FeaturedUdemy
Sentiment Analysis in Python
4.8(445)23k studentsINTERMEDIATEEnglish
Korshub's take
Course Overview
The Sentiment Analysis in Python course covers complete text processing pipelines to extract emotional tone from unstructured text. Using Python libraries nltk and scikit-learn, you will process product reviews, movie reviews, and tweets, culminating in an end-to-end sentiment classification project analyzing US airline passenger tweets.
Who Is This Course For?
Intermediate Python developers, data analysts, and NLP practitioners interested in text classification, opinion mining, and natural language processing.
Key Takeaways
- Clean and preprocess raw text data for sentiment analysis in Python.
- Apply lexicon-based tools and feature extraction using nltk and scikit-learn.
- Train machine learning classification models on movie reviews and product feedback.
- Build an end-to-end sentiment analysis project evaluating US airline customer tweets.
About this course
Have you left a review to express how you feel about a product or a service? And do you have a habit of checking a product’s reviews online before you buy it? This kind of information is valuable not only for you but also for companies. In this course, you will learn how to make sense of the sentiment expressed in various documents. You will use real-world datasets featuring tweets, movie and product reviews, and use Python’s nltk and scikit-learn packages. By the end of the course, you will be able to carry an end-to-end sentiment analysis task based on how US airline passengers expressed their feelings on Twitter.
Price
Free
This course is free to enrol.
Advertisement