Sentiment Analysis in Python
Sentiment Analysis in Python is a great way to learn the fundamentals of sentiment analysis. With real-world datasets such as tweets, movie reviews, and product ratings, you can explore the sentiment of movie reviews and use Python's nltk and scikit-learn packages to complete a sentiment analysis task from start to finish. Learn how US airline passengers expressed their feelings on Twitter and gain the skills to complete a sentiment analysis task. ▼
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Course Feature
Cost:
Free Trial
Provider:
Datacamp
Certificate:
No Information
Language:
English
Course Overview
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Updated in [June 30th, 2023]
This course provides an overview of sentiment analysis in Python. Students will learn the fundamental structure of a sentiment analysis problem and begin exploring the sentiment of movie reviews. They will use real-world datasets such as tweets, movie reviews, and product ratings, as well as Python's nltk and scikit-learn packages. By the end of the course, students will be able to complete a sentiment analysis task from start to finish based on how US airline passengers expressed their feelings on Twitter.
[Applications]
After completing this course, students should be able to apply sentiment analysis to real-world datasets. They should be able to use Python's nltk and scikit-learn packages to analyze the sentiment of movie reviews, tweets, and product ratings. Furthermore, students should be able to complete a sentiment analysis task from start to finish based on how US airline passengers expressed their feelings on Twitter.
[Career Path]
The career path recommended to learners of this course is a Sentiment Analysis Engineer. A Sentiment Analysis Engineer is responsible for developing and deploying sentiment analysis models to analyze customer feedback, product reviews, and other text-based data. They must be able to use natural language processing (NLP) techniques to extract sentiment from text, as well as machine learning algorithms to build and evaluate sentiment analysis models. They must also be able to interpret the results of their models and communicate them to stakeholders.
The development trend for sentiment analysis engineers is to use more advanced NLP techniques and machine learning algorithms to build more accurate and robust sentiment analysis models. Additionally, sentiment analysis engineers must be able to use more sophisticated data sources, such as social media posts, to gain deeper insights into customer sentiment. Finally, sentiment analysis engineers must be able to use their models to provide actionable insights to stakeholders, such as product teams and marketing teams.
[Education Path]
The recommended educational path for learners interested in sentiment analysis in Python is to pursue a degree in Data Science. Data Science is a field that combines mathematics, statistics, computer science, and domain expertise to analyze and interpret data. It involves the use of algorithms, machine learning, and natural language processing to extract insights from data.
Data Science degrees typically include courses in mathematics, statistics, computer science, and domain-specific topics such as natural language processing. Students will learn how to use Python and its libraries such as nltk and scikit-learn to analyze and interpret data. They will also learn how to apply sentiment analysis techniques to real-world datasets such as tweets, movie reviews, and product ratings.
The development trend of Data Science degrees is to focus on the application of data science techniques to solve real-world problems. This includes the use of machine learning, natural language processing, and other advanced techniques to extract insights from data. Data Science degrees are also becoming more specialized, with courses focusing on specific topics such as sentiment analysis, predictive analytics, and data visualization.
Course Syllabus
Sentiment Analysis Nuts and Bolts
Numeric Features from Reviews
More on Numeric Vectors: Transforming Tweets
Let's Predict the Sentiment
Course Provider
Provider Datacamp's Stats at AZClass
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