# The plan to take over the world: do data science (organic, low fat version) with Python.
# You may want to start by looking at the list of resources we compiled.
# Feel free to jump right in and do the Problem Set excercises. We won't judge (much).
resources = ["python tutorials", "data science websites", "online courses", "books", "podcasts"]
def expand_knowledgebase(resources):
collect(resources) # done
post_online(resources) #done
discuss_w_pyladies(resources)
append_new(resources)
rank(resources)
# defining some variables
easy = 0
hard = 100
difficulty = easy
You = "Advanced Beginner"
PyLadies_meetup = "Wednesdays biweekly"
# step_0 will only be repeated once for every beginner
step_0 = "install and learn the basic tools like Git/GitHub, Sublime text, Jupyter, ..."
# steps 1-7 will be repeated for every PyLadies meetup
steps = [
"Define a data science problem to solve",
"Create a toy data set",
"Using resources, find out how this problem is typically solved",
"Create your own solution for the problem using the toy data set",
"At the PyLadies meetup: \
Tell other PyLadies about the problem \
Give them your toy data set and let them try steps 2 and 3",
"At the PyLadies meetup + 2 weeks: \
Collect all solutions \
Pick the best one (the most understandable for a beginner) \
Post the best solution online",
"Profit (the winner gets a small prize)!"
]
while (You != "Data Scientist"):
if difficulty == hard:
You = "Data Scientist"
print "Congratulations!"
else:
for each d in difficulty:
print "Difficulty: %s" % difficulty
for each s in steps:
my_steps = steps[s]
print "Step %d" % s, ": %s", % my_steps
difficulty +=1
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Learning Data Science by Doing Data Science and Failing Repeatedly
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