{"id":13516095,"url":"https://github.com/kmonsoor/data-must-watch","last_synced_at":"2026-04-03T20:34:17.646Z","repository":{"id":49336031,"uuid":"44965966","full_name":"kmonsoor/data-must-watch","owner":"kmonsoor","description":"Must-watch videos on data-science","archived":false,"fork":false,"pushed_at":"2015-11-30T23:04:02.000Z","size":0,"stargazers_count":47,"open_issues_count":1,"forks_count":8,"subscribers_count":9,"default_branch":"master","last_synced_at":"2025-03-24T11:18:00.645Z","etag":null,"topics":[],"latest_commit_sha":null,"homepage":null,"language":null,"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/kmonsoor.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":"2015-10-26T12:08:09.000Z","updated_at":"2025-02-19T14:30:23.000Z","dependencies_parsed_at":"2022-09-16T00:40:43.023Z","dependency_job_id":null,"html_url":"https://github.com/kmonsoor/data-must-watch","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/kmonsoor%2Fdata-must-watch","tags_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/kmonsoor%2Fdata-must-watch/tags","releases_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/kmonsoor%2Fdata-must-watch/releases","manifests_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/kmonsoor%2Fdata-must-watch/manifests","owner_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/owners/kmonsoor","download_url":"https://codeload.github.com/kmonsoor/data-must-watch/tar.gz/refs/heads/master","host":{"name":"GitHub","url":"https://github.com","kind":"github","repositories_count":246423527,"owners_count":20774795,"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":"2024-08-01T05:01:19.060Z","updated_at":"2026-04-03T20:34:17.562Z","avatar_url":"https://github.com/kmonsoor.png","language":null,"funding_links":[],"categories":["Technical","Others","\u003ca id=\"Data\"\u003e\u003c/a\u003eData"],"sub_categories":["ramanihiteshc@gmail.com"],"readme":"# Must-watch videos on Data Science\n\nThis list tries to cover from basic introductory staffs to deep analytical staffs on industry-renowned tools.\n\nInspired by [py-must-watch](https://github.com/s16h/py-must-watch). \n\n### Contribution\nPlease create pull requests to suggest more awesome video links. However, please don't add too many in a single pull-request. :)\nPlease add your name in the file **contributors.md** file, if possible, in the same pull-request you make to add new video in the main list.\n\nThanks !\n\n------------------------------------------------------\n\n## Intro into Data-science\n* DJ Patil: **Data Science, how to be data driven and build great products** (BBVA Innovation Center, 2014)\n    * Video: [youtube](https://www.youtube.com/watch?v=54t7bSXniAs) [1:22:37]\n    * Comments: A great intro. Potrays Spock(Star Trek) as ship's data scientist.\n\n* Micheael Manoochehri: **Data Just Right: A Practical Introduction to Data Science Skills** (DataEDGE 2013)\n    * Video: [youtube](https://www.youtube.com/watch?v=rpwZ_i-9U0o) [1:24:50]\n    * Slides: [Google Docs](http://goo.gl/sCmF0)\n    * Comments: awesome intro\n\n* Ryan Orban: **How To Become A Data Scientist** (SF Data Science)\n    * Video: [youtube](https://www.youtube.com/watch?v=c52IOlnPw08) [59:07]\n    * Slides: [slideshare](http://www.slideshare.net/ryanorban/how-to-become-a-data-scientist)\n    * Comments: Audio is a bit hazy with background noise\n\n* Buck Woody: **Becoming a Data Professional: Taking It To The Next Level** (The DRIVE/conference 2013)\n    * Video: [youtube](https://www.youtube.com/watch?v=Zdh3p4EKLeQ) [57:05]\n    * Notes: [MSDN Blog](http://blogs.msdn.com/b/buckwoody/archive/2013/02/21/link-list-becoming-a-data-professional.aspx)\n    * Comments: \n\n\n## Machine Learning\n* Dr. Andrew Ng: **CS 229: Machine Learning** (Stanford Lecture series 2008)\n    * Video: [youtube](https://www.youtube.com/view_play_list?p=A89DCFA6ADACE599) (20 videos, 1+Hr each)\n    * Lecture materials: [Handouts](http://cs229.stanford.edu/materials.html), [course-home](http://cs229.stanford.edu/)\n* [Dr. Yaser S. Abu-Mostafa](https://work.caltech.edu/index.html): **Learning from Data** (from Caltech) \n    * Lecture materials: [Handouts/Videos/Homeworks](https://work.caltech.edu/telecourse.html)\n    * Comments: A self-paced advanced course on Machine Learning\n* Jake VanderPlas: Machine Learning with Scikit-Learn (I) (PyCon 2015)\n    * Video: [youtube](https://www.youtube.com/watch?v=L7R4HUQ-eQ0)[3:02:11]\n    * Lecture materials: [codes](https://github.com/jakevdp/sklearn_pycon2015), [IPython Notebook](http://nbviewer.ipython.org/github/jakevdp/sklearn_pycon2015/blob/master/notebooks/Index.ipynb)\n\n\n## Statistical Methods\n* Chris Fonnesbeck: **Statistical Thinking for Data Science** (SciPy 2015)\n    * Video: [youtube](https://www.youtube.com/watch?v=TGGGDpb04Yc) [23:49]\n\n\n## Algorithms\n* Presenter-name: **Title of the video** (Event, Year)\n    * Video: [video link] [length-of-video]\n    * Slides: [slide link]\n    * [Misc resources](link)\n    * \n\n\n\n## Mathematics\n* Presenter-name: **Title of the video** (Event, Year)\n    * Video: [video link] [length-of-video]\n    * Slides: [slide link]\n    * [Misc resources](link)\n    * \n\n\n\n## Intro on Hadoop Ecosystem\n*  Bill Graham: **Intro to Hadoop** (Part of BerkeleyiSchool course Info290:\"Analyzing Big Data With Twitter\", 2012)\n    * Video: [youtube](https://www.youtube.com/watch?v=t3fEGhE-HYA) [1:22:26]\n    * Slides: [presentation](http://blogs.ischool.berkeley.edu/i290-abdt-s12/files/2012/08/BillGraham_IntroToHadoop_Aug30.pdf)\n    * \n\n\n## HDFS\n* Andrew Collette: **HDF5 is Eating the World** (SciPy 2015)\n    * Video: (Youtube)[https://www.youtube.com/watch?v=nddj5OA8LJo] [18:30]\n    * Slides: \n\n* Quincey Koziol: **Title of the video** (2014)\n    * Video: (Youtube)[https://www.youtube.com/watch?v=IN1bqxj4pxE] [1:17:09]\n    * Slides: (mcs.anl.gov)[http://press3.mcs.anl.gov/computingschool/files/2014/01/QKHDF5-Intro-v2.pdf]\n\n\n## Spark\n* Presenter-name: **Title of the video** (Event, Year)\n    * Video: [video link] [length-of-video]\n    * Slides: [slide link]\n    * [Misc resources](link)\n    * \n\n\n\n## Python-based analysis\n* Wes McKinney: **My Data Journey with Python** (SciPy 2015)\n    * Video: [youtube](https://www.youtube.com/watch?v=kHdkFyGCxiY) [47:45]\n    * Slides: [SlideShare](http://www.slideshare.net/wesm/my-data-journey-with-python)\n* Sarah Guido: **Hands-on Data Analysis with Python** (PyCon 2015)\n    * Video: [Youtube](https://www.youtube.com/watch?v=L4Hbv4ugUWk) [2:54:57]\n* Jonathan Rocher: **Analyzing and Manipulating Data with Pandas** (SciPy 2015 Tutorial )\n    * Video: [Youtube](https://www.youtube.com/watch?v=0CFFTJUZ2dc)\n    * [Exercise and tutorial instructions](https://github.com/jonathanrocher/pandas_tutorial)\n* Andreas Mueller \u0026 Kyle Kastner: **Machine Learning with Scikit Learn** (SciPy 2015 Tutorial)\n    * Video: [Part I](https://www.youtube.com/watch?v=80fZrVMurPM), [Part II](https://www.youtube.com/watch?v=Ud-FsEWegmA)\n    * [Tutorial Materials](https://github.com/amueller/scipy_2015_sklearn_tutorial)\n\n## R-based analysis\n* David Langer: **Introduction to Data Science with R - Data Analysis** (2014)\n    * Video: [https://www.youtube.com/watch?v=32o0DnuRjfg\u0026index=1\u0026list=PLTJTBoU5HOCRrTs3cJK-PbHM39cwCU0PF] [1:21:49]\n    * Source code: [https://github.com/EasyD/IntroToDataScience]\n    * This is the first video of a two-part tutorial. \n\n## Uncategorized\n* Presenter-name: **Title of the video** (Event, Year)\n    * Video: [video link] [length-of-video]\n    * Slides: [slide link]\n    * comments\n    * \n\n","project_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fkmonsoor%2Fdata-must-watch","html_url":"https://awesome.ecosyste.ms/projects/github.com%2Fkmonsoor%2Fdata-must-watch","lists_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fkmonsoor%2Fdata-must-watch/lists"}