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PyParis 2017 / Un mooc python, by thierry parmentelat

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MOOC PYTHON / FUN
Thierry Parmentelat - Inria
PyParis, May 13th 2017
Auteurs : Arnaud Legout & Thierry Parmentelat

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30,000 ft
for whom: figures about the audience
what: scope
how: thanks jupyter !

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AUDIENCE

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PyParis 2017 / Un mooc python, by thierry parmentelat

  1. 1. MOOC PYTHON / FUN Thierry Parmentelat - Inria PyParis, May 13th 2017 Auteurs : Arnaud Legout & Thierry Parmentelat
  2. 2. 30,000 ft for whom: figures about the audience what: scope how: thanks jupyter !
  3. 3. AUDIENCE
  4. 4. Plateforme FUN http://fun-mooc.fr/
  5. 5. TARGET (1) french-speaking MOOC target audience : BAC+2 not the actual audience..
  6. 6. TARGET (2) little exposure to programming but not newbie-oriented either python as a tool - and not as an end still thorough review of python concepts
  7. 7. FIGURES past: 3 sessions so far: 2014, 2015, 2016 33268 total registered students for python2.7 next: being rewritten for python3 shooting in Sept - run in Nov/Dec inputs welcome !
  8. 8. SESSION 1
  9. 9. Profil des parti Motivations SESSION 2
  10. 10. SESSION 2Niveau d'études Connaissances préalables de Python
  11. 11. SESSION 2 Niveau d'études Sources: statistiquesFUN et réponsesau questionnaire Environ 80% et 20% de Moyenne d'âge : e
  12. 12. SESSION 2 Situation actuelle - Belgique - Sénégal - Cameroun - Togo - Brésil ron 80% d'hommes t 20% de femmes
  13. 13. SESSION 3
  14. 14. SESSION 3
  15. 15. SESSION 3
  16. 16. WORTH NOTING a few institutions instruct their students to follow the MOOC online and then organize their own exams namely: UPMC, CentraleSupelec as well as a few master programs
  17. 17. CONTENTS
  18. 18. THE PIECES 7 - rather dense - weeks, with videos - of course .. quiz - as supported by FUN (marginal use) notebooks - more on this later forum : very active, hence the ‘scheduled' runs
  19. 19. COMMON TRACK (W1-W5) getting started basic types, functions, syntax advanced types,
 shared refs, copies packages / modules iterables / iterators comprehensions functional objects argument passing attributes classes - inheritance
 overloading operators generators / gen exps exceptions
  20. 20. ADVANCED TRACK (W6-W7) generators advanced attributes decorators metaclasses mini-projects data networking system
  21. 21. LITTLE OR NO COVERAGE stdlib: only touch on some tools benchmarking / profiling / debugging : only mentioned en passant not covered numpy, a fortiori pandas not covered : testing
  22. 22. NOTEBOOKS
  23. 23. REQUIREMENTS need for some programming sandbox integrated with the FUN / edx platform without requiring a local installation potentially extensible: auto correction auto illustration
  24. 24. EDX/INTEGRATION In order to allow for notebooks inside FUN/edX : new type of component (video, quiz, … notebook) that simply redirects to a separate architecture through an <iframe>
  25. 25. SAMPLES On the FUN platform
  26. 26. NOTEBOOK INFRA accepts all incoming URLs from FUN’s IP create Unix accounts / student on the fly hosts as many notebook servers as students copies master notebooks on demand
  27. 27. NBHOSTING a replacement for a former quick-and-dirty solution http://github.com/parmentelat/nbhosting based on nginx, for reverse-proxy / firewall-friendly django, for internal logic docker, for isolation / student + 1 course = 1 image
  28. 28. THANK YOU again : inputs for the python3 next release are more than welcome !

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