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.
• Lecture: Why Programming and Data Science — 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 Chapter 1

Week 2: April 4

Day 2 plan

Class schedule

• Lecture — working with data

• flow control
• modules
• user-defined functions

Exercises

• Reading data from a flat file (interactively & from a script)

Homework

• Python quiz #2
• Coding challenges
• Set up a Wikimedia account

Resources

• followup

Week 3: April 11

Day 3 plan

Class schedule

• Day 3 lecture - working with web data 1 (APIs)
• programming concepts 3

• APIs
• JSON

Exercises

• Practice in API sandboxes
• Requesting data from an API using Python

Homework

• Python quiz #3
• Day 3 coding challenges

Resources

• go here

Week 4: April 18

Day 4 plan

Class schedule

• 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

• Python quiz #4
• Day 4 coding challenges

Resources

• go here

Week 5: April 25

Day 5 plan

Assignments due

• Final project idea

Class schedule

• 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

• Python quiz #5
• Day 5 coding challenges

Resources

• go here

Week 6: May 2

Day 6 plan

Class schedule

• Day 6 lecture - working with text
• Jupyter notebooks 2

• 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

• Day 6 coding challenges

Resources

• go here

Week 7: May 9

Day 7 plan

Assignments due

• DS4UX_(Spring_2016)#Final_Project_Proposal

Class schedule

• 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

• Day 7 coding challenges

Resources

• go here

Week 8: May 16

Day 8 plan

Class schedule

• Day 8 lecture - research study design

Exercises

• Replicate Teahouse invite A/B test

Coding challenges

• Day 8 coding challenges

Resources

• go here

Week 9: May 23

Day 9 plan

Class schedule

• 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

• Final project presentation

Class schedule

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

Week 11: June 6

Assignments due

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

Class schedule

• Finals week - No class!