DS4UX (Spring 2016)/Schedule: Difference between revisions

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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]
* [[Python data types cheat sheet]]
* [[Python loops cheat sheet]]
* [http://communitydata.cc/~mako/cdsw-au2015-lecture1-20151010.ogv cdsw-au2015-lecture1-20151010.ogv] -- Professor Mako Hill's lecture video from a previous course, which covers most of the concepts from my Week 1 and Week 2 lectures.


=== Week 3: April 11 ===
=== Week 3: April 11 ===

Revision as of 02:41, 31 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

Agenda
  • We'll walk through the concepts and solutions to the code challenges from last week as a group.
  • Interactive lecture - reading and writing datafiles, dictionaries
  • We'll explore dataset and research question options for the Final Project assignments.
  • We'll begin working on a series of exercises using the Baby Names dataset
Homework
Resources
  • go here

Week 4: April 18

Day 4 plan

Agenda
Homework
Resources

Week 5: April 25

Day 5 plan

Assignments due
Agenda
  • Day 5 lecture - visualizing web data
  • Introduction to Jupyter notebooks
  • graphing data with matplotlib
Homework
Resources
  • go here


Week 6: May 2

Day 6 plan

Agenda
Homework
Resources
  • go here


Week 7: May 9

Day 7 plan

Assignments due
Agenda
Coding challenges
Resources
  • go here


Week 8: May 16

Day 8 plan

Agenda
Coding challenges
Resources
  • go here


Week 9: May 23

Day 9 plan

Agenda
  • Day 9 lecture - research study design
  • review of key concepts and tools from this course
  • presentation workshop
Resources
  • go here


Week 10: June 3 (DATE CHANGE)

Please note that this class we will meet Friday evening, rather than Monday evening, because of the Memorial Day holiday.

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