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NLP Programming

Course Highlights

  • 30+ Scenarios
  • 10+ Real world Use cases
  • Understanding Techniques from Scratch
  • Individual Guidance
  • Unique Training & Internship Program (TIP) & Evaluation

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    Course Description

    With the increasing demand for automation and digital transformation, AI and machine learning engineers are expected to be in high demand. Salaries for these roles are already high and are projected to continue to rise in the coming years.

    Most of the freshers are tempted to move to Artificial Intelligence, since the market promises very high paid jobs. To get into NLP you must be strong in Logical & mathematical skills and should show deep interest in research and analysis. Minimum of two to three years of experience in relevant industry will fetch you the status of NLP Engineer. The average salary of an NLP Engineer with a minimum of 2+ years experience is 9.7 LPA. 

    In the modern era, most of the applications are requiring the developers to work with NLP tools and techniques. NLP being the sub field of Artificial Intelligence, is concerned with enabling computers to understand and process human intelligence. You shall be working with multiple Ambiguity and uncertainty in processing text messages which can be expressed in multiple ways. You will also be required to do Analysis of data which will help to predict the approximate data points. 

    Course Details

    • Prerequisites: Python Basics
    • Assignment: 1 per session
    • Assessment & Evaluations: 1 per week
    • Training Mode : Offline / Online / Onsite
    Tools Covered
    • Matplotlib, Seaborn
    • Histogram
    • Text Processing
    • TensorFlow, NLTK
    Course Content
    • Introduction To Python
    • Conditional Statements And Loops
    • Pandas And Numpy
    • Data Preprocessing
    • Data Visualization
    • Natural Language Processing
    • NLP Techniques
    • Syntactic Analysis
      • Tokenization  
      • Part Of Speech Tagging (Pos Tagging)
      • Lemmatization & Stemming
        • Stemming Words With Nltk
        • Lemmatization With Nltk  
        • Lemmatization With Textblob
      • Stop-Word Removal
    • Semantic Analysis
      • Word Sense Disambiguation  
      • Relationship Extraction  
      • How To Get Synonyms/Antonyms From Nltk Wordnet In Python?

     

    Course Details

    • Hands On Training : 20-30 Hrs
    • Practical Session : 10-20 Hrs
    • Practical Assignment : 1 per session

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    • .NET Full Stack Development
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