Course Overview

The Natural Language Processing course covers concepts like statistical machine translation and neural models, deep semantic similarity models (DSSM), neural knowledge base embedding, deep reinforcement learning techniques, neural models applied in image captioning, and visual question answering with Python’s Natural Language Toolkit.

Key Features

  • Lifetime access to self-paced learning
  • Industry-recognized course completion certificate

Skills Covered

  • Perform text processing
  • Working with NLP Pipeline
  • Create an NLP module
  • Classify cluster for articles
  • Create a basic speech model
  • Convert speech to text

Training Options

Blended Learning

$ 799

  • 90 days of flexible access to online classes
  • Lifetime access to high-quality self-paced e-learning content and live class recordings
  • 24x7 learner assistance and support
  • Classes starting from:-
25th Sep: Weekday Class

Corporate Training

Customized to your team's needs

  • Blended learning delivery model (self-paced e-learning and/or instructor-led options)
  • Course, category, and all-access pricing
  • Enterprise-class learning management system (LMS)
  • Enhanced reporting for individuals and teams
  • 24x7 teaching assistance and support

Course Curriculum

Eligibility

Natural Language Processing course is ideal for anyone who wants to become familiar with this emerging and exciting domain of artificial intelligence (AI), including data scientists, analytics managers, data analysts, data engineers, and data architects.
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Pre-requisites

Learners are looking to enroll for Natural Language Processing course should have a basic understanding of math, statistics, data science, and machine learning.
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Course Content

  • Section 01 - NLP Overview (Self Learning)

    Preview
    • Lesson 1 Working with Text Corpus

      26:17Preview
      • 1.1 The Course Overview
        03:59
      • 1.2 Access and Use the Built-in Corpora of NLTK
        06:20
      • 1.3 Loading a Corpus
        04:08
      • 1.4 An Example of Conditional Frequency Distribution
        05:11
      • 1.5 An Example of Lexical Resouce
        06:39
    • Lesson 2 Processing Raw Text with NLTK

      23:12Preview
      • 2.1 Working with an NLP Pipeline
        06:14
      • 2.2 Implementing Tokenization
        05:31
      • 2.3 Regular Expressions
        05:30
      • 2.4 Regular Expressions Used in Tokenization
        05:57
    • Lesson 3 A Practical Real World Example of Text Classification

      19:38
      • 3.1 Naive Bayes Text Classification
        07:06
      • 3.2 Age Prediction Application
        06:37
      • 3.3 Document Classifier Application
        05:55
    • Lesson 4 Finding Useful Information from Piles of Text

      13:24Preview
      • 4.1 Hierarchy of Ideas or Chunking
        02:33
      • 4.2 Chunking in Python NLTK
        05:18
      • 4.3 Chinking Non Chunk Patterns in NLTK
        05:33
    • Lesson 5 Developing a Speech to Text Application Using Python

      28:43Preview
      • 5.1 Python Speech Recognition Module
        06:11
      • 5.2 Speech to Text with Recurrent Neural Networks
        09:36
      • 5.3 Speech to Text with Convolutional Neural Networks Part One
        06:29
      • 5.4 Speech to Text with Convolutional Neural Networks Part Two
        06:27
  • Section 02 -NLP (Live Classes)

    Preview
    • Lesson 1 - Introduction to NLP

      • Introduction to Natural Language Processing
      • Components of NLP
      • Applications of NLP
      • Challenges and scope
      • Data formats
      • Text Processing
      • Assisted Practice: Implement Text Processing Using Stemming and Regular Expression after Noise Removal and Convert It into List of Phrases
      • Tweets Cleanup and Analysis Using Regular Expressions
    • Lesson 2 - Feature Engineering on text data

      • N-Gram
      • Bag of Words
      • Document Term Matrix
      • TF-IDF
      • Levenshtein Distance
      • Word Embedding(Word2Vec)
      • Doc2vec
      • PCA
      • Word Analogies
      • Topic Modelling
      • Assisted Practice: Word2vec Model Creation
      • Assisted Practice: Word Analogies Demo
      • Assisted Practice: Identify Topics from News Items
      • Build Your Own News Search Engine
    • Lesson 3 - Natural Language Understanding techniques

      • Parts of Speech Tagging
      • Dependency Parsing
      • Constituency Parsing
      • Morphological Parsing
      • Named Entity Recognition
      • Coreference Resolution
      • Word Sense Disambiguation
      • Fuzzy Search
      • Document and Sentence Similarity
      • Document Indexing
      • Sentiment Analysis
      • Assisted Practice: Analyzing the Disease and Instrument Name with the Action Performed
      • Assisted Practice: Analyzing the Sentiments
      • Assisted Practice: Extract City and Person Name from Text
      • Identifying Top Product Feature from User Reviews
    • Lesson 4 - Natural Language Generation

      • Retrieval based model
      • Generative based model
      • AIML
      • Language Modelling
      • Sentence Correction
      • Assisted Practice: Create AIML Patterns for QnA on Mental Wellness
      • Assisted Practice: To Predict the Next Word in a Sentence
      • Create your Own Spell Checker
    • Lesson 5 - NLP Libraries

      • Spacy
      • NLTK
      • Gensim
      • TextBlob
      • StanfordNLP
      • LUIS
      • Assisted Practice: Simplilearn Review Analysis
      • Create your Own NLP Module
    • Lesson 6 - NLP with Machine Learning and Deep Learning

      • Neural Machine Translation
      • Text Classification
      • Text Summarization
      • Document Clustering
      • Attention Mechanism
      • Question Answering Engine
      • Assisted Practice: Target Spam Words and Patterns
      • Assisted Practice: Summarization of News
      • Document Clustering for BBC News
    • Lesson 7 - Speech recognition techniques

      • Basic concepts for voice/sound
      • Reading, loading and processing the voice data
      • Creating speech model
      • Saving model
      • Implementation/use cases
      • Speech libraries
      • Assisted Practice: Translation from Speech to Text
      • Speech to Text: Extract Keywords from Audio Reviews
  • Natural Language Processing

    Preview
    • Section 03 - Practice Projects

      • Twitter Hate
      • Zomato Rating

Exam & Certification

Natural Language Processing Certificate
  • What do I need to do to unlock my Simplilearn certificate?

    You must complete this Natural Language Processing course in order to unlock the Simplilearn certificate.

  • Who provides the certificate and how long it is valid for?

    Once you successfully complete the Natural Language Processing course as part of Artificial Intelligence Engineer Master’s Program, Simplilearn will provide you with an industry-recognized course completion certificate which will have a lifelong validity.
     

Why Simplilearn

Simplilearn’s Blended Learning model brings classroom learning experience online with its world-class LMS. It combines instructor-led training, self-paced learning and personalized mentoring to provide an immersive learning experience.

  • Self-Paced Online Video

    A 360-degree learning approach that you can adapt to your learning style

  • Live Virtual Classroom

    Engage and learn more with these live and highly-interactive classes alongside your peers

  • 24/7 Teaching Assistance

    Keep engaged with integrated teaching assistance in your desktop and mobile learning

  • Online Practice Labs

    Projects provide you with sample work to show prospective employers

  • Applied Projects

    Real-world projects relevant to what you’re learning throughout the program

  • Learner Social Forums

    A support team focused on helping you succeed alongside a peer community

FAQs

  • What is Natural Language Processing (NLP)?

    Natural language processing (or text analytics/text mining) applies analytic tools to read from a huge collection of natural language data to derive a meaningful conclusion. It has given rise to chatbots and virtual assistants to address queries of millions of users. It is a branch of artificial intelligence that has important implications on the ways that computers and humans interact. Natural language processing will help bridge the gap between human communication and digital data.
     

  • How do I enroll in this online training?

    You can enroll in this training on our website and make an online payment using any of the following options:
     
    ·     Visa Credit or Debit Card
    ·     MasterCard
    ·     American Express
    ·     Diner’s Club
    ·     PayPal
     
    Once payment is received you will automatically receive a payment receipt and access information via email.

  • Can I cancel my enrollment? Will I get a refund?

    Yes, you can cancel your enrollment if necessary. We will refund the course price after deducting an administration fee. To learn more, you can view our refund policy.
     

  • What is covered under the 24/7 Support promise?

    We offer 24/7 support through email, chat, and calls. We also have a dedicated team that provides on-demand assistance through our community forum. What’s more, you will have lifetime access to the community forum, even after completion of your course with us.

  • Is this live training, or will I watch pre-recorded videos?

    It depends on the learning you choose. If you enroll for self-paced e-learning, you will have access to pre-recorded videos. However, if you enroll for the Online Classroom Flexi-Pass, you will have access to both live training conducted online as well as the pre-recorded videos.

  • Who are the instructors and how they are selected?

    All of Simplilearn’s Natural Language Processing trainers are experienced industry experts. Each of them have gone through a rigorous selection process that includes profile screening, technical evaluation, and a training demo before they are certified to train for us. We at Simplilearn also ensure that only those trainers with a high alumni rating are selected as our faculty.

  • What is Global Teaching Assistance?

    All of Simplilearn’s teaching assistants are subject matter experts who will help you learn Natural Language Processing thoroughly and get certified in the first attempt itself. They engage students proactively to ensure the course path is being followed and help you enrich your learning experience, from class onboarding to project mentoring and job assistance. Teaching Assistance is available during business hours.

  • Whom should I contact to learn more about this Natural Language Processing course?

    If you want to know more about this NLP certification course, you can contact us using the form on the right of any page on the Simplilearn website, or select the Live Chat link in the live chat tab present in all the pages at the bottom right part of the webpage. Our customer service representatives will be able to give you more details.

  • Disclaimer
  • PMP, PMI, PMBOK, CAPM, PgMP, PfMP, ACP, PBA, RMP, SP, and OPM3 are registered marks of the Project Management Institute, Inc.