5.00
(3 Ratings)

Intro to NLP for AI

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About Course

Natural language processing is an exciting and rapidly evolving data science field that fundamentally impacts how we interact with technology. In this Intro to NLP for AI course, you’ll learn to unlock the power of natural language processing and be equipped with the knowledge and skills to start working on your own NLP projects. You’ll explore essential topics for working with text data via video lessons and practical coding exercises. Whether you want to create custom text classifiers, analyze sentiment, or explore concealed topics, you’ll learn how NLP works and obtain the tools and concepts necessary to tackle these challenges. We’ll utilize algorithms like Latent Dirichlet Allocation, Transformer models, Logistic Regression, Naive Bayes, and Linear SVM, along with such techniques as part-of-speech (POS) tagging and Named Entity Recognition (NER). You won’t need prior natural language processing training to get started—just basic Python skills and familiarity with machine learning. This introduction to NLP guides you step-by-step through the entire process of completing a project. We’ll cover models and analysis and the fundamentals, such as processing and cleaning text data and how to get data in the correct format for NLP with machine learning.

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What Will You Learn?

  • Acquire a solid foundation in handling text data and learn to implement your own NLP solutions
  • Master essential text preprocessing techniques to get your data NLP-ready
  • Gain a deep understanding of how exciting models like ChatGPT operate behind the scenes
  • Learn how to create custom text classifiers, perform sentiment analysis, and uncover hidden topics from text data
  • Be able to vectorize and prepare text data for machine learning modeling
  • Improve your career prospects by mastering NLP, a highly sought-after technical skill that is especially relevant in the current AI-driven tech environment

Course Content

1. Introduction

  • 1.1 Introduction to the course
    02:39
  • 1.2 Course Materials and Notebooks
  • 1.3 Introduction to NLP
    01:37
  • 1.4 NLP in everyday life
    01:15
  • Exercise
  • 1.5 Supervised vs Unsupervised NLP
    01:46

2. Text Preprocessing

3. Identifying Parts of Speech and Named Entities

4. Sentiment Analysis

5. Vectorizing Text

6. Topic Modelling

7. Builing your own text classifier

8. Case Study Categorizing Fake News

9. The Future of NLP

Final Project

Earn a certificate

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Student Ratings & Reviews

5.0
Total 3 Ratings
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1
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10 months ago
goood
1 year ago
Good course.
Great course!

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