Hi PJ So you're aiming to offer a course in data analytics relating to github? I'd be interested as I want to develop my skill in Python and work with Data as well. Would you be interested in Data Analytics directed at the Financial Markets. I've for a couple of months with a Company developing for trading and risk management.
Damien On Monday, September 22, 2014 2:21:00 PM UTC+1, PJ Fitzpatrick wrote: > > I have over 20 years experience in the financial services and it > industries working in trading, financial market analysis, risk and it. In > the past I have given training courses on financial market analysis and > derivatives. > > I have a proposal for a training course and I want to see if there is much > interest. Below is a brief description of the proposed course. If you are > interested in discussing further or would be interested in attending I can > be contacted at [email protected] <javascript:>. > > > Course Summary > > Describe a methodology, with applications, to analyse popularity in open > source. > > > > Definition of Popularity > > This will look at how to define popularity. The data used will be a time > series of the number of starts and forks for github projects and usage > counts of stackexchange tags. > > > > Description of Methodologies > > In this section appropriate methodologies to analyse popularity will be > discussed. As a lot of these methods will be taken from financial market > analysis there will be an emphasis on: > > -Introducing various approaches to analysing financial time series data > > -Comparing and contrasting financial and open source time series data. > > > > Application of Methodology > > The methodologies presented will be used to answer questions including: > > -Is there any difference between projects that have a steady growth in > popularity and projects that have periodic bursts in popularity. > > -Is there a critical popularity level that if reached means that a project > becomes established and sustainable. > > -For competing projects what relative popularity patterns tend to indicate > what project will become most popular. > > -For complementary projects what can we deduce from relative popularity > movements. > > -What can we tell about projects that have a high degree of correlations > in their popularity. > > > > Specific Detailed Analysis > > The final section will examine in detail: > > - A number of current github projects that appear from their popularity > trends to becoming very popular. > > - The relative popularity of organisations that have significant open > source projects. > > > All participants in the course will get extensive source code used in the > analysis along with the time series data. > > -- You received this message because you are subscribed to the Google Groups "Python Ireland" group. To unsubscribe from this group and stop receiving emails from it, send an email to [email protected]. For more options, visit https://groups.google.com/d/optout.
