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Machine Learning/AI Series: Getting Started with Data Exploration using Python

New session times will be displayed below upon confirmation.

Most Technology Training classes will be delivered online until further notice.

Before each sesson, Tech Training will provide a Zoom link for live online classes, along with any required class materials.

 


This session is intended to help you get started with exploring and analyzing data prior to building Machine Learning models. You will have the opportunity to learn about popular tools used to perform such analysis.

Prerequisite:
Have a basic understanding of the Python language, Pandas library, and an understanding of how to use Jupyter Notebook.

Audience:
This session is designed for anyone who wants to start with machine learning and understand the tools and techniques involved in analyzing and exploring data.

Objectives
Use Pandas library to explore data and have an opportunity to practice with the following:

  • Reading data from various file formats such as Comma Separated Values (.csv), JavaScript object notation (.JSON)
  • Look for data values missing in the dataset
  • Understand the statistics in the dataset
  • Replace missing values in the dataset

Training material provided: Yes (Digital format)

Setup
Attendees must install Anaconda software (https://www.anaconda.com/) prior to the class and have a basic understanding of using Jupyter Notebook

Antony Ross

Antony originally attained a degree in psychology with an emphasis in sport psychology. He began working with athletes and eventually chose to pursue a graduate degree in exercise physiology. He conducted research in muscle physiology while teaching at USC and, subsequently, UCLA.

Custom training workshops are available for this program

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University IT Technology Training sessions are available to a wide range of participants, including Stanford University staff, faculty, students, and employees of Stanford Hospitals & Clinics, such as Stanford Health Care, Stanford Health Care Tri-Valley, Stanford Medicine Partners, and Stanford Medicine Children's Health.

Additionally, some of these programs are open to interested individuals not affiliated with Stanford, allowing for broader community engagement and learning opportunities.