Loader attribute of the E Learning Platform
Avail Flat 10% off on all courses | Utilise this to Up-Skill for best jobs of the industry Enroll Now

Natural Language Processing with Phyton Certification Course

876+ Learners

Stepleaf’s Natural Language Processing with Python course will take you through the essentials of text processing all the way up to classifying texts using Machine Learning algorithms. You will learn various concepts such as Tokenization, Stemming, Lemmatization, POS tagging, Named Entity Recognition, Syntax Tree Parsing and so on using Python’s most famous NLTK package. Once you delve into NLP, you will learn to build your own text classifier using the Naïve Bayes algorithm

Instructor led training provided by Stepleaf E-Learning Platform Instructor Led Training
Real time cases are given for students attending the online professional development courses Real Time Projects
Intertviews are scheduled after completing  Online Professional Development Courses Guaranteed Job Interviews
E-Learning Platform Flexible Schedule
E-Learning Platform LifeTime Free Upgrade
Stepleaf is the E-Learning Platform provides 24*7 customer support 24x7 Support

Natural Language Processing Online Course

Jul 25 Sat,Sun (4 Weeks) Weekend Batch Filling Fast 02:30 PM  04:30 PM
Time schedule for Online Professional Development Courses

Can't find a batch you were looking for?

Course Price at

$ 459.00

About Course

Stepleaf's Natural Language Processing using Python Training focuses on step by step guide to NLP and Text Analytics with extensive hands-on using Python Programming Language. It has been packed up with a lot of real-life examples, where you can apply the learned content to use. Features such as Semantic Analysis, Text Processing, Sentiment Analytics, and Machine Learning have been discussed. This course is for anyone who works with data and text– with good analytical background and little exposure to Python Programming Language. It is designed to help you understand the important concepts and techniques used in Natural Language Processing using Python Programming Language. You will be able to build your own machine learning model for text classification. Towards the end of the course, we will be discussing various practical use cases of NLP in the python programming language to enhance your learning experience.

Course Objectives

After completing this NLP training in Python, you will be able to:

  • Learn basics of Natural Language Processing in the most popular Python Library: NLTK
  • Learn techniques to access or modify some of the most common file types
  • Using I python notebooks, master the art of step by step text processing
  • Gain insight into the 'Roles' played by an NLP Engineer
  • Learn about Bag of Words Modelling and Tokenization of Text.
  • Use n-Gram Models to model and analyze the Bag of words from Corpus
  • Learn about converting text to vector using word frequency count, tf-idf etc.
  • Learn about Latent Semantic Analysis and its usage in the processing of context-aware Semantic Content.
  • Work with real-time data
  • Learn in detail about Sentiment Analysis one of the most interesting applications of Natural Language Processing
  • Gain expertise to handle business in future, living the present

Who should go for this training?

Stepleaf’s NLP Training is a good fit for the below professionals:

  • From a college student having exposure to programming to a technical architect/lead in an organisation
  • Developers aspiring to be a ‘Data Scientist'
  • Analytics Managers who are leading a team of analysts
  • Business Analysts who want to understand Text Mining Techniques
  • 'Python' professionals who want to design automatic predictive models on text data
  • "This is apt for everyone”

Pre-requisites

The prerequisites for this NLP course is Python programming and a good understanding of Machine Learning concepts.

As a goodwill gesture, Stepleaf offers a complimentary self-paced course in your LMS on Python to brush up on your Python Skills. 


Key Skills

machinelearning, textmining, NLP, OS Module, NLTK Corpora, POS Tagging, NER, Stopword Removal, Tokenization, Analyzing Sentence Structure, Syntax Trees, Chunking, Chinking, Context Free Grammars (CFG), Automating Text Paraphrasing, Count Vectorizer, Term Frequency, Inverse Document Frequency

Free Career Counselling
+91

Course Contents

Download Syllabus

Natural Language Processing with Phyton Certification Course Content

Learning Objectives: In this module, you will learn about text mining and the ways of extracting and reading data from some common file types including NLTK corpora  

Topics:

  • 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

Hands-On/Demo:

  • Install NLTK Packages using NLTK Downloader
  • Accessing your operating system using the OS Module in Python
  • Reading & Writing .txt Files from/to your Local
  • Reading & Writing .docx Files from/to your Local
  • Working with the NLTK Corpora
Learning Objectives: This module will help you understand some ways of text extraction and cleaning using NLTK.
Topics:
  • Tokenization
  • Frequency Distribution
  • Different Types of Tokenizers
  • Bigrams, Trigrams & Ngrams
  • Stemming
  • Lemmatization
  • Stopwords
  • POS Tagging
  • Named Entity Recognition

Hands-On/Demo:

  • Tokenization: Regex, Word, Blank line, Sentence Tokenizers
  • Bigrams, Trigrams & Ngrams
  • Stopword Removal
  • POS Tagging
  • Named Entity Recognition (NER)

Learning Objective: In this Module, you will learn how to analyse a sentence structure using a group of words to create phrases and sentences using NLP and the rules of English grammar
Topics:
  • Syntax Trees
  • Chunking
  • Chinking
  • Context Free Grammars (CFG)
  • Automating Text Paraphrasing

Hands-On/Demo:

  • Parsing Syntax Trees
  • Chunking
  • Chinking
  • Automate Text Paraphrasing using CFG’s

Learning Objective: In this module, you will explore text classification, vectorization techniques and processing using scikit-learn
Topics:
  • Machine Learning: Brush Up
  • Bag of Words
  • Count Vectorizer
  • Term Frequency (TF)
  • Inverse Document Frequency (IDF)

Hands-On/Demo:

  • Demonstrate Bag of Words Approach
  • Working with CountVectorizer()
  • Using TF & IDF

Learning Objective: In this module, you will learn to build a Machine Learning classifier for text classification
Topics:
  • Converting text to features and labels
  • Multinomial Naive Bayes Classifier
  • Leveraging Confusion Matrix

Hands-On/Demo:

  • Converting text to features and labels
  • Demonstrate text classification using Multinomial NB Classifier
  • Leveraging Confusion Matrix

Goal: In this module, you will learn Sentiment Classification on Movie Rating Dataset
Objective: At the end of this module, you should be able to:
Implement all the text processing techniques starting with tokenization
Express your end to end work on Text Mining
Implement Machine Learning along with Text Processing
Hands-On:
Sentiment Analysis

Like the curriculum? Enroll Now

Structure your learning and get a certificate to prove it.

+91
Two persons discussing about the online developemnet courses

Projects

What are the system requirements for our NLP Certification Training?

You don’t have to worry about the System Requirements as you will be doing your Practical on a Cloud LAB environment. This environment already contains all the necessary software that will be required to execute your practicals.

How will I execute the practicals?

You will do your Assignments/Case Studies using Jupyter Notebook that is already installed on your Cloud LAB environment whose access details will be available on your LMS. You will be accessing your Cloud LAB environment from a browser. For any doubt, the 24*7 support team will promptly assist you.

Certification

StepLeaf’s Natural Language Processing Engineer Certificate Holders work at 1000s of companies

FAQ

All the instructors at StepLeaf are practitioners from the Industry with minimum 10-12 yrs of relevant IT experience. They are subject matter experts and are trained by StepLeaf for providing an awesome learning experience to the participants.


You will never miss a lecture at StepLeaf! You can choose either of the two options:
  • View the recorded session of the class available in your LMS.
  • You can attend the missed session, in any other live batch.
We have limited number of participants in a live session to maintain the Quality Standards. So, unfortunately participation in a live class without enrollment is not possible. However, you can go through the sample class recording and it would give you a clear insight about how are the classes conducted, quality of instructors and the level of interaction in a class.
All the instructors at StepLeaf are practitioners from the Industry with minimum 10-12 yrs of relevant IT experience. They are subject matter experts and are trained by StepLeaf for providing an awesome learning experience to the participants.
;
Bootstrap
Title