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Basic Training: Intro to Python Skills for AI

Learn web scraping, data cleaning, and other AI skills to build a Markov Bot of your favorite celebrity.

Workshop Overview

  • Beginner
  • 1.5h - 2h
  • Python, Artificial Intelligence, Data Cleaning

Learning Objectives

  • Scrape data from Twitter
  • Clean data from Twitter
  • Use the Markovify library to create a Markov chain bot of your favorite celebrity, based on their Twitter

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Get in touch if you have any questions regarding this workshop or MLH Localhost.

About these Workshops

Basic TrAIning is a series of three workshops developed in partnership with Capital One to teach Python skills for Artificial Intelligence use cases.

Part I: Web Scraping

In the first workshop in this series, participants will learn how to scrape the web for data using Python. They will scrape Tweets from their favorite celebrity or other public figure’s Twitter. Then, they’ll edit a chat app that responds to messages with Tweets.

Part II: Data Cleaning

In the second workshop in this series, participants will use data cleaning techniques to improve the data set they retrieved from Twitter using regular expressions.

Part III: Use Your Data in a Bot!

In the third workshop in this series, participants will feed their data into a Markov chain bot. They will compare the quality of responses from data scraped from Twitter (a small data set) to data retrieved using the Twitter API (a larger data set). At the end of the series, participants will have a fully functional, deployed Markov chain bot of the celebrity of their choice!

Requirements / Prerequisites

No special software is necessary. Computers that can connect to the internet are all that’s required!

System Requirements:


When you host an MLH Localhost workshop, we’ll send you everything you need to run it. Here’s what we’ll send you:

The List:

Resources & Downloads

Organizers can familiarize themselves with the following resources.

Learn Python

Learn Python: Codecademy

Get Started

The hackers are waiting for you.

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