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Offered By: IBMSkillsNetwork

Youtube Sentiment Analysis: Jake Paul vs. Mike Tyson Trailer

Learn sentiment analysis with Python and data visualization techniques to evaluate YouTube comments on the Jake Paul vs. Mike Tyson trailer. This hands-on project guides you through data processing methods to classify sentiments and extract actionable insights using libraries like pandas, numpy, and nltk. Ideal for beginners in data science or marketing professionals, complete this engaging introduction to sentiment analysis in just 30 minutes and enhance your analytical skill set.

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Guided Project

Data Visualization

317 Enrolled
4.5
(61 Reviews)

At a Glance

Learn sentiment analysis with Python and data visualization techniques to evaluate YouTube comments on the Jake Paul vs. Mike Tyson trailer. This hands-on project guides you through data processing methods to classify sentiments and extract actionable insights using libraries like pandas, numpy, and nltk. Ideal for beginners in data science or marketing professionals, complete this engaging introduction to sentiment analysis in just 30 minutes and enhance your analytical skill set.

Project Overview

Explore text sentiment analysis with python and unlock valuable insights from text data! This guided project focuses on evaluating sentiments in YouTube comments related to the Jake Paul vs. Mike Tyson trailer, using powerful Python libraries such as pandas, numpy, and nltk. Gain hands-on experience with essential data processing techniques to classify sentiments and extract actionable insights from textual data. Designed for beginners in data science and marketing professionals seeking to enhance analytical capabilities, this project equips you with valuable skills in just 30 minutes.



Learning Objectives

Upon completion of this project, you will be proficient in:
- Grasping the fundamental concepts of sentiment analysis and its practical applications.
- Employing Python libraries to effectively process text data for sentiment evaluation.
- Deriving significant insights from sentiment data to support decision-making across various scenarios.

Prerequisites

To complete this project successfully, ensure you have:
- A current version of a compatible web browser (Chrome, Edge, Firefox, Internet Explorer, or Safari) for optimal platform performance.


From emails and tweets to online survey responses, chats with customer service representatives and reviews, the sources available to gauge customer sentiment are seemingly endless. Sentiment analysis systems help companies better understand their customers, deliver stronger customer experiences and improve their brand reputation.

Estimated Effort

30 Minutes

Level

Beginner

Skills You Will Learn

Data Analysis, Data Visualization, Numpy, Pandas, Python

Language

English

Course Code

GPXX04JHEN

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