2012-08-20: Machine Learning

Interested in artificial intelligence, programming with open source software? Then join us!

Machine Learning @ Stanford University

On 20th of August the Machine Learning Course from the Stanford University is starting. The course takes 10 weeks and is well known for the excelent content: programming in Python and GNU Octave and statistic methods: a challenging introduction into the field of artificial intelligence.

Why?
AI is for different fields and applications interesting: robots, data mining or agent-based modeling for example – everwhere, where machines have to learn and complex processes and decisions are part of it.

How it works

The course will take around 5-7 hours a week and consists of small chunks of video lectures (8-12min), sometimes with quizzes in it. There are also standalone quizzes and some programming assignments.

We will meet 1-2 times a week to watch & learn together, but how we manage this depends on the participating people’s needs and choice. The learning group can use Spektral for the learning session, but it’s not limited to it (i. e. learning at flats). This all will be discussed in the mailinglist and organized by doodles week by week.

JOIN

Just subscribe to the Mailingliste and you are part of the learning group of the Freie Universität course in spektral. For taking part on coursera, please follow the instructions on their website.

This course will be held in English, so also international students are very welcome.

Open Science Partnership

Members of the Open Science Project are also attending the course, so the whole exercises and experiences will be documented and done in a free and open way. Interested in doing it the open science way? Then look at their Open Science page for this lecture and join them too.

One comment on “2012-08-20: Machine Learning
  1. there is some look up for a study group in vienna: https://class.coursera.org/ml-2012-002/forum/thre

Leave a Reply

Your email address will not be published. Required fields are marked *

*

This site uses Akismet to reduce spam. Learn how your comment data is processed.