Cornell Data Science Training Program

Gates G01 · 5:30 - 6:30 PM Wednesdays

First Lecture on September 6th


Instructor

Dae Won Kim (dk444)

Jared Junyoung Lim (jl3248)

Teaching Associates

Piazza

Abby Beeler (arb379)

Kexin Zheng (kz73)

Shubhom Bhattacharya (sb2287)

Office Hour

Ann Zhang (az275)

Cameron Ibrahim (cai29)

Ryan Kannanaikal (rk635)

Office Hour Schedule

Cameron Ibrahim Ann Zhang Ryan Kannanaikal Dae Won Kim
Day Monday Thursday Saturday Sunday
Time 6 - 7 PM 3 - 4 PM 1 - 2 PM 12 - 1 PM
Location Gates 122 Gates 122 Gates 122 Gates 122

Fall 2017 Schedule

Date Lecture Slides Recordings Lecture Notes Assignment
09/01/17 - - LECTURE 0: INTRO -
09/06/17 Lecture 1: Introduction to Data Science Lecture 1 Recording LECTURE 1: NUMPY Take Home Quiz 1
09/13/17 Lecture 2: Data Manipulation Lecture 2 Recording LECTURE 2: PANDAS
LECTURE 2: DEMO
Take Home Quiz 2
09/20/17 Lecture 3: Data Visualization Lecture 3 Recording LECTURE 3: VISUAL Project Part A
09/27/17 Lecture 4: Intro to Machine Learning Lecture 4 Recording LECTURE 4: SUPER Project Part A
10/04/17 Lecture 5: Intro to Classification Lecture 5 Recording LECTURE 5: CLASS
Project Part B
10/11/17 Lecture 6: SVM Lecture 6 Recording LECTURE 6: SVM
LECTURE 6: DEMO
Project Part B
10/18/17 Lecture 7: Logistic Regression and Decision Trees Lecture 7 Recording LECTURE 7: LOGIT
LECTURE 7: DEMO
Project Part B
10/25/17 Lecture 8: Unsupervised Learning Lecture 8 Recording LECTURE 8: UNSUP Project Part C
11/01/17 Lecture 9: Ensemble Learning Lecture 9 Recording LECTURE 9: ENSEM
LECTURE 9: BAG
Project Part C
11/08/17 Lecture 10: Model Optimization Lecture 10 Recording LECTURE 10/11: MODEL Project Part D
11/15/17 Lecture 11: Cross Validation Lecture 11 Recording LECTURE 10/11: MODEL Project Part E

Coming Soon!


Spring 2017 Archive

Date Lecture Slides Recordings Lecture Notes Assignment
02/15/17 Lecture 1: Introduction to R Lecture 1: Introduction to R Lecture 1: Introduction to R Assignment 1
02/22/17 Lecture 2: Data Manipulation Lecture 2: Data Manipulation Lecture 2: Data Manipulation Assignment 2
03/01/17 Lecture 3: Data Visualization Lecture 3: Data Visualization Lecture 3: Data Visualization Assignment 3
03/08/17 Lecture 4: Linear Regression Lecture 4: Linear Regression Lecture 4: Linear Regression Project 1
03/22/17 Lecture 5: Logistic Regression Lecture 5: Logistic Regression Lecture 5: Logistic Regression Project 1
03/29/17 Lecture 6: Classification Lecture 6: Classification Lecture 6: Classification Project 1
04/12/17 Lecture 7: Unsupervised Learning Lecture 7: Unsupervised Learning Lecture 7: Unsupervised Learning Project 1
04/19/17 Lecture 8: Model Selection and Optimization Lecture 8: Model Selection and Optimization Lecture 8: Model Selection and Optimization Assignment 4
04/26/17 Lecture 9: Meta-Learning Lecture 9: Meta-Learning Lecture 9: Meta-Learning Project 2
05/03/17 Lecture 10: Text Analysis Lecture 10: Text Analysis Lecture 10: Text Analysis Project 2
05/10/17 Lecture 11: Big Data Tools Lecture 11: Big Data Tools No notes! Project 2