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Natural Language Processing with Python Certification Course

Natural Language Processing with Python Certification Course

Name: Natural Language Processing with Python Certification Course
Item: Natural Language Processing with Python Certification Course
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Edureka’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.

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60 days of Cloud Lab access

Why should you take Natural Language Processing with Python?

NLP to help AI market to be greater than $60 Billion buy 2025 ~ Forbes

IBM, Microsoft Corporation, Nuance Communications, Health Fidelity have high demand for NLP experts

As per indeed.com, Mean salary of NLP professional is $128,857

Instructor-led Natural Language Processing with Python live online classes

May 23 ^rd

Sat & Sun (3 Weeks) Weekend Batch

Sold Out Timings - 11:00 AM to 02:00 PM (EDT)

Jul 10 ^th

Fri & Sat (3 Weeks) Weekend Batch

Filling Fast Timings - 09:30 PM to 12:30 AM (EDT)

Sep 12 ^th

Sat & Sun (3 Weeks) Weekend Batch

Timings - 11:00 AM to 02:00 PM (EDT)

Course Price at

296 349

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Curriculum

Introduction to Text Mining and NLP

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

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Extracting, Cleaning and Pre-processing Text

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)

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Analyzing Sentence Structure

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

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Text Classification - I

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

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Text Classification - II

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 Naiive Bayes Classifier
Leveraging Confusion Matrix

Hands On/Demo:

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

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In Class Project

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

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Course Description

About the Natural Language Processing with Python course

Edureka'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 learnt 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 python programming language to enhance your learning experience.

Why learn Natural Language Processing or NLP?

Natural Language Processing (or Text Analytics/Text Mining) applies analytic tools to learn from collections of text data, like social media, books, newspapers, emails, etc. The goal can be considered to be similar to humans learning by reading such material. However, using automated algorithms we can learn from massive amounts of text, very much more than a human can. It is bringing a new revolution by giving rise to chatbots and virtual assistants to help one system address queries of millions of users.

NLP is a branch of artificial intelligence that has many important implications on the ways that computers and humans interact. Human language, developed over thousands and thousands of years, has become a nuanced form of communication that carries a wealth of information that often transcends the words alone. NLP will become an important technology in bridging the gap between human communication and digital data.

What are the objectives of our NLP using Python Training?

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 NLP Training in Python?

Edureka’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”

What are the prerequisites for this Course?

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

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

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Certification

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

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Your Name

Natural Language Processing Engineer

with Grade X

Sample ID NA Signature

The Certificate ID can be verified at www.edureka.co/verify to check the authenticity of this certificate

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Testimonial Reviews

Dheerendra YadavProject Lead at HCL Technologies, Ghaziabad, Uttar Pradesh, India

Earlier I had taken training in different technologies from other institutes and companies but no do ... Read More

Chandra Bhushan KIT Consultant, Architect - Analytics in Karmanya Software Pvt Ltd, Hyderabad Area, India

Edureka has redefined the e-learning service with the help of technology. They have excellent facult ... Read More

Vishal PawarPMP Certified, Lead Consultant, HCL Technologies Ltd. Mumbai Area, India

edureka! is efficiently able to provide effective e-learning for Big Data. All the required material ... Read More

Janardhan SingamaneniPrincipal Data Engineer at Staples

I took kafka and datascience classes with EDUREKA and its overall nice. After thorough scanning of a ... Read More

Gagan Maheshwari

Thanks a lot for your Android course. Right from the point of the start of the demo class, until the ... Read More

GopinathSAP Architect Consultant, IBM India Pvt Ltd, Bengaluru, Karnataka, India

I attended the demo session without any intention of joining a course. But the demo class was so imp ... Read More

Video Reviews

Our learner Balasubramaniam shares his Edureka learning experience and how our training helped him stay updated with evolving technologies.

Vinayak shares his Edureka learning experience and how our Big Data training helped him achieve his dream career path.

Shyam speaks about his learning experience with Edureka and how our DevOps Certification Training gave him the confidence to make a career shift.

Nidhi shares her Edureka learning experience and how our Python course helped her gain an edge in her job interviews and land a job.

Sriram speaks about his learning experience with Edureka and how our Hadoop training helped him execute his Big Data project efficiently.

Sabari Abhilash shares his Digital Marketing course experience and how it helped him upgrade his skill-sets to keep up with the changing digital landscape.

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Project

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.

Features

Instructor-led Sessions

18 Hours of Online Live Instructor-Led Classes. Weekend Class: 6 sessions of 3 hours each.

Real-life Case Studies

Live project based on any of the selected use cases, involving the implementation of the various NLP concepts using Python

Assignments

Each class will be followed by practical assignments which will aggregate to a minimum 20 hours.

Lifetime Access

You get lifetime access to the Learning Management System (LMS) where presentations, quizzes, installation guide & class recordings are there.

24 x 7 Expert Support

We have the 24x7 online support team to resolve all your technical queries, through ticket based tracking system, for the lifetime.

Certification

Towards the end of the course, you will be working on a project. Edureka certifies you as a "Natural Language Processing Engineer" based on the project.

Forum

We have a community forum for all our customers that further facilitates learning through peer interaction and knowledge sharing.

FAQ

What if I miss a class?

"You will never miss a lecture at Edureka! 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."

What if I have queries after I complete this course?

Your access to the Support Team is for lifetime and will be available 24/7. The team will help you in resolving queries, during and after the course.

How soon after Signing up would I get access to the Learning Content?

Post-enrolment, the LMS access will be instantly provided to you and will be available for lifetime. You will be able to access the complete set of previous class recordings, PPTs, PDFs, assignments. Moreover the access to our 24x7 support team will be granted instantly as well. You can start learning right away.

Is the course material accessible to the students even after the course training is over?

Yes, the access to the course material will be available for lifetime once you have enrolled into the course.

What if I have more queries?

You can give us a CALL at +91 90660 20867/1844 230 6362 (US Tollfree Number) OR email at sales@edureka.co

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Be future ready. Start learning

Structure your learning and get a certificate to prove it.

Natural Language Processing with Python Certification Course

Why should you take Natural Language Processing with Python?

Instructor-led Natural Language Processing with Python live online classes

Financing Options

Curriculum

Introduction to Text Mining and NLP

Extracting, Cleaning and Pre-processing Text

Analyzing Sentence Structure

Text Classification - I

Text Classification - II

In Class Project

Course Description

About the Natural Language Processing with Python course

Why learn Natural Language Processing or NLP?

What are the objectives of our NLP using Python Training?

Who should go for this NLP Training in Python?

What are the prerequisites for this Course?

Testimonial Reviews

Video Reviews

Project

What are the system requirements for our NLP Certification Training?

How will I execute the practicals?

Features

Instructor-led Sessions

Real-life Case Studies

Assignments

Lifetime Access

24 x 7 Expert Support

Certification

Forum

FAQ

What if I miss a class?

What if I have queries after I complete this course?

How soon after Signing up would I get access to the Learning Content?

Is the course material accessible to the students even after the course training is over?

What if I have more queries?

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