{"id":16722240,"url":"https://github.com/cpfiffer/julia-bootcamp-2022","last_synced_at":"2025-04-05T12:07:46.561Z","repository":{"id":41268100,"uuid":"444155963","full_name":"cpfiffer/julia-bootcamp-2022","owner":"cpfiffer","description":null,"archived":false,"fork":false,"pushed_at":"2023-08-22T16:10:47.000Z","size":6216,"stargazers_count":480,"open_issues_count":0,"forks_count":80,"subscribers_count":28,"default_branch":"main","last_synced_at":"2025-03-28T19:04:50.729Z","etag":null,"topics":["autodiff","bayesian-statistics","econometrics","julia","numerical-optimization","statistics"],"latest_commit_sha":null,"homepage":"","language":"Jupyter Notebook","has_issues":true,"has_wiki":null,"has_pages":null,"mirror_url":null,"source_name":null,"license":"mit","status":null,"scm":"git","pull_requests_enabled":true,"icon_url":"https://github.com/cpfiffer.png","metadata":{"files":{"readme":"README.md","changelog":null,"contributing":null,"funding":null,"license":"LICENSE","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":"2022-01-03T18:08:05.000Z","updated_at":"2025-03-22T08:13:45.000Z","dependencies_parsed_at":"2024-10-26T21:11:11.829Z","dependency_job_id":"1eea16cf-20b6-4654-a4d6-7b7be1316f88","html_url":"https://github.com/cpfiffer/julia-bootcamp-2022","commit_stats":null,"previous_names":[],"tags_count":0,"template":false,"template_full_name":null,"repository_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/cpfiffer%2Fjulia-bootcamp-2022","tags_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/cpfiffer%2Fjulia-bootcamp-2022/tags","releases_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/cpfiffer%2Fjulia-bootcamp-2022/releases","manifests_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/cpfiffer%2Fjulia-bootcamp-2022/manifests","owner_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/owners/cpfiffer","download_url":"https://codeload.github.com/cpfiffer/julia-bootcamp-2022/tar.gz/refs/heads/main","host":{"name":"GitHub","url":"https://github.com","kind":"github","repositories_count":247332609,"owners_count":20921853,"icon_url":"https://github.com/github.png","version":null,"created_at":"2022-05-30T11:31:42.601Z","updated_at":"2022-07-04T15:15:14.044Z","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":["autodiff","bayesian-statistics","econometrics","julia","numerical-optimization","statistics"],"created_at":"2024-10-12T22:34:04.644Z","updated_at":"2025-04-05T12:07:46.537Z","avatar_url":"https://github.com/cpfiffer.png","language":"Jupyter Notebook","funding_links":[],"categories":[],"sub_categories":[],"readme":"# Julia for Economists Bootcamp, 2022\n\nI taught a series of instructional Julia sessions at Stanford's GSB. Each month's session was two to four hours of lectures, practical examples, and guided projects tailored towards economics research computing using Julia.\n\nEach month covers a different topic and can be attended in isolation, though the first session covers the basics of Julia and may be useful for more advanced sessions if you are not currently familiar with Julia.\n\n## Session 1: Julia basics\n\n- [Recording](https://youtu.be/BnTYMOOPEzw)\n- [Lecture notes](https://github.com/cpfiffer/julia-bootcamp-2022/blob/main/session-1/intro.ipynb)\n- [Example data](https://github.com/cpfiffer/julia-bootcamp-2022/blob/main/session-1/example.csv)\n- [Project solution](https://github.com/cpfiffer/julia-bootcamp-2022/blob/main/session-1/project.jl)\n\n## Session 2: Parallelization\n\n- [Recording](https://www.youtube.com/watch?v=trhsvOAH0YI)\n- [Lecture notes](https://github.com/cpfiffer/julia-bootcamp-2022/blob/main/session-2/parallelization-lecture.ipynb)\n\n## Session 3: Optimization and Automatic Differentiation\n\n- [Recording](https://www.youtube.com/watch?v=B5O3xBolDCc)\n- [Lecture notes](https://github.com/cpfiffer/julia-bootcamp-2022/blob/main/session-3/optimization-lecture.ipynb)\n\n## Session 4: High-performance Julia\n\n- [Recording](https://youtu.be/i35LlZWZl1g)\n- [Lecture notes](https://github.com/cpfiffer/julia-bootcamp-2022/blob/main/session-4/speed-lecture.ipynb)\n\n## Session 5: Computational Bayesian statistics\n\n- [Recording](https://youtu.be/lnbA_j2YwyA)\n- [Lecture notes](https://github.com/cpfiffer/julia-bootcamp-2022/blob/main/session-5/bayes-lecture.ipynb)\n","project_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fcpfiffer%2Fjulia-bootcamp-2022","html_url":"https://awesome.ecosyste.ms/projects/github.com%2Fcpfiffer%2Fjulia-bootcamp-2022","lists_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fcpfiffer%2Fjulia-bootcamp-2022/lists"}