Editing Community Data Science Course (Spring 2015)
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* Write or modify a program to collect a dataset from the Wikipedia and Twitter APIs. | * Write or modify a program to collect a dataset from the Wikipedia and Twitter APIs. | ||
* Effectively | * Effectively web API documentation and write Python software to parse and understand a new and unfamiliar JSON-based web API. | ||
* Use both Python based tools like MatPlotLib as well as tools like LibreOffice, Google Docs, or Microsoft Excel to effectively graph and analyze data. | * Use both Python based tools like MatPlotLib as well as tools like LibreOffice, Google Docs, or Microsoft Excel to effectively graph and analyze data. | ||
* Use web-based data to effective answer a substantively interesting question and to present this data effectively in the context of both a formal presentation and a written report. | * Use web-based data to effective answer a substantively interesting question and to present this data effectively in the context of both a formal presentation and a written report. | ||
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The assignments in this class are designed to give you an opportunity to try your hand at using the technical skills that we're covering in the class. There will be no exams or quizzes. There will be weekly assignments that I will ask you to hand-in but will only be graded as ''complete/incomplete''. | The assignments in this class are designed to give you an opportunity to try your hand at using the technical skills that we're covering in the class. There will be no exams or quizzes. There will be weekly assignments that I will ask you to hand-in but will only be graded as ''complete/incomplete''. | ||
Unless otherwise noted, all assignments are due at the end of the day (i.e., 11:59pm on of before Sunday the class they are listed on in the syllabus. | |||
=== Final Project Idea === | === Final Project Idea === | ||
:'''Maximum Length:''' 600 words (~2 pages double spaced) | :'''Maximum Length:''' 600 words (~2 pages double spaced) | ||
:'''Due Date:''' April | :'''Due Date:''' April 6 | ||
In this assignment, you should concisely identify an community that you are interested in a source of data and/or and a list of at least 3-4 questions you might be interested in answering in the context of your final project. I am hoping that each of you will pick an area or domain that you are intellectually committed to and invested in (e.g., in your business or personal life). You will be successful if you describe the scope of the problem and explain why you are interested in using community data science methods. | In this assignment, you should concisely identify an community that you are interested in a source of data and/or and a list of at least 3-4 questions you might be interested in answering in the context of your final project. I am hoping that each of you will pick an area or domain that you are intellectually committed to and invested in (e.g., in your business or personal life). You will be successful if you describe the scope of the problem and explain why you are interested in using community data science methods. | ||
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=== Final Project Proposal === | === Final Project Proposal === | ||
:'''Maximum Length:''' 1500 words (~5 pages) | :'''Maximum Length:''' 1500 words (~5 pages) | ||
:'''Due Date:''' | :'''Due Date:''' April 27 | ||
Building on your project idea assignment, you should describe the specific types of data you will collect, the steps you will take to collect the dataset, the limits and strength of these data for answering the question you have selected, and a description of the kinds of report and visualization you will make. | Building on your project idea assignment, you should describe the specific types of data you will collect, the steps you will take to collect the dataset, the limits and strength of these data for answering the question you have selected, and a description of the kinds of report and visualization you will make. | ||
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I expect that your reports will include text from the first two assignments and reflect comprehensive documentation of your project. Each project should include: (a) the description of the question and community you have identified and information necessary to frame your question, (b) a description of the how you collected your data, (c) the results. | I expect that your reports will include text from the first two assignments and reflect comprehensive documentation of your project. Each project should include: (a) the description of the question and community you have identified and information necessary to frame your question, (b) a description of the how you collected your data, (c) the results. | ||
You should also share with me the full Python source code you used to collect the data and the dataset itself. | |||
I will not be judging the quality or quantity of your code but rather the degree to which you have been successful at answering the ''substantive'' questions you have identified. | |||
A successful project will tell a compelling story and will engage with, and improve upon, the course material to teach an audience that includes me, your classmates, and Comm Lead students taking this class in future years, how to take advantage of community data science more effectively. The very best papers will give us all a new understanding of some aspect of course material and change the way I teach some portion of this course in the future. | |||
=== Participation === | === Participation === | ||
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* Final project presentation: 15% | * Final project presentation: 15% | ||
* Final paper: 40% | * Final paper: 40% | ||
== Schedule == | == Schedule == | ||
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* [[Community Data Science Course (Spring 2015)/Day 1 Exercise|Installation and setup]] — You'll install software including the Python programming language and run through a series of exercises. | * [[Community Data Science Course (Spring 2015)/Day 1 Exercise|Installation and setup]] — You'll install software including the Python programming language and run through a series of exercises. | ||
* [[Community Data Science Course (Spring 2015)/Day 1 Exercise|Self-guided tutorial and exercises]] — You'll work through a self-guided tutorial introducing you to some basic concepts. When you're done, you'll meet with a member of the teaching team and we'll check you off. | * [[Community Data Science Course (Spring 2015)/Day 1 Exercise|Self-guided tutorial and exercises]] — You'll work through a self-guided tutorial introducing you to some basic concepts. When you're done, you'll meet with a member of the teaching team and we'll check you off. | ||
=== Week 2: April 6 === | === Week 2: April 6 === | ||
'''Assignment Due:''' | '''Assignment Due (Sunday at 11:59):''' [[#Final_Project_Ideas|Final Project Ideas]] | ||
'''Readings:''' | '''Readings:''' | ||
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'''Class Schedule:''' | '''Class Schedule:''' | ||
* | * Lecture — Interactive class lecture including a review of material from last week and new material including dictionaries, loops, functions, and modules. | ||
* Project time — We'll begin working on the [[ | * Project time — We'll begin working on the [[Baby names]] independent projects independently or in small groups with assistance from the teaching team. | ||
=== Week 3: April 13 === | |||
'''Assignment Due (Sunday at 11:59):''' Code solving challenges in [[Baby names]] project. | |||
'''Readings:''' | |||
''' | |||
* [ | * Python for Informatics: [http://www.pythonlearn.com/html-009/book013.html Chapter 12 Networked programs] and [http://www.pythonlearn.com/html-009/book014.html Chapter 13 Using Web Services] | ||
'''Class Schedule:''' | '''Class Schedule:''' | ||
* Review | * Review — We'll walk through answers to the assignments for last week as a group. | ||
* Project time — We'll begin working on a series of | * Lecture — Interactive class lecture including background into web APIs; requesting web pages with <code>requests</code>, JSON, and writing to files. | ||
* Project time — We'll begin working on a series of projects using the Wikipedia API. | |||
=== Week 4: April 20 === | === Week 4: April 20 === | ||
'''Assignment Due (Sunday at 11:59):''' Code solving challenges in in the Wikipedia API project from last week. | |||
'''Readings:''' | '''Readings:''' | ||
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* Review — We'll walk through answers to the assignments for last week as a group. | * Review — We'll walk through answers to the assignments for last week as a group. | ||
* Lecture — | * Lecture — Interactive class lecture covering <code>while</code> loops, user-defined functions, debugging, filesystem output, and putting things together into a "real" program. | ||
* Project time — We'll begin modifying the program we walk through in class to adapt it toward our needs and we'll pick out ideas for next steps and challenges for the coming week.. | * Project time — We'll begin modifying the program we walk through in class to adapt it toward our needs and we'll pick out ideas for next steps and challenges for the coming week.. | ||
=== Week 5: April 27 === | |||
=== Week | |||
'''Assignment Due:''' | '''Assignment Due (Sunday at 11:59):''' | ||
* Code solving challenges in created at the end of class the previous week. | * Code solving challenges in created at the end of class the previous week. | ||
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* Review — We'll walk through answers to the assignments for last week as a group. | * Review — We'll walk through answers to the assignments for last week as a group. | ||
* Lecture — Interactive class lecture covering Python objects and classes and using Tweepy to collect data from Twitter. | * Lecture — Interactive class lecture covering code abstraction, Python objects and classes and using Tweepy to collect data from Twitter. | ||
* Project time — | * Project time — Twitter API challenges. | ||
=== Week 6: May 4 === | |||
'''Assignment Due (Sunday at 11:59):''' | |||
* Code solving challenges in created at the end of previous class. | |||
'''Readings:''' | |||
* Python for Informatics: [http://www.pythonlearn.com/html-009/book005.html Chapter 4 Functions] and [http://www.pythonlearn.com/html-009/book012.html Chapter 11 Regular expressions] | |||
''' | '''Class Schedule:''' | ||
* ' | * Review — We'll walk through answers to the assignments for last week as a group. | ||
* | * Lecture — Interactive class lecture counting and powerful "group by" functionality using dictionaries and exporting and simple graphing of processed data using Google Docs , LibreOffice, Microsoft Excel, etc. | ||
* | * Project time — Graphing and work on challenges that use either the Twitter and/or Wikipedia data that we've collected in the two previous sessions. | ||
=== Week 7: May 11 === | === Week 7: May 11 === | ||
'''Assignment Due:''' | '''Assignment Due (Sunday at 11:59):''' | ||
* Code solving challenges in created at the end of previous class. | * Code solving challenges in created at the end of previous class. | ||
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'''Readings:''' | '''Readings:''' | ||
* Python for Informatics: [http://www.pythonlearn.com/html-009/ | * Python for Informatics: [http://www.pythonlearn.com/html-009/book016.html Chapter 15 Visualizing Data] | ||
* Python for Data Analysis: ''Chapter 8 Plotting and Visualization'' | |||
'''Class Schedule:''' | '''Class Schedule:''' | ||
* Review — We'll walk through answers to the assignments for last week as a group. | * Review — We'll walk through answers to the assignments for last week as a group. | ||
* Lecture — Interactive class | * Lecture — Interactive class on using Python to creating visualization using MatPlotLib. Graphing and work on challenges on data on gender and Wikipedia. | ||
* Project time — | * Project time — Project time will be devoted to Q&A focused on individual final projects. | ||
=== Week 8: May 18 === | === Week 8: May 18 === | ||
''' | '''Readings:''' | ||
* | * Python for Data Analysis: ''Chapter 4 NumPy Basics: Arrays and Vectorized Computation'' and ''Chapter 5 Getting Started with pandas'' | ||
''' | '''Class Schedule:''' | ||
* | * Review — We'll walk through answers to the assignments for last week as a group. | ||
* | * Lecture — Interaction lecture on [http://www.numpy.org/ num.py], [http://pandas.pydata.org/ pandas], doing basic statistical tests using [http://statsmodels.sourceforge.net/ Statmodels]. | ||
* Project time — Project time will be devoted to Q&A focused on individual final projects. | |||
=== Week 9: May 25 === | === Week 9: May 25 === | ||
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{{divbox|Note|May 25th is Memorial day and is a University Holiday. Because UW policy requires that we meet 10 times, we will meeting as scheduled. That said, because the building will lock at 6pm, we will be meeting half an hour early at '''5:30pm'''. Please do not be late!}} | {{divbox|Note|May 25th is Memorial day and is a University Holiday. Because UW policy requires that we meet 10 times, we will meeting as scheduled. That said, because the building will lock at 6pm, we will be meeting half an hour early at '''5:30pm'''. Please do not be late!}} | ||
''' | '''Readings:''' | ||
* | * If you are not very comfortable with reading and writing HTML already, complete [http://www.w3schools.com/html/html_intro.asp this online HTML Tutorial]. | ||
* | * Scrapy: [http://doc.scrapy.org/en/latest/intro/tutorial.html Tutorial]; browse [http://scrapy.org/doc/ Documentation] | ||
''' | '''Class Schedule:''' | ||
* | * Review — We'll walk through answers to the assignments for last week as a group. | ||
* Lecture — Interaction lecture on web scraping focusing on what scraping is, what's involved, and how to do it using the Python module [http://scrapy.org/ Scrapy]. | |||
* Project time — Project time will be devoted to Q&A focused on individual final projects. | |||
=== Week 10: June 1 === | === Week 10: June 1 === |