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Machine Learning – Twitter Sentiment Analysis in Python Online Course

Machine Learning – Twitter Sentiment Analysis in Python Online Course


Course Description

Use Python & the Twitter API to Build Your Own Sentiment Analyzer.

Sentiment Analysis, or Opinion Mining, is a field of Neuro-linguistic Programming that deals with extracting subjective information, like positive/negative, like/dislike, and emotional reactions. In this “Twitter Sentiment Analysis in Python” online course, you’ll learn real examples of why Sentiment Analysis is important and how to approach specific problems using Sentiment Analysis. Supplemental Material included!

What Will I Learn?

  • Design and Implement a sentiment analysis measurement system in Python
  • Grasp the theory underlying sentiment analysis, and its relation to binary classification
  • Identify use-cases for sentiment analysis
  • Learn about Sentiment Lexicons, Regular Expressions & Twitter API

No prerequisites required, however knowledge of some undergraduate level mathematics would help, but is not mandatory. Working knowledge of Python would be helpful if you want to perform the coding exercise and understand the provided source code.

Who is the target audience?

  • Analytics professionals, modelers, big data professionals who haven’t had exposure to machine learning
  • Engineers who want to understand or learn machine learning and apply it to problems they are solving
  • Tech executives and investors who are interested in big data, machine learning or natural language processing
  • Product managers who want to have intelligent conversations with data scientists and engineers about machine learning


Length of Subscription: 12 Months Online On-Demand Access
Running Time: 3 hrs 30 min
Platform: Windows & MAC OS
Level: Beginner to Advanced
Project Files: Included

Learn anytime, anywhere, at home or on the go.

Stream your training via the internet, or download to your computer and supported mobile device, including iPad, iPhone, iPod Touch and most Android devices.

Course Outline

Chapter 01: What are You Feeling Like?

Lesson 01: Introduction: You, This Course & Us!

Lesson 02: Sentiment Analysis: What’s all the fuss about?

Lesson 03: Machine Learning Solutions for Sentiment Analysis: the devil is in the details

Lesson 04: Sentiment Lexicons (with an introduction to WordNet and SentiWordNet)

Lesson 05: Installing Python – Anaconda and Pip

Lesson 06: Back to Basics: Numpy in Python

Lesson 07: Back to Basics: Numpy & Scipy in Python

Lesson 08: Regular Expressions

Lesson 09: Regular Expressions in Python

Lesson 10: Put it to work: Twitter Sentiment Analysis

Lesson 11: Twitter Sentiment Analysis: Work the API

Lesson 12: Twitter Sentiment Analysis: Regular Expressions for Preprocessing

Lesson 13: Twitter Sentiment Analysis: Naive Bayes, SVM & SentiWordNet

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