PROF. LINDA ZHAO PRESENTS

Data Science Live

5-7PM, Monday, April 29, 2019
SHDH 351

Organizing Committee

Jeffrey Junhui Cai, Carol Chen, Arun Kumar Kuchibhotla, Michelle Lok, and Linda Zhao

Acknowledgement

Teaching Assistants:
Arun Kumar Kuchibhotla (Head TA), Harrison Beard, Ryan Galea,
Jason Liebmann, Alex Zhao and Andres Carrillo Pearea

Supported by WACI (Wharton Customer Analytics Initiative)

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Intro

"In the past, one could get by on intuition and experience. Times have changed. Today the name of the game is data" writes Steven D. Levitt. Data mining and statistical analysis have suddenly revolutionized many real life aspects like politics, housing, health analytics, criminal justice and sports...

By using data preparation, statistics, predictive modeling and machine learning, data mining tries to resolve many issues within individual sectors and the economy at large.

STAT 471/571/701 (Modern Data Mining) created and taught by Prof. Linda Zhao, a faculty in the statistics department provides a thorough treatment of data mining techniques such as data cleaning, exploratory data analysis, predictive modeling and machine learning. The course is designed to provide an overview of these techniques with prime focus on analyzing real datasets. The students are self-selective in the way they are strong analytically and are mostly enthusiastic with data science. It is well balanced mixture of upper level undergraduates, Wharton MBAs, MS and Ph.D’s campus wise. The students at the end of the semester are required to conduct studies of their choice focusing on tackling real world problems using the techniques learnt.

We wholeheartedly thank our TA group: Arun Kumar Kuchibhotla (Head TA), Harrison Beard, Ryan Galea, Jason Liebmann, Alex Zhao and Andres Carrillo Pearea. We could not have made it without their support. We also proudly acknowledge the support of WACI (Wharton Customer Analytics Initiative).

Organizing Committee: Jeffrey Junhui Cai, Carol Chen, Arun Kumar Kuchibhotla, Michelle Lok, and Linda Zhao.

Schedule