The purpose of PyNoon is to help professionals learn Python, the world’s most popular programming language, in a friendly and convenient learning environment to the level where they can actually start using Python at work.

Accessible: To make them as accessible as possible, PyNoon courses are scheduled around lunchtime and in central locations such as the CBD.

Community: The secret sauce is the community dimension. It is easy to have good intentions about learning Python on our own but doing it alongside others makes it much easier to actually learn enough to achieve useful results.

Supported Self-Learning: The course is centred around on-line resources but friendly and knowledgeable volunteers will be available to assist learners. There will also be instructor-led live coding to help people bridge the gap between learning simple syntax and actually writing working programs. It is also assumed that learners will aim to do an hour of extra on-line learning between sessions.

Practical: The latter weeks of the course will shift towards independent project work according to individual interests and work needs. This is the chance to consolidate learning into something useful.

To learn more about the TechNoon movement behind PyNoon, check out the TechNoon manifesto.

Founders

Dr Grant Paton-Simpson

Grant has been an enthusiastic user of Python for many years and has delivered numerous conference talks, meetup presentations, and training sessions on the language. Grant's open source statistics application, SOFA Statistics (over 300,000 downloads to date) is completely written in Python as is the forthcoming replacement SOFA Lite. More recently, Grant has collaborated with Ben Denham to launch the When Of Python initiative aimed at ensuring Python lives up to its original promise of simplicity and elegance. Grant currently works in the Tech Insights team at 2degrees and was part of the Data Science Team at Qrious where he processed hundreds of billions of records using PySpark and Python.

Dr Ben Denham

Ben loves using Python every day in his work as a data scientist to help organisations get more from their data. For his recently completed PhD thesis in collaboration with Fisher & Paykel Appliances, Ben developed machine learning algorithms in Python that can be applied despite common data deficiencies. Ben's experience ranges from data science to web application development, and he previously worked as software architect for NZ security software startup DataMasque. Ben loves teaching others how to get stuff done with Python; he has run training courses on a variety of technologies for software development and co-delivered talks and an 'unconference' with Grant Paton-Simpson at the national Python conference: KiwiPycon.