ABCDEFGHIJKLMNOPQRSTUVWXY
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Class
Meeting
DateBefore ClassIn Class
2
11/19/2016Course introduction and "the value of data"
intro to tools: pandas, numpy, ipython notebook
3
21/22/2016Finish setting up your environment
Do the "Value of Data" assignment
Read ThinkStats Chapter 1		Value of Data assignment discussion
Data cleaning and basic data visualization / exploration
4
31/26/2016Read ThinkStats Chapter 2 and 7
Finish "Data Exploration" part of the warmup project.		Sharing titanic explorations
Predictive modeling workflow
Intro to ML using scikit learn
5
41/29/2016Finish "Model Iteration 1" part of warmup project
ThinkStats Ch. 10.1-10.5 and 11		Machine Learning from the bottom up
6
52/2/2016Finish Warmup ProjectSharing lessons learned, best practices, strategies, etc.
Project 1 Kickoff
7
62/5/2016Pick dataset and partner for "Choose your own Adventure" (CYOA)
Write project proposal + learning goals
Finish "bottom up machine learning" (optional)		Tuning machine learning algorithms
8
72/9/2016Explore your new dataset, and come to class ready to discuss
and brainstorm with peers.		Decision trees and random forests
Brainstorming / debrief on data exploration and visualization
9
82/12/2016Complete preclass exercise on TF-IDF
Continue working on CYOA		Working with text data
10
92/16/2016Test at least two models, and come to class ready to discuss
and brainstorm with peers.		Project work day
11
102/19/2016Interpreting Log Loss, Visualizing Models
12
112/23/2016Finish CYOA projectCYOA debrief, Change the World (CTW) project launch
13
122/26/2016Do CTW proposalCreating effective data visualizations
14
133/1/2016Read ThinkStats Chapter 3
15
143/4/2016Read ThinkStats Chapter 4
Do CTW Mid-project checkin
16
153/8/2016Keep working on CTW
17
163/11/2016Finish CTW Final Output and Reflection
18
Spring Break
19
173/22/2016Project ideation and team formation
20
183/25/2016Do first part of ThinkStats Chapter 9 reading
Prepare project proposal		Debrief on first part of hypothesis testing
Discuss project proposals
21
193/29/2016Do second part of ThinkStats Chapter 9 readingHypothesis testing
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204/1/2016Power analysis
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214/5/2016Project Story 1 DueDimensionality Reduction
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224/8/2016Clustering
25
234/12/2016Causal Inference and Experimental Design
26
244/15/2016
27
254/22/2016Project Story 2 Due
28
264/26/2016
29
Fin5/3/2016Final event will be 12pm-3pm in AC326
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