DS4UX (Spring 2016)/Schedule

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
 * Complete Self-guided tutorial and exercises (if you didn't finish this in class).
 * Complete CodeAcademy lessons


 * Resources
 * Python for Informatics: Preface and Chapter 1 Why should you learn to write programs?

Week 2: April 4
Day 2 plan


 * Agenda
 * Review concepts we covered last week
 * Interactive lecture: programming concepts 2
 * Peer programming exercise: Baby Names (download)


 * Homework
 * Complete the second set of CodeAcademy lessons
 * Work on the Week 2 coding challenges
 * Create a Wikimedia account & submit your username using 


 * Resources
 * Python for Informatics: Chapter 2 Variables, expressions and statements and Chapter 3  Conditional execution

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
 * Day 3 coding challenges


 * Resources
 * go here

Week 4: April 18
Day 4 plan


 * Agenda
 * Review: We'll walk through answers to the assignment and code challenges from last week as a group.
 * Day 4 lecture - background of web APIs; requesting web pages with, JSON, and writing to files.
 * We'll begin working on a series of projects using the Wikipedia API.


 * Homework
 * Day 4 coding challenges


 * Resources
 * Python for Informatics: Chapter 12 Networked programs and Chapter 13  Using Web Services

Week 5: April 25
Day 5 plan


 * Assignments due
 * Final project idea


 * Agenda
 * Day 5 lecture - visualizing web data
 * Introduction to Jupyter notebooks
 * graphing data with matplotlib


 * Homework
 * Python quiz #5
 * Day 5 coding challenges


 * Resources
 * go here

Week 6: May 2
Day 6 plan


 * Agenda
 * Day 6 lecture - querying databases


 * Homework
 * Day 6 coding challenges


 * Resources
 * go here

Week 7: May 9
Day 7 plan


 * Assignments due
 * Final project proposal


 * Agenda
 * Day 7 lecture - corpus analysis


 * Coding challenges
 * Day 7 coding challenges


 * Resources
 * go here

Week 8: May 16
Day 8 plan


 * Agenda
 * Day 8 lecture - statistics with scipy


 * Coding challenges
 * Day 8 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: May 30

 * Assignments due
 * Final project presentation


 * 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
 * Final project report and code due by midnight on Wednesday, 6/8/2016