From 87d88037fabe95f67be1f55f8e49bed7434f3215 Mon Sep 17 00:00:00 2001 From: Rahul Date: Sun, 1 Feb 2015 00:52:50 +0530 Subject: [PATCH 1/2] Adding UC Berkeley's Analyzing Big Data with Twitter course. --- README.md | 5 +++++ 1 file changed, 5 insertions(+) diff --git a/README.md b/README.md index d5f3972..da15869 100644 --- a/README.md +++ b/README.md @@ -390,3 +390,8 @@ Courses - [Lectures](http://www.schneems.com/ut-rails/) - [Assignments](http://www.schneems.com/ut-rails/) - [Videos](https://www.youtube.com/playlist?list=PL7A85FD7803A8CB1F) + + +- [Info 290](http://www.ischool.berkeley.edu/courses/i290-abdt) **Analyzing Big Data with Twitter** *UC Berkeley school of information* Lecture Videos + - In this course, UC Berkeley professors and Twitter engineers provide lectures on the most cutting-edge algorithms and software tools for data analytics as applied to Twitter's data. Topics include applied natural language processing algorithms such as sentiment analysis, large scale anomaly detection, real-time search, information diffusion and outbreak detection, trend detection in social streams, recommendation algorithms, and advanced frameworks for distributed computing. + - [Lecture Videos](http://www.ischool.berkeley.edu/newsandevents/audiovideo/webcast/21963) From 63575a63032ac8a5990be086516afca8591080e9 Mon Sep 17 00:00:00 2001 From: Prakhar Srivastav Date: Sun, 1 Feb 2015 10:59:30 +0300 Subject: [PATCH 2/2] added coursepage for Info290 --- README.md | 3 +-- 1 file changed, 1 insertion(+), 2 deletions(-) diff --git a/README.md b/README.md index da15869..38963b8 100644 --- a/README.md +++ b/README.md @@ -390,8 +390,7 @@ Courses - [Lectures](http://www.schneems.com/ut-rails/) - [Assignments](http://www.schneems.com/ut-rails/) - [Videos](https://www.youtube.com/playlist?list=PL7A85FD7803A8CB1F) - - - [Info 290](http://www.ischool.berkeley.edu/courses/i290-abdt) **Analyzing Big Data with Twitter** *UC Berkeley school of information* Lecture Videos - In this course, UC Berkeley professors and Twitter engineers provide lectures on the most cutting-edge algorithms and software tools for data analytics as applied to Twitter's data. Topics include applied natural language processing algorithms such as sentiment analysis, large scale anomaly detection, real-time search, information diffusion and outbreak detection, trend detection in social streams, recommendation algorithms, and advanced frameworks for distributed computing. - [Lecture Videos](http://www.ischool.berkeley.edu/newsandevents/audiovideo/webcast/21963) + - [Previous Years coursepage](http://blogs.ischool.berkeley.edu/i290-abdt-s12/)