Natural Language Processing in Python

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Learn Path Description

The majority of data is unstructured. This includes information recorded in books, online articles, and audio files. In this track, you’ll gain the core Natural Language Processing (NLP) skills you need to convert that data into valuable insights—from learning how to automatically transcribe TED talks through to identifying whether a movie review is positive or negative. Along the way, you’ll be introduced to popular NLP Python libraries, including NLTK, scikit-learn, spaCy, and SpeechRecognition. You’ll start this track by learning how to identify words and extract topics in text before building your very own chatbot that transforms human language into actionable instructions. By the end of the track, you'll be ready to transcribe audio files and understand how to extract insights from real-world sources, including Wikipedia articles, online review sites, and data from a flight booking system. 

Skills You Will Gain

Courses In This Learning Path

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Total Duration

4 hours

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Level

Beginner

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Learn Type

Certifications

Introduction to Natural Language Processing in Python

This course will cover the basics of natural-language processing (NLP). It will show you how to extract topics and separate words from text. Learn how to create fake news classifications. You'll also learn about basic libraries such as NLTK and libraries that use deep learning for NLP problems. This course will assist you in your Python learning.

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Total Duration

4 hours

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Level

Intermediate

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Learn Type

Certifications

Sentiment Analysis in Python

Are you a person who leaves reviews to let others know what you think about a product? Are you able to read product reviews online before purchasing a product? These reviews are valuable not only for you but also for businesses. This course will help you interpret different documents' sentiments. You will use real-world datasets such as product reviews, tweets, movie trailers, and twitter. Additionally, you will use Python nltk and scikit-learn as well as other Python tools. This course will prepare you to do an end-to-end sentiment analysis task, based on the tweets of US airline passengers.

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Total Duration

4 hours

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Level

Intermediate

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Learn Type

Certifications

Building Chatbots in Python

Next big platforms will be messaging and voice-controlled devices. Conversational computing is a key component in creating immersive virtual and augmented reality experiences. This course will show you how to build these apps. These types of programs are not easy to build. How can I convert human languages into machine-readable instructions? This course will show you how to use rule-based and machine learning systems. Some chat systems can be useful while others can be fun. Each will be combined to create a friendly and helpful chatbot. You'll also learn how you can link your chatbot to Facebook Messenger after the course is completed.

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Total Duration

5 hours

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Level

Advanced

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Learn Type

Certifications

Advanced NLP with spaCy

If you deal with text frequently, it is worth learning more. What does it all mean? What is the meaning of the context? What's the purpose of these words What products or companies are being mentioned? What texts are similar to each other? This course will show you how to use spaCy, an industry-standard library that allows for NLP in Python. This course will teach you how to build advanced natural language understanding systems that use both rule-based and machine approaches.

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Total Duration

4 hours

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Level

Intermediate

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Learn Type

Certifications

Spoken Language Processing in Python

Before we can read, it is important to learn how speak before we can read. In today's digital age, speech is still the primary mode of communication. Spoken Language Processing allows you to load, convert, and transcribe audio files in Python. This article will show you how Python handles raw sound. Next, we'll show you how Python handles raw audio.

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Total Duration

4 hours

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Level

Intermediate

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Learn Type

Certifications

Feature Engineering for NLP in Python

This course will show you how to extract useful information from text and transform it into a format suitable for ML modeling. Named entity recognition and POS tagging will be covered. You will also learn how to compare documents. Additionally, you will learn how to predict movie reviews as well as create Ted Talk recommendations. Learn how to extract key features from any text, and how to solve the most challenging problems in data science.

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