Natural Language Processing with Python Certification Course

Bridge the communication gap between Artificial Intelligence and humans

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Key Highlights

  • 18 Hours of Live Instructor-led Classes
  • 6 sessions of 3 hours each on Weekends
  • Live Project on Real-life Case Studies
  • Practical Assignments of Over 20 Hours
  • Lifetime Access to Learning Management System
  • 24x7 Expert Support
  • Course Completion Certificate
  • Online Forum for Discussions
  • Cloud lab for hands-on experience

Course Price Range

$349.00 - $349.00 $700.00 - $700.00

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1866-216-7898

(Toll Free)

Available Courses Delivery

This course is available in the following formats:

Virtual Live

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Nov 16th
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Delivery: Online
Access: Lifetime
Sat - Sun (3 Weeks)
Timings - 10:00 AM to 01:00 PM (EST)

Weekend Batch (Morning)
$700  $349
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Course Overview

Natural Language Processing (NLP) is a part of Artificial Intelligence (AI) that backs meaningful communication between a computer and human to meet a valuable objective. Virtual assistants like Alexa, Siri, Cortana, and Ok Google use NLP to interact with humans. Using Python?s NLTK package, this course will take you through the essentials of how NLP is done, including text processing, text classification, machine learning algorithms, syntax tree parsing, POS tagging, and more.

Course Objectives

  • Basic NLP training using NLTK Python library
  • Learn stepwise text processing using Jupyter Notebook (formerly IPython Notebook)
  • Familiarize with an NLP engineer?s roles
  • Work with real-time data used in NLP
  • Get acquainted with n-Gram model, text-to-vector conversion, sentiment analysis and more
  • Get insights into Latent Semantic Analysis, and how it processes semantic content that is context-aware

Career Benefits

  • Get better opportunities in the AI sector
  • Work on exciting and surreal projects that promote humanization of the AI
  • Better remuneration with new AI skills
  • Improve business processes through created chatbots
  • Better documentation in your company/business

Prerequisites

  • None, but knowing the fundamentals of AI helps.

Who should take up?

  • Software Developers who want to explore data sciences
  • Aspiring NLP engineers
  • College students interested in AI
  • Analyst team leaders
  • Business analysts who want to use text mining profitably
  • Python programmers interested in AI

Course Content

  • Overview of Text Mining
  • Need of Text Mining
  • Natural Language Processing (NLP) in Text Mining
  • Applications of Text Mining
  • OS Module
  • Reading, Writing to text and word files
  • Setting the NLTK Environment
  • Accessing the NLTK Corpora
  • Tokenization
  • Frequency Distribution
  • Different Types of Tokenizers
  • Bigrams, Trigrams & Ngrams
  • Stemming
  • Lemmatization
  • Stopwords
  • POS Tagging
  • Named Entity Recognition
  • Syntax Trees
  • Chunking
  • Chinking
  • Context Free Grammars (CFG)
  • Automating Text Paraphrasing
  • Machine Learning: Brush Up
  • Bag of Words
  • Count Vectorizer
  • Term Frequency (TF)
  • Inverse Document Frequency (IDF)
  • Converting text to features and labels
  • Multinomial Naiive Bayes Classifier
  • Leveraging Confusion Matrix
  • In this module, you will learn Sentiment Classification on Movie Rating Dataset.

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