Python workshop 11th March – instructions

Schedule

7:00-7:10 getting started: organise yourselves around the table, from beginner upwards

7:10-7:30 talk: a brief introduction to data science

7:30-9:00 coding: work at your own level with those around you

What we’ll do

We guess that people will fit into one of three categories: beginner, intermediate or advanced, and have tasks for all levels.

Beginner

If you’re completely new to coding, the first thing to do is learn a bit about programming. The very basic concepts of coding are the same across lots of languages, but we’re using Python which was designed with an emphasis on readability. A great place to get started is Code Academy, which has tutorials and exercises you can run in your browser, without having to install anything.

Intermediate

If you already have some experience with writing code, and either want some more practice, or to get familiar with Python, we recommend the Google Python class. This covers some of the basics of Python, with a data science bias to the exercises.

There are instructions for installing Python, or you could use an online service like Python Anywhere to write and run code without having to install anything on your own machine.

Advanced

If you know how to write code and want to work on real problems, then we’ll get started on some data science challenges.

First step is to install Python and some of the libraries that are useful: numpyscipypandas and scikit-learn. A great place to get the set of useful libraries is Anaconda, a free Python distribution for scientific computing.

Kaggle have some ‘getting started’ tasks, including one from Data Science London. This is a binary supervised classification task where you have to identify whether each example in the dataset belongs to class 0 or to class 1. You can use sci-kit learn to get started without knowing too much about what’s going on under the hood; the most important thing to get to grips with is the use of training, development and test datasets, cross-validation and generalisation. These are things we can discuss on the night. There’s some starter code on GitHub which will read in the data from the Data Science London task and train a basic classifier.

Finally, if you want to really get a good understanding, then Coursera’s Machine Learning course started last week and covers a lot of the theory of machine learning. To do the course, you’ll need to know linear algebra (matrices and vectors) and a little calculus, as well as be able to program in Matlab/Octave.

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4 Responses to Python workshop 11th March – instructions

  1. yvonne nobis says:

    I’m really sorry -but can’t come to this as childcare/children issues…will come to next one!

  2. Suzie says:

    It’s a shame I missed this – I only discovered your website yesterday! I’m completely new to programming (I started learning python last week on Code Academy). I wonder if there are plans to run any further workshops?

    • Hi Suzie, we are running another workshop in April, on visualisation in javascript, and I’m sure we’ll run more on Python in the future! Sign up to our meetup group to stay informed, hope you can make it along soon 🙂

      Cambridge Women and technology

      Cambridge, GB
      118 Members

      This is a meet-up for women and technology. The group format and topics will be directed by the needs of its members. We will have events, talks and/or workshops on a variety …

      Next Meetup

      Examining data with Matlab

      Tuesday, Aug 26, 2014, 7:00 PM
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