Professional CertificateIntermediate

Natural Language Processing Specialization

Instructors: Younes Bensouda Mourri, Łukasz Kaiser

DeepLearning.AI logo

Natural Language Processing Specialization

Intermediate

Instructors: Younes Bensouda Mourri, Łukasz Kaiser

DeepLearning.AI

DeepLearning.AI

What you'll learn

  • Use logistic regression, naïve Bayes, and word vectors to implement sentiment analysis, complete analogies, translate words, and use locality-sensitive hashing to approximate nearest neighbors.

  • Use dynamic programming, hidden Markov models, and word embeddings to autocorrect misspelled words, autocomplete partial sentences, and identify part-of-speech tags for words.

  • Use dense and recurrent neural networks, LSTMs, GRUs, and Siamese networks in TensorFlow to perform advanced sentiment analysis, text generation, named entity recognition, and to identify duplicate questions.

  • Use encoder-decoder, causal, and self-attention to perform advanced machine translation of complete sentences, text summarization, and question-answering. Learn models like T5, BERT, and more with Hugging Face Transformers!

Skills you will gain

Sentiment Analysis
Transformers
Attention Models
Machine Translation
Word2vec
Word Embeddings
Locality-Sensitive Hashing
Vector Space Models
Parts-of-Speech Tagging
N-gram Language Models
Autocorrect
Sentiment with Neural Networks
Siamese Networks
Natural Language Generation
Named Entity Recognition (NER)
Neural Machine Translation
T5 + BERT Models

Natural language processing is a subfield of linguistics, computer science, and artificial intelligence that uses algorithms to interpret and manipulate human language.

In the Natural Language Processing (NLP) Specialization, you will learn how to design NLP applications that perform question-answering and sentiment analysis, create tools to translate languages, and summarize text. These and other NLP applications will be at the forefront of the coming transformation to an AI-powered future.

NLP is one of the most broadly applied areas of machine learning and is critical in effectively analyzing massive quantities of unstructured, text-heavy data. As AI continues to expand, so will the demand for professionals skilled at building models that analyze speech and language, uncover contextual patterns, and produce insights from text and audio.

Instructors

Younes Bensouda Mourri

Younes Bensouda Mourri

Instructor of AI, Stanford University
Łukasz Kaiser

Łukasz Kaiser

Staff Research Scientist, Google Brain; Chargé de Recherche, CNRS

Course Slides

You can download the annotated version of the course slides below.

*Note: The slides might not reflect the latest course video slides. Please refer to the lecture videos for the most up-to-date information. We encourage you to make your own notes.

Frequently Asked Questions

Natural Language Processing Specialization

Intermediate

Instructors: Younes Bensouda Mourri, Łukasz Kaiser

DeepLearning.AI

DeepLearning.AI

Want to learn more about Generative AI?

Keep learning with updates on curated AI news, courses, and events, as well as Andrew's thoughts from DeepLearning.AI!

Enroll for Free

Also available on Coursera