Week	Class	Date	Topic	Due Dates
Week 1	1	Jan-23	Overview of Computational and Data Sciences
	2	Jan-25	The data scientist’s toolbox I	Twitter Study Article
Week 2	3	Jan-30	The data scientist’s toolbox II	Try R Tutorial
	4	Feb-01	The data scientist’s toolbox III	Reading 1
Week 3	5	Feb-06	Introduction to data/Data visualization I	Reading 2 RMarkdown mini-assignment
	6	Feb-08	Data visualization II	Reading 3
		Feb-09		Visualization mini-assignment
Week 4	7	Feb-13	Data visualization III	Reading 4
	8	Feb-15	Data wrangling I ,
Week 5	9	Feb-20	Data wrangling II ,	Reading 5
	10	Feb-22	Data wrangling III	Reading 6
		Feb-23		Homework 1
Week 6	11	Feb-27	Data wrangling IV ,	Reading 7
	12	Mar-01	Midterm project brainstorming session	Reading 8
Week 7	13	Mar-06	Exploratory data analysis I
	14	Mar-08	Exploratory data analysis II
		Mar-09		Homework 2
		Mar-13	Spring Break (no class)
		Mar-15	Spring Break (no class)
Week 8	15	Mar-20	Midterm project group conferences
	16	Mar-22	Introduction to Web Scraping I
Week 9	17	Mar-27	Midterm project presentations I/Web scraping group activity	Midterm Project
	18	Mar-29	Midterm project presentations II/Web scraping group activity
Week 10	19	Apr-03	Introduction to Web Scraping II/Principles of Data Collection
	20	Apr-05	Statistical distributions I	Reading 9
Week 11	21	Apr-10	Statistical distributions II	Reading 10
	22	Apr-12	Inference and simulations I	Reading 11
		Apr-13		Reading 12
		Apr-16		Homework 3
Week 12	23	Apr-17	Inference and simulations II ,	Reading 13
	24	Apr-19	Inference and simulations III	Reading 14
Week 13	25	Apr-24	Inference and simulations IV/Modeling I	Reading 15
	26	Apr-26	Modeling II	Reading 16
		Apr-27		Homework 4
Week 14	27	May-01	Modeling III
	28	May-03	Modeling IV ,
		May-04		Homework 5
		May-08	Reading Day
		May-11		Final Portfolio
		May-15	Final Interview Time: 1:30pm – 4:15pm