{"id":18494279,"url":"https://github.com/amitkaps/art-data-science","last_synced_at":"2026-03-15T06:50:08.970Z","repository":{"id":39787823,"uuid":"79078847","full_name":"amitkaps/art-data-science","owner":"amitkaps","description":"The Art of Data Science","archived":false,"fork":false,"pushed_at":"2019-06-18T02:48:47.000Z","size":54147,"stargazers_count":36,"open_issues_count":0,"forks_count":29,"subscribers_count":5,"default_branch":"master","last_synced_at":"2025-08-24T20:41:33.303Z","etag":null,"topics":["data-analysis","data-science","data-visualisation","problem-solving","workshop-materials"],"latest_commit_sha":null,"homepage":null,"language":"HTML","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/amitkaps.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}},"created_at":"2017-01-16T03:20:49.000Z","updated_at":"2025-06-17T08:01:30.000Z","dependencies_parsed_at":"2022-09-14T21:00:46.102Z","dependency_job_id":null,"html_url":"https://github.com/amitkaps/art-data-science","commit_stats":null,"previous_names":[],"tags_count":0,"template":false,"template_full_name":null,"purl":"pkg:github/amitkaps/art-data-science","repository_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/amitkaps%2Fart-data-science","tags_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/amitkaps%2Fart-data-science/tags","releases_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/amitkaps%2Fart-data-science/releases","manifests_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/amitkaps%2Fart-data-science/manifests","owner_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/owners/amitkaps","download_url":"https://codeload.github.com/amitkaps/art-data-science/tar.gz/refs/heads/master","sbom_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/amitkaps%2Fart-data-science/sbom","scorecard":null,"host":{"name":"GitHub","url":"https://github.com","kind":"github","repositories_count":286080680,"owners_count":30537108,"icon_url":"https://github.com/github.png","version":null,"created_at":"2022-05-30T11:31:42.601Z","updated_at":"2026-03-15T05:01:24.307Z","status":"ssl_error","status_checked_at":"2026-03-15T04:58:50.392Z","response_time":61,"last_error":"SSL_connect returned=1 errno=0 peeraddr=140.82.121.6:443 state=error: 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":["data-analysis","data-science","data-visualisation","problem-solving","workshop-materials"],"created_at":"2024-11-06T13:18:57.418Z","updated_at":"2026-03-15T06:50:08.951Z","avatar_url":"https://github.com/amitkaps.png","language":"HTML","funding_links":[],"categories":[],"sub_categories":[],"readme":"# The Art of Data Science\n\n- [Curriculum](curriculum.md) - The scope of the workshop.\n- [Installation](/installation) - To get yourself ready for the workshop.\n- [Pre-requisites](pre-requisites.md) - To get yourself ready for the workshop.\n- [Schedule](schedule.md) - The broad schedule for the workshop\n- [Overview](overview.md) - The overview presentation for the workshop.\n- [Intro to Art of Data Science](/notebook/Intro-Art-of-Data-Science.ipynb) - The overall introduction to the workshop.\n- [Intro to Data Structures in Python](/notebook/Intro-Python.ipynb) - Get started with Python.\n- [Intro to Data Structures in R](/notebook/intro-to-r.ipynb) - Get started with R.\n- [Intro to Visualisation in R](/notebook/intro-viz.ipynb) - Visualisation with R.\n\nCase Studies\n- [Case #1 - Peeling the Onion](/notebook/onion) - Price \u0026 Quantity of Onion across in India.\n    - Frame the Problem - [Python](/notebook/onion/1-Frame.ipynb) or  [R](/notebook/onion/1-Frame-R.ipynb)\n    - Acquire the Data - [Python](/notebook/onion/2-Acquire.ipynb) or [R](/notebook/onion/2-Acquire.ipynb)\n    - Refine the Data - [Python](/notebook/onion/3-Refine.ipynb) or [R](/onion/3-Refine-R.ipynb)\n    - Transform the Data - [Python](/notebook/onion/4-Transform.ipynb) or [R](/onion/3-Refine-R.ipynb)\n    - Explore the Data - [Python](/notebook/onion/5-Explore.ipynb) or [R](/onion/5-Explore-R.ipynb)\n    - Model the Solution - [Python](/notebook/onion/6-Model.ipynb) or [R](/onion/6-Model-R.ipynb)\n    - Insight Communication - [Python](/notebook/onion/7-Insight.ipynb) or  [R](/onion/7-Insight-R.ipynb)\n- [Case #2 - Kitna Deti Hain - Cars](/cars/Movies.ipynb) - Finding the star pairing in popular movies.\n- [Case #3 - Stars in Movies](/movies/Movies.ipynb) - Finding the star pairing in popular movies.\n- [Case #4 - Shining Diamonds](/diamonds/Diamonds.ipynb) - Price of Diamonds based on 4Cs (Carat, Colour, Cut and Clarity)\n- [Case #5 - Wine Selection](/wine/Wine.ipynb) - Selecting a good Red Wine to drink\n\n[Practice Exercises](/exercise.md)\n","project_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Famitkaps%2Fart-data-science","html_url":"https://awesome.ecosyste.ms/projects/github.com%2Famitkaps%2Fart-data-science","lists_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Famitkaps%2Fart-data-science/lists"}