Process Mining: Data Science in Action by Coursera

This is  my short feedback for Coursera Process Mining course (by Wil van der Aalst from Eindhoven University of Technology)
Name of the course sounds very interesting, but the main task is quite simple.
It's about building behaviour model based on events log(you need to consider overfitting and underfitting). That's mean: your model should explain majority of cases and be general enough for explaining new cases.
Main tools, recommended in the course, are Disco and ProM. They allow building models according to different notations(e.g. BPMN) and making visualisations.
Two main aspects of process mining are organisational and social aspects:
Organisational aspects tasks:

• discover typical workflow actions(for customers, employees, etc)
• analyse of time spent for every tasks
• "bottlenecks" mining

Social aspects tasks:

• discover users groups and users relations within process
• analysis of time spending for every worker, customer, etc

In addition, in both aspects you can recommend next steps or forecast time of completion future tasks.

Lectors slideshare: http://www.slideshare.net/wvdaalst
Next session: April-May 2015

Visualizing Data using t-SNE

If you need solution for  visualization of high-dimensional datasets- t-SNE  is a great choice.
Video:

 

Read more about t-SNE 

Dive into Deep Learning

If you are interested in deep learning - you can try UFLDL (Unsupervised Feature Learning and Deep Learning) tutorial from Stanford University.
If this topic is really new for you - it is better to start from https://www.coursera.org/course/ml. After this session course will change format into self-study.