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UID:20250506T154250EDT-35461SN8NG@132.216.98.100
DTSTAMP:20250506T194250Z
DESCRIPTION:Workshop Overview: In thisworkshop\, we will delve into the art
  of conducting Exploratory Data Analysis (EDA) on a given dataset. EDA enc
 ompasses a broad spectrum of critical data analysis components\, which inc
 lude\, but are not restricted to\, the following:\n\n\n	Data Preprocessing:
  This encompasses activities such as data cleaning\, summarization\, and w
 rangling\, ensuring that the dataset is in a usable and informative state.
 \n	Data Visualization: EDA entails univariate\, bivariate\, and multivariat
 e analyses\, employing various visualization techniques to unveil underlyi
 ng patterns and relationships within the data.\n	Hypothesis Formulation: ED
 A aids in the generation of hypotheses\, setting the stage for further tes
 ting and validation through statistical techniques.\n	Time Series Analysis:
  For datasets with temporal aspects\, EDA includes the examination of tren
 ds\, seasonality\, and patterns over time\, providing insights into data e
 volution.\n	Feature Selection: Identifying and selecting the most relevant 
 features is a crucial step in EDA\, as it can significantly impact the suc
 cess of subsequent analyses and modeling.\n\n\nBy the end of this workshop
 \, students will have a solid foundation in conducting EDA\, a vital skill
  in the realm of data analysis and decision-making.\n\nPrerequisites:\n\n-
  Introductory knowledge of Python\n\n-You need to bring your own laptop fo
 r this workshop. Install Anaconda on your computer. You can find installat
 ion instructions here. Please contact us (cdsi.science at mcgill.ca) if yo
 u are having trouble with installation.\n\nLocation: HYBRID. Online via Zo
 om\, or in-person at Burnside Hall room 1104 (11th floor).\n	Instructor: Ki
 won Lee\, Faculty Lecturer\, Department of Mathematics & Statistics\n\nReg
 istration: Register Here\n
DTSTART:20240318T140000Z
DTEND:20240318T160000Z
SUMMARY:Workshop: Exploratory Data Analysis in Python
URL:/cdsi/channels/event/workshop-exploratory-data-ana
 lysis-python-353555
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