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Microcredential

Natural Language Processing

IBM and Amazon via Udacity Nanodegree

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Overview

Over the course of this program, you’ll become an expert in the main components of Natural Language Processing, including speech recognition, sentiment analysis, and machine translation. You’ll learn to code probabilistic and deep learning models, train them on real data, and build a career-ready portfolio as an NLP expert!
Learn the skills to get computers to understand, process, and respond to human language. Build models on real data, and get hands-on experience with sentiment analysis, machine translation, and more.

Syllabus

Prerequisite Knowledge

This program requires experience with Python, statistics, machine learning, and deep learning.See detailed requirements.

  • Introduction to Natural Language Processing

    Learn text processing fundamentals, including stemming and lemmatization. Explore machine learning methods in sentiment analysis. Build a speech tagging model.

    Part of Speech Tagging
  • Computing with Natural Language

    Learn advanced techniques like word embeddings, deep learning attention, and more. Build a machine translation model using recurrent neural network architectures.

    Machine Translation
  • Communicating with Natural Language

    Learn voice user interface techniques that turn speech into text and vice versa. Build a speech recognition model using deep neural networks.

    Speech Recognizer

Taught by

Luis Serrano, Jay Alammar, Arpan Chakraborty, Dana Sheahen, Daniel C., Mansa kaur k., Shukhrat K., Ammar A., Philippe Claude Alain R. and Dapeng L.

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