Editing Community Data Science Course (Spring 2019)

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=== Final Project Proposal ===  
 
=== Final Project Proposal ===  
 
:'''Maximum Length:''' 1500 words (~5 pages)
 
:'''Maximum Length:''' 1500 words (~5 pages)
:'''Due Date:''' Week 8
+
:'''Due Date:''' Week 7
  
 
This proposal should focus on two questions:
 
This proposal should focus on two questions:
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* Class overview and expectations — We'll walk through this syllabus.
 
* Class overview and expectations — We'll walk through this syllabus.
 
* [[Community_Data_Science_Course/Day_1_Exercise|Day 1 Exercise]] — You'll install software including the Python programming language and run through a series of exercises.
 
* [[Community_Data_Science_Course/Day_1_Exercise|Day 1 Exercise]] — You'll install software including the Python programming language and run through a series of exercises.
* [[Community_Data_Science_Course_(Spring_2017)/Day_1_Tutorial|Day 1 Tutorial]] — You'll work through a self-guided tutorial introducing you to some basic concepts. When you're done, you'll meet with me and I'll check you off.
+
* [[Community_Data_Science_Course/Day_1_Tutorial|Day 1 Tutorial]] — You'll work through a self-guided tutorial introducing you to some basic concepts. When you're done, you'll meet with me and I'll check you off.
  
 
* A few interesting links we discussed in class are [[Community_Data_Science_Course_%28Spring_2019%29/DataSources|here]]
 
* A few interesting links we discussed in class are [[Community_Data_Science_Course_%28Spring_2019%29/DataSources|here]]
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* Have a working python environment on your personal laptop.
 
* Have a working python environment on your personal laptop.
 
* Have written your first program in the python language.
 
* Have written your first program in the python language.
 
=== Week 2: April 10 ===
 
 
'''Assignment Due (nothing to turn in):'''
 
 
Read chapters 2 and 3 of Python for Everyone:
 
* Chapter 2, Variables
 
* Chapter 3, Conditionals
 
 
Finish setup, tutorial and code academy in the week 01 exercises.
 
 
Do the Tip Calculator exercise in Code Academy. You can access this exercise after you finish the first 14 exercises.
 
 
'''Class Schedule:'''
 
 
* Discuss a successful final project from last year.
 
* [[Community_Data_Science_Course_%28Spring_2019%29/Day_2_Lecture|Lecture notes]]
 
* Review material from last week: variables, assignments, if statements
 
* Introduce new material: loops and lists
 
* Project time — We'll begin working on the [[wordplay]] independent projects independently or in small groups.
 
 
Here are your [[Community_Data_Science_Course_(Spring_2019)/Day_2_Coding_Challenges|Exercises]]
 
 
'''By the end of class you will:'''
 
 
* Have written a program with loops and lists.
 
* Have a better understanding of the expectations for your final project, and be ready to hand in your initial assignment.
 
 
=== Week 3: April 17 ===
 
 
'''Assignment Due:'''
 
 
Final project idea.  Turn in on [https://canvas.uw.edu/courses/1272567/assignments/4788468 Canvas].
 
 
Finish Wordplay examples
 
 
Reading
 
* Read chapter 4, 5 of Python for Informatics:
 
** Functions (this is mostly new)
 
** Iteration (this is mostly review)
 
 
'''Course plan:'''
 
 
* Go over last week's assignment.
 
* Dictionaries and aggregations [[Community Data Science Course (Spring 2019)/Day 3 Notes|Day 3 Notes]]
 
* A break! Let's really aim for 7:30 this time.
 
* Discuss average, median using the wordplay data.
 
* Project time — We'll begin working on a series of project based on the [http://mako.cc/teaching/2015/cdsw-autumn/babynames.zip Baby names] project.
 
* [[Community Data Science Course (Spring 2019)/Day 3 Coding Challenges|Day 3 Coding Challenges]]
 
 
'''Resources:'''
 
 
* [[Python_data_types_cheat_sheet]] A cheat sheet with everything we've covered in class so far including today.
 
 
=== Week 4: April 24 ===
 
'''Assignment Due:'''
 
 
Finish Baby Names examples.
 
 
Reading
 
* Read chapters 10 and 8 of Python for Informatics: Dictionaries and Files.
 
 
'''Course Plan'''
 
 
* Let's discuss two visualizations I found.
 
* Discuss week of May 8. I'm in North Carolina.
 
* Go over last week's assignment.
 
* Discuss histograms in python, and build a few.
 
* Project time - We'll reuse the babynames code.
 
* [[Community Data Science Course (Spring 2019)/Day 4 Coding Challenges|Day 4 Coding Challenges]]
 
 
=== Week 5: May 1 ===
 
'''Assignment Due:'''
 
 
Turn in (on canvas!) solution to this problem:
 
 
List '''how many babies''' were born that share a name with 4, 6, 7, 8, ..., 19 other babies. Also, list how many babies share names with more than 20 other babies under the key "common".
 
 
 
'''Course Plan'''
 
 
* Let's discuss week of May 8. (Doodle poll results)
 
* Go over last week's assignment and review histograms.
 
* Discuss APIs and downloading data from the internet. Refer to [[Community Data Science Course (Spring 2019)/Day 5 Notes|Day 5 Notes]]
 
* Spend time on [[Community Data Science Course (Spring 2019)/Day 5 Coding Challenges|Day 5 Coding Challenges]]
 
 
 
=== Week 7: May 15 ===
 
 
'''Course Plan'''
 
 
* Let's discuss remaining schedule
 
* Discuss data downloading and cleaning. Refer to [[Community Data Science Course (Sprint 2019)/Day 7 Notes|Day 7 Notes]]
 
* We will be discussing this data set: https://data.seattle.gov/Transportation/Collisions/vac5-r8kk
 
* Spend time on [[Community Data Science Course (Spring 2019)/Day 7 Coding Challenges|Day 7 Coding Challenges]] which are group challenges.
 
 
 
=== Week 8: May 22 ===
 
 
'''Assignment Due:'''
 
 
Final Project Proposal. Canvas link [https://canvas.uw.edu/courses/1272567/assignments/4821879 here].
 
 
'''Course Plan'''
 
 
* Discuss pivot tables in Excel
 
* [[Community Data Science Course (Spring 2019)/Day 8 notes|Day 8 notes]]
 
 
=== Week 9: May 29 ===
 
 
'''Assignment Due:'''
 
 
Nothing! But I hope you are making good progress.
 
 
'''Course Plan'''
 
 
* Follow up from last week: let's discuss inference and A/B testing.
 
** [https://www.exp-platform.com/Documents/2016-11BestRefutedCausalClaimsFromObservationalStudies.pdf Examples of bad observational studies]
 
* Visualization dos and don'ts. We'll discuss the European Environmental Agency's [https://www.eea.europa.eu/data-and-maps/daviz/learn-more/chart-dos-and-donts list of advice for making charts]. **I will refer to this guide as a grade your final projects.**
 
* Two options for remainder of class. You can work through this introductory guide to visualization in python or you can work on your final project. I'll be here to answer any questions.
 
 
'''Optional visualization in python tutorial'''
 
Self-guided visualization tutorial in python. [https://raw.githubusercontent.com/guyrt/teaching/master/2019/Com520B/VisualizationNotebook.ipynb Download here]. Save the file in a new directory in your desktop and open it with jupyter notebook
 
 
If you are on Windows, you may run into an issue with missing path variables. [https://stackoverflow.com/questions/52821162/jupyter-notebook-failed-to-load-dll This SO post helped me solve it.]
 
 
=== Week 10: June 5 ===
 
 
'''Assignment Due:'''
 
 
Final Project Presentation!
 
  
 
== Administrative Notes ==
 
== Administrative Notes ==

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