS","commit_stats":null,"previous_names":[],"tags_count":0,"template":false,"template_full_name":null,"purl":"pkg:github/HughParsonage/CCDS","repository_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/HughParsonage%2FCCDS","tags_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/HughParsonage%2FCCDS/tags","releases_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/HughParsonage%2FCCDS/releases","manifests_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/HughParsonage%2FCCDS/manifests","owner_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/owners/HughParsonage","download_url":"https://codeload.github.com/HughParsonage/CCDS/tar.gz/refs/heads/master","sbom_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/HughParsonage%2FCCDS/sbom","scorecard":null,"host":{"name":"GitHub","url":"https://github.com","kind":"github","repositories_count":286080680,"owners_count":29907021,"icon_url":"https://github.com/github.png","version":null,"created_at":"2022-05-30T11:31:42.601Z","updated_at":"2026-02-27T17:28:36.873Z","status":"ssl_error","status_checked_at":"2026-02-27T17:28:20.970Z","response_time":57,"last_error":"SSL_read: unexpected eof while reading","robots_txt_status":"success","robots_txt_updated_at":"2025-07-24T06:49:26.215Z","robots_txt_url":"https://github.com/robots.txt","online":false,"can_crawl_api":true,"host_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub","repositories_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories","repository_names_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repository_names","owners_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/owners"}},"keywords":[],"created_at":"2024-12-25T19:13:13.682Z","updated_at":"2026-02-27T17:47:08.761Z","avatar_url":"https://github.com/HughParsonage.png","language":"HTML","funding_links":[],"categories":[],"sub_categories":[],"readme":"# CCDS\nFor the collective campus data science course.\n\n## Week One: Data Munging\n\nIntroduction to R\nReading in data from csv files\nIntroduction to databases\nExtracting data from databases\nMerging data tables\nTidy data\nWriting functions\nThe split-apply-combine strategy using dplyr\nGenerating summary statistics for arbitrary sub-groups\nWriting data to files \u0026 databases\n\n## Week Two: Prediction\n\nIntroduction to predictive modelling\nStructural modelling vs machine learning\nPredicting different data types\nBuilding a predictive model using linear regression\nUnder the hood: maximum likelihood\nFeature selection \u0026 prediction using regularised GLMs\nA brief introduction to Bayesian modelling\nClassification and regression trees\nBoosted trees and Random Forests\n\n## Week Three: Causality\n\nWhat is causality, and why won’t predictive models help me?\nData generating processes and observational equivalence\nUnobserved data and simultaneity\nThe experimental ideal\nNatural experiments as a way of thinking about the world\nInstrumental variables\nOther techniques (Difference-in-differences, regression discontinuity)\nMatching routines\n\n## Week Four: Visualisation\n\nIntroduction to ggplot2\nAesthetics – x, y, size, weight, group, colour, fill, etc.\nChart types\nData exploration using faceting and grouping\nCustomising chart appearance\nPublishing work using Rmd and Rpres\nCelebratory breakup drinks (!)\n","project_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fhughparsonage%2Fccds","html_url":"https://awesome.ecosyste.ms/projects/github.com%2Fhughparsonage%2Fccds","lists_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fhughparsonage%2Fccds/lists"}