DS4UX (Spring 2016)/Schedule: Difference between revisions

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* [[DS4UX_(Spring_2016)/Day_1_lecture#Part 2: Basic Python concepts|Interactive lecture]]: ''programming concepts 1''
* [[DS4UX_(Spring_2016)/Day_1_lecture#Part 2: Basic Python concepts|Interactive lecture]]: ''programming concepts 1''
* [[DS4UX (Spring 2016)/Day 1 tutorial|Self-guided tutorial and exercises]] — You'll work through a self-guided tutorial to practice the basic concepts we introduced in the lecture.
* [[DS4UX (Spring 2016)/Day 1 tutorial|Self-guided tutorial and exercises]] — You'll work through a self-guided tutorial to practice the basic concepts we introduced in the lecture.


;Homework
;Homework
* Complete [[DS4UX (Spring 2016)/Day 1 tutorial|Self-guided tutorial and exercises]] (if you didn't finish this in class).
* Complete [[DS4UX (Spring 2016)/Day 1 tutorial|Self-guided tutorial and exercises]] (if you didn't finish this in class).
* Complete [[DS4UX_(Spring_2016)/Day_1_exercise#Goal_7:_Practice_Python_using_Codecademy|CodeAcademy lessons]]
* Complete [[DS4UX_(Spring_2016)/Day_1_exercise#Goal_7:_Practice_Python_using_Codecademy|CodeAcademy lessons]]


;Resources
;Resources
* Python for Informatics: [http://www.pythonlearn.com/html-009/book001.html Preface] and [http://www.pythonlearn.com/html-009/book002.html Chapter 1  Why should you learn to write programs?]
* Python for Informatics: [http://www.pythonlearn.com/html-009/book001.html Preface] and [http://www.pythonlearn.com/html-009/book002.html Chapter 1  Why should you learn to write programs?]


=== Week 2: April 4 ===
=== Week 2: April 4 ===
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*[[DS4UX_(Spring_2016)/Day_2_lecture#Part_2:_New_programming_conceptse|Interactive lecture]]: ''programming concepts 2''
*[[DS4UX_(Spring_2016)/Day_2_lecture#Part_2:_New_programming_conceptse|Interactive lecture]]: ''programming concepts 2''
*'''Peer programming exercise:''' [[Baby Names]] ([[Community_Data_Science_Workshops_(Fall_2015)/Day_1_baby_names_project_download|download]])
*'''Peer programming exercise:''' [[Baby Names]] ([[Community_Data_Science_Workshops_(Fall_2015)/Day_1_baby_names_project_download|download]])


;Homework  
;Homework  
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;Resources
;Resources
* Python for Informatics: [http://www.pythonlearn.com/html-009/book003.html Chapter 2  Variables, expressions and statements] and [http://www.pythonlearn.com/html-009/book004.html Chapter 3  Conditional execution]
* Python for Informatics: [http://www.pythonlearn.com/html-009/book003.html Chapter 2  Variables, expressions and statements] and [http://www.pythonlearn.com/html-009/book004.html Chapter 3  Conditional execution]


=== Week 3: April 11 ===
=== Week 3: April 11 ===
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;Resources
;Resources
*''go here''
*''go here''


=== Week 4: April 18 ===
=== Week 4: April 18 ===
[[DS4UX_(Spring_2016)/Day_4_plan|Day 4 plan]]
[[DS4UX_(Spring_2016)/Day_4_plan|Day 4 plan]]


;Class schedule
;Agenda
*[[DS4UX_(Spring_2016)/Day_4_lecture|Day 4 lecture]] - working with web data 2 (SQL)
*[[DS4UX_(Spring_2016)/Day_4_lecture|Day 4 lecture]] - working with web data 2 (SQL)
*introduction to the Wikipedia database
*introduction to the Wikipedia database
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;Resources
;Resources
* 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]  
* 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]  


=== Week 5: April 25 ===
=== Week 5: April 25 ===
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* [[DS4UX_(Spring_2016)#Final_Project_Idea|Final project idea]]
* [[DS4UX_(Spring_2016)#Final_Project_Idea|Final project idea]]


;Class schedule
;Agenda
*[[DS4UX_(Spring_2016)/Day_5_lecture|Day 5 lecture]] - visualizing data
*[[DS4UX_(Spring_2016)/Day_5_lecture|Day 5 lecture]] - visualizing data
*Introduction to Jupyter notebooks
*Introduction to Jupyter notebooks
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[[DS4UX_(Spring_2016)/Day_6_plan|Day 6 plan]]
[[DS4UX_(Spring_2016)/Day_6_plan|Day 6 plan]]


;Class schedule
;Agenda
* [[DS4UX_(Spring_2016)/Day_6_lecture|Day 6 lecture]] - working with text
* [[DS4UX_(Spring_2016)/Day_6_lecture|Day 6 lecture]] - working with text
* Jupyter notebooks 2
* Jupyter notebooks 2
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*[[Final project proposal|DS4UX_(Spring_2016)#Final_Project_Proposal]]
*[[Final project proposal|DS4UX_(Spring_2016)#Final_Project_Proposal]]


;Class schedule
;Agenda
* [[DS4UX_(Spring_2016)/Day_7_lecture|Day 7 lecture]] - describing data with statistics
* [[DS4UX_(Spring_2016)/Day_7_lecture|Day 7 lecture]] - describing data with statistics
* Jupyter notebooks 3
* Jupyter notebooks 3
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[[DS4UX_(Spring_2016)/Day_8_plan|Day 8 plan]]
[[DS4UX_(Spring_2016)/Day_8_plan|Day 8 plan]]


;Class schedule
;Agenda
* [[DS4UX_(Spring_2016)/Day_8_lecture|Day 8 lecture]] - research study design
* [[DS4UX_(Spring_2016)/Day_8_lecture|Day 8 lecture]] - research study design


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[[DS4UX_(Spring_2016)/Day_9_plan|Day 9 plan]]
[[DS4UX_(Spring_2016)/Day_9_plan|Day 9 plan]]


;Class schedule
;Agenda
* [[DS4UX_(Spring_2016)/Day_9_lecture|Day 9 lecture]] - communicating your findings
* [[DS4UX_(Spring_2016)/Day_9_lecture|Day 9 lecture]] - communicating your findings
* review of key concepts and tools
* review of key concepts and tools
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* [[DS4UX_(Spring_2016)#Final_Project_Presentation|Final project presentation]]
* [[DS4UX_(Spring_2016)#Final_Project_Presentation|Final project presentation]]


;Class schedule
;Agenda
* [[DS4UX_(Spring_2016)/Day_10_lecture|Day 10 lecture]] - Final project report review, next steps for Data Science
* [[DS4UX_(Spring_2016)/Day_10_lecture|Day 10 lecture]] - Final project report review, next steps for Data Science
* Final project presentations
* Final project presentations
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=== Week 11: June 6 ===
=== Week 11: June 6 ===
 
FINALS WEEK - NO CLASS
;Assignments due
;Assignments due
*[[DS4UX_(Spring_2016)#Final_Project_Report|Final project report and code]] due '''by midnight on Wednesday, 6/8/2016'''
*[[DS4UX_(Spring_2016)#Final_Project_Report|Final project report and code]] due '''by midnight on Wednesday, 6/8/2016'''


;Class schedule
 
*Finals week - No class!


[[Category:DS4UX (Spring 2016)]]
[[Category:DS4UX (Spring 2016)]]

Revision as of 00:37, 27 March 2016

Week 1: March 28

Day 1 plan

Assignments due
  • fill out the pre-course survey
Agenda
  • Quick introductions — Be ready to introduce yourself and describe your interest and goals in the class.
  • Why Programming and Data Science for UX Research? — What this course is about
  • Class overview and expectations — We'll walk through this syllabus.
  • Group formation — We'll assemble in our peer programming groups for the first time.
  • Installation and setup — You'll install software including the Python programming language and run through a series of exercises.
  • Interactive lecture: programming concepts 1
  • Self-guided tutorial and exercises — You'll work through a self-guided tutorial to practice the basic concepts we introduced in the lecture.
Homework
Resources


Week 2: April 4

Day 2 plan

Agenda
Homework
Resources


Week 3: April 11

Day 3 plan

Class schedule
  • Interactive lecture: creating your own functions
  • Day 3 lecture - working with web data 1 (APIs)
  • Peer programming: Practice with API sandboxes
  • Interactive lecture: requesting data from an API using Python
Homework
Resources
  • go here


Week 4: April 18

Day 4 plan

Agenda
  • Day 4 lecture - working with web data 2 (SQL)
  • introduction to the Wikipedia database
  • programming concepts 4
  • SQL queries
  • advanced API queries
  • final project discussion 1
  • data sources
  • research questions
  • outline of project idea and project plan deliverables
Exercises
  • MYSQL queries with Quarry
  • SOQL queries with Hurl.it and Python
Homework
Resources


Week 5: April 25

Day 5 plan

Assignments due
Agenda
  • Day 5 lecture - visualizing data
  • Introduction to Jupyter notebooks
  • Jupyter notebooks 1
  • importing data with SQL and API queries
  • data manipulation with Jupyter
Exercises
  • visualize Seattle building permit data
Homework
Resources
  • go here


Week 6: May 2

Day 6 plan

Agenda
  • basic regular expressions
  • graphing data with MatPlotLib
Exercises
  • counting mentions and welcomes in the Teahouse corpus
  • plotting trends over time in the Teahouse corpus
Homework
Resources
  • go here


Week 7: May 9

Day 7 plan

Assignments due
Agenda
  • Day 7 lecture - describing data with statistics
  • Jupyter notebooks 3
  • running statistics with SciPy
Exercises
  • plotting Burke-Gilman bike traffic on rainy days
Coding challenges
Resources
  • go here


Week 8: May 16

Day 8 plan

Agenda
Exercises
  • Replicate Teahouse invite A/B test
Coding challenges
Resources
  • go here


Week 9: May 23

Day 9 plan

Agenda
  • Day 9 lecture - communicating your findings
  • review of key concepts and tools
  • presentation practice
Homework
  • goes here
Resources
  • go here


Week 10: May 30

Assignments due
Agenda
  • Day 10 lecture - Final project report review, next steps for Data Science
  • Final project presentations


Week 11: June 6

FINALS WEEK - NO CLASS

Assignments due
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