Natural Language Processing


Natural Language Processing

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  • Study Hours

    Study Hours

    150 Hours

  • Total Fee

    Total Fee


  • Delivery



  • Modality


    Self Paced

Programme Overview

In this module, you will learn about the modern natural language process (NLP) and how it addresses differences in speech recognition and other patterns. You will explore statistical methods and deep learning concepts to understand syntactic and semantic analysis of text, sentiment analysis, question answering and translation. The goal is for you to understand how NLP works by using the information available to provide adequate results back to the user in a business scenario. In addition, this course will cover how NTP fits in machine learning by discussing areas such as classifications, neural networks, model training and transfer learning. 

Learning Outcomes

  1. Describe the key concepts and techniques of natural language processing and its usage.
  2. Design a speech application that uses technologies such as speech recognition, semantics, and translations.
  3. Create a program with Python that uses natural learning algorithms and libraries based on project examples to solve a business problem.
  4. Create an AI system used for a conversational agent to answer questions such as for a support call centre or other examples to demonstrate how the process works.
  5. Create a benefit analysis report on the performance of different NLP tools and systems.

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