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Python for Data Science


The amount of data available to us is growing rapidly, but what is required to make useful conclusions out of it? During this presentation we are going to learn how to use Python as your tool for data science. The presentation will go through the phases most often required when working with real-world data.


  1. Different tactics to gather your data
  2. Cleansing, scrubbing, correcting your data
  3. Running analysis for your data
  4. Bring your data to live with visualizations
  5. Publishing your data for rest of us as linked open data

The presentation is for those of us brave enough to enter the valley of wild data and face the horrors of uncertainty. It's an introductory presentation but people with experience of doing similar things with Python or some other tool such as R are also warmly welcome to participate the discussion.


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