Merge branch 'master' of https://github.com/TZstatsADS/ADS_Teaching

README.md

@@ -1,27 +1,27 @@
 # Stat GU4243/GR5243 Applied Data Science
-### Spring 2021 - Teaching Materials ([Syllabus](/CourseInfo/G5243_ADS.md))
+### Fall 2021 - Teaching Materials ([Syllabus](/CourseInfo/G5243_ADS.md))
 
 ##### Shortcuts: [Project 1](#project-cycle-1-individual-r-notebook-for-exploratory-data-analysis) | [Project 2](#project-cycle-2-shiny-app-development) | [Project 3](#project-cycle-3-predictive-modeling) | [Project 4](#project-cycle-4-algorithm-implementation-and-evaluation)
 ----
 ### Project cycle 1: (Individual) R notebook for exploratory data analysis 
 
 ([starter codes](Projects_StarterCodes/Project1-RNotebook))
 
-#### Week 1 (Jan 13)
+#### Week 1 (Sep 15)
 
 + [Introduction to ADS](Tutorials/wk1-Intro.pdf)
 + [Project 1 description](Projects_StarterCodes/Project1-RNotebook/doc/Proj1_desc.md)
 + [Tutorial 1 R Notebook](https://htmlpreview.github.io/?https://github.com/TZstatsADS/ADS_Teaching/blob/master/Tutorials/wk1-RNotebook/wk1-rnotebook.html) + Example: [Repo](https://github.com/TZstatsADS/Fall2018-Proj1-wanghouyaoleyao) | [Knitted HTML R Notebook](http://tzstatsads.github.io/tutorials/proj1_jiaqianyu.html) | [Presentation](https://www.youtube.com/watch?v=tBIuh_tZ98Q&feature=youtu.be) + More Examples: [Repo1](https://github.com/TZstatsADS/Spring2020-Project1-petkunm)
 + [A tutorial on GitHub](Tutorials/wk1-GitHub_simplified)
 
-#### Week 2 (Jan 20)
+#### Week 2 (Sep 22)
 <!--
 + Recap on last week
 + [Overview of starter codes](Projects_StarterCodes/Project1-RNotebook)
 + Submission and presentation for project 1
 + Discussion and Q&A
 -->
-#### Week 3 (Jan 27)
+#### Week 3 (Sep 29)
 <!--
 + Project 1 presentations.
 -->
@@ -35,7 +35,7 @@
 <!--
 ([starter codes](Projects_StarterCodes/Project2-ShinyApp))
 -->
-#### Week 3 (Jan 27)
+#### Week 3 (Sep 29)
 <!--
 + [Project 2](Projects_StarterCodes/Project2-ShinyApp) starts.
   	+ Check Piazza for your project team and *GitHub join link*.
@@ -45,7 +45,7 @@
    		+ an example **toy** shiny app 
     	+ a short tutorial to get you started.
 -->
-#### Week 4 (Feb 3)
+#### Week 4 (Oct 6)
 <!--
 + [Spatial data visualization](Tutorials/wk4-DataVis.pdf)
 + Tutorial on project 2 - [Introduction to shiny app](http://tzstatsads.github.io/tutorials/wk3_Tutorial2.html) ([app](Projects_StarterCodes/Project2-ShinyApp/app/))
@@ -54,14 +54,14 @@
 + [A note on contribution](Projects_StarterCodes/Project2-ShinyApp/doc/a_note_on_contributions.md)
 + Discussion and Q&A
 -->
-#### Week 5 (Feb 10)
+#### Week 5 (Oct 13)
 <!--
 + [Tutorial on SQL in R](https://htmlpreview.github.io/?https://github.com/TZstatsADS/ADS_Teaching/blob/master/Tutorials/wk5-SQL%2BGCP/sql.html)([zipped folder](https://github.com/TZstatsADS/ADS_Teaching/blob/master/Tutorials/wk5-sql.zip))
 + [Tutorial on RShiny Deployment in GCP](https://htmlpreview.github.io/?https://github.com/TZstatsADS/ADS_Teaching/blob/master/Tutorials/wk5-SQL%2BGCP/Rshiny_GCP.html)
 + [Tutorial on giving presentations](Tutorials/wk5-MakingPresentation.pdf)
 + Brainstorm or Discussion on project 2
 -->
-#### Week 6 (Feb 17)
+#### Week 6 (Oct 20)
 <!--
 + Project 2 presentations
 -->
@@ -75,7 +75,7 @@
 <!--
 ([starter codes](Projects_StarterCodes/Project3-ImbalancedClassification))
 -->
-#### Week 6 (Feb 17)
+#### Week 6 (Oct 20)
 <!--
 + [Project 3](Projects_StarterCodes/Project3-ImbalancedClassification/doc/project3_desc.md) starts.
   + Check Piazza for your project team and GitHub join link.
@@ -85,7 +85,7 @@
     + an example `main.rmd` that provides an example structure for this project.  [Example `main.Rmd`](Projects_StarterCodes/Project3-ImbalancedClassification/doc/main.Rmd)
 -->
 
-#### Week 7 (Feb 24)
+#### Week 7 (Oct 27)
 <!--
 + Recap on [project 3 requirements](Projects_StarterCodes/Project3-ImbalancedClassification/doc/project3_desc.md) and [starter codes](Projects_StarterCodes/Project3-ImbalancedClassification/). 
 + Tutorials + Q&A
@@ -95,15 +95,14 @@
 	+ [Overview on Imbalanced Classification](Tutorials/wk7-Imbalanced_Classification_Overview.pdf)
 -->	
 
-#### Spring Break
 
-#### Week 8 (Mar 10) 
+#### Week 8 (Nov 3) 
 <!--
 + [Overview on predictive modeling](Tutorials/wk8-TutorialModelSelection.pdf)
 + Project submission checklist (on piazza)
 + Discussion
 -->
-#### Week 9 (Mar 17) 
+#### Week 9 (Nov 10) 
 <!--
 + Project 3 submission and presentations
 -->
@@ -117,43 +116,42 @@
 <!--
 ([starter codes](Projects_StarterCodes/Project4-CausalInference))
 -->
-#### Week 9 (Mar 17) 
+#### Week 9 (Nov 10) 
 <!--
 + Introduction to [Project 4](Projects_StarterCodes/Project4-CausalInference/doc/project4_desc.md)
 -->
-#### Weeks 10 (Mar 24)
+#### Weeks 10 (Nov 17)
 <!--
 + Recap on project 4 requirements.
 + Overview of Causal Inference
 + [Overview of the Methods from the reference papers](Tutorials/wk10-overview-casual-inference-methods.pdf).
 + Method assignment on Piazza
 -->
-#### Weeks 11 (Mar 31)
-<!--
-+ Q&A
-+ Team Meeting
--->
 
-#### Weeks 12 (Apr 7)
+#### Thanksgiving Break
+
+#### Weeks 11 (Dec 1)
 <!--
 + Project 4 presentations
+-->
+
 
 <!--
 [Finished student projects](https://github.com/TZstatsADS?utf8=✓&q=Spring2021-project4&type=&language=)
 -->
 ----
 ### Project cycle 5: 
 
-#### Weeks 12 (Apr 7)
+#### Weeks 11 (Dec 1)
 <!--
 + Project 5 discussions
 + Project 3 Summary on Piazza
 -->
-#### Week 13 (Apr 14)
+#### Week 12 (Dec 8)
 <!--
 + Project 5 presentations
 -->
 <!--
 [Finished student projects](https://github.com/TZstatsADS?utf8=✓&q=Spring2021-project5&type=&language=)
 -->
-##### Shortcuts: [Project 1](#project-cycle-1-individual-r-notebook-for-exploratory-data-analysis) | [Project 2](#project-cycle-2-shiny-app-development) | [Project 3](#project-cycle-3-predictive-modeling) | [Project 4](#project-cycle-4-algorithm-implementation-and-evaluation)
+##### Shortcuts: [Project 1](#project-cycle-1-individual-r-notebook-for-exploratory-data-analysis) | [Project 2](#project-cycle-2-shiny-app-development) | [Project 3](#project-cycle-3-predictive-modeling) | [Project 4](#project-cycle-4-algorithm-implementation-and-evaluation)