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?
 * Command line cheat sheet — covers basics like  and much more.

Week 2: April 4
Day 2 plan


 * Agenda
 * We will review the programming concepts introduced last week as a group.
 * We will introduce some new programming concepts into the mix.
 * We will play a guessing game (click here to download the code)
 * We will use what we have learned so far to cheat at Scrabble.
 * We will introduce our first set of Coding Challenges.
 * We will take a sneak peak at what a good final project looks like.


 * Homework
 * Complete the second set of CodeAcademy lessons
 * Work on the Week 2 coding challenges


 * Resources
 * Python for Informatics: Chapter 2 Variables, expressions and statements and Chapter 3  Conditional execution
 * Python data types cheat sheet
 * Python loops cheat sheet
 * Working within loops
 * Wordplay handout
 * cdsw-au2015-lecture1-20151010.ogv -- 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
Day 3 plan


 * Agenda
 * We will review your feedback from last week
 * We will walk through the solutions to the code challenges from last week
 * We will introduce some new programming concepts
 * We will walk through an example of programming in a UX Research context
 * We will begin working on a series of exercises using the Baby Names dataset


 * Homework
 * Day 3 coding challenges


 * Resources
 * go here

Week 4: April 18
Day 4 plan


 * Agenda
 * Week 3 code challenges — We'll briefly walk through the concepts and solutions to the Week 3 coding challenges as a group.
 * Day 3 follow up — We will cover some important concepts that we didn't have a chance to cover in depth last week.
 * DS4UX_(Spring_2016)/Wikipedia Notifications survey — We will walk through a real life example that uses the concepts we've developed so far to answer research questions.
 * Reading and writing files — we will learn how to read and write basic datafiles with Python.
 * Burke-Gilman traffic counter — we will start working with a dataset of bike and pedestrian traffic on the Burke-Gilman trail.


 * Homework
 * Day 4 coding challenges (Required)


 * Resources
 * Two video lectures by Mako Hill, which covers most of the concepts from NEXT week's lecture (as well as some useful review):
 * cdsw-au2015-lecture2-20151024.ogv
 * cdsw-au2015-lecture3-20151107.ogv

Week 5: April 25
Day 5 plan


 * Assignments due
 * Final project idea
 * Day 4 coding challenge


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


 * Homework
 * Day 5 coding challenges (Required)


 * Resources
 * go here

Week 6: May 2
Day 6 plan


 * Assignments due
 * Day 5 coding challenge


 * Agenda
 * Day 6 lecture - querying databases


 * Homework
 * Day 6 coding challenges (Required)


 * Resources
 * go here

Week 7: May 9
Day 7 plan


 * Assignments due
 * Final project proposal
 * Week 6 coding challenge


 * 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: 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
 * 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