Unlock the power of natural language processing and leverage machine learning algorithms in Python to create valuable NLP solutions.
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.
As we discuss deep learning applications for natural language processing, you’ll see how exciting models like ChatGPT operate behind the scenes. By the end of this Intro to NLP for AI course, you’ll have a solid foundation for working with text data and implementing your own NLP solutions.
Student feedback
“In this course, we will be delving into the exciting field of NLP and looking at techniques that enable computers to understand, generate, and classify human language.”
Worked at BBC
Intro to NLP for AI
with Lauren Newbould
