Second Round at Lawrence Berkeley

Last week we finished up our second workshop at Lawrence Berkeley Lab. This time around, we tried a more free-form version of the feedback exercise in which students live-typed their feedback into an Etherpad at the end of each day. This went very well, as it gave us time to gather unique comments, get a rough idea of the amount of support for each comment, and to respond to some of the comments in real time. We asked three questions: what was good, what was bad/confusing, and what we didn't do or talk about that we should have.

The Good

• Introduction to python and how to install things with command lines
• Understanding python objects, classes, functions, methods, etc.
• Thinking about how to structure the directories for a project
• Hearing how regular Python users use Python (+1)
• Just getting finally to write some .py code!
• Real world example-driven exercises
• Knowledge of helpful data types in Python
• iPython notebook and Etherpad are amazing (+1)
• The party on the Etherpad !!!!! (+1 +1) [Ed: the students had some fun "passing notes" in the Etherpad]
• Patient, fast, specific help (+1)
• An explanation of git from people who use git (+1 +1 +1)
• Inside structure of git
• You put a lot of things in my brain in a very short time (+1)
• Standalone scripts is my new goal for my code!
• Start thinking about how to test code for reusability
• Danish and coffee / snacks / food juice

The Bad or Confusing

• Python version issues, especially multiple Python versions on same system (+1 +1 +1)
• Relationship between Anaconda/IPython/Enthought/system Python
• Use of iPython Notebook vs console, roles in real-world code development (+1)
• Glossary/handout on Python would have been helpful for beginners
• Most of the Unix tutorial was extremely basic (+1 +1 +1) [Ed: There were two follow ups to this comment in which students said they needed the basic tutorial badly.]
• Worrying about whether to abandon perl and R for python - then I'd have to start the learning curve all over.
• Too fast for beginners, but noticed that others were bored (+1)
• Not enough 'signposting' during talks/lessons
• It's over now :\

Things We Didn't Do or Talk About But Should Have

• Online "getting started with Unix" tutorial before class (+1 +1 +1)
• Making and annotating/labelling plots, more Matplotlib (+1 +1)
• Discussion of computational and memory efficiency
• "Best practices" for developing and maintaining code (+1 +1 +1 +1)
• Fitting data (+1 +1)
• How to share code, etc. with those who don't use version control
• Working with specific types of data (ie, DNA)
• More about modules and importing, common bugs, etc.
• Is there a better way to find help than google and stackoverflow?
• Overhead when working with extremeley large data sets

Thanks to Shreyas Cholia and to instructors Matthew Brett, Cindee Madison, and Ariel Rokem and helpers Paul Ivanov and Matt Terry.