{"id":21887373,"url":"https://github.com/sskender/introduction-to-data-science","last_synced_at":"2026-05-19T06:31:49.146Z","repository":{"id":79364828,"uuid":"421503271","full_name":"sskender/introduction-to-data-science","owner":"sskender","description":"Introduction to Data Science FER","archived":false,"fork":false,"pushed_at":"2022-01-04T18:48:11.000Z","size":65027,"stargazers_count":0,"open_issues_count":0,"forks_count":0,"subscribers_count":4,"default_branch":"master","last_synced_at":"2025-01-26T20:26:23.181Z","etag":null,"topics":[],"latest_commit_sha":null,"homepage":null,"language":"Jupyter Notebook","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/sskender.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":"2021-10-26T16:32:42.000Z","updated_at":"2022-01-04T18:48:14.000Z","dependencies_parsed_at":null,"dependency_job_id":"578e5736-e464-41dd-b3e3-9c5c9d63cef3","html_url":"https://github.com/sskender/introduction-to-data-science","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/sskender%2Fintroduction-to-data-science","tags_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/sskender%2Fintroduction-to-data-science/tags","releases_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/sskender%2Fintroduction-to-data-science/releases","manifests_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/sskender%2Fintroduction-to-data-science/manifests","owner_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/owners/sskender","download_url":"https://codeload.github.com/sskender/introduction-to-data-science/tar.gz/refs/heads/master","host":{"name":"GitHub","url":"https://github.com","kind":"github","repositories_count":244894945,"owners_count":20527800,"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":[],"created_at":"2024-11-28T11:09:30.185Z","updated_at":"2026-05-19T06:31:44.115Z","avatar_url":"https://github.com/sskender.png","language":"Jupyter Notebook","funding_links":[],"categories":[],"sub_categories":[],"readme":"# Introduction to Data Science  \nIntroduction to Data Science FER\n\n- - - -\n\nLearning Outcomes:\n- Use Python and other tools to scrape, clean, and process data\n- Use data management techniques to store data locally and in cloud infrastructures\n- Use statistical methods and visualization to quickly explore data\n- Apply statistics and computational analysis to make predictions based on data\n- Describe the outcome of data analysis using descriptive statistics and visualizations\n- Use cluster and cloud infrastructure to perform data-intensive computation\n\n## Getting started\n\nInstall requirements:\n```bash\npython -m pip install -r requirements.txt\n```\n\nRun notebook:\n```bash\njupyter notebook\n```\n","project_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fsskender%2Fintroduction-to-data-science","html_url":"https://awesome.ecosyste.ms/projects/github.com%2Fsskender%2Fintroduction-to-data-science","lists_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fsskender%2Fintroduction-to-data-science/lists"}