Natural Language Processing with Python Certification Course

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Natural language processing (NLP) denotes artificial intelligence (AI) to manipulate written or spoken languages. With this course, you will master Machine Learning algorithms with Python programming.

Course Description

Natural Language Processing with Python Certification Course will take you through the necessities of text processing to classify texts using Machine Learning algorithms. In this course, candidates will understand diverse concepts such as Tokenization, Stemming, Lemmatization, POS tagging, Named Entity Recognition, Syntax Tree Parsing using Python’s NLTK.

NLP is a subset of artificial intelligence and machine learning that enables computers to comprehend, analyze, and control human language. It has numerous applications, including speech recognition, automated chatbots, sentiment analysis, and more.

This NLP course is for candidates who operate data and Text– with good analytical background. It is created to assist you in comprehending the crucial notions and methods used in Natural Language Processing using Python Programming Language.

NLP is important because it assists fix ambiguity in language and adds functional numeric structure to the data for many downstream applications, such as speech recognition or text analytics. This certification validates your knowledge of managing NLP with Python programming.

The conditions for this Natural Language Processing course is Python programming and sound knowledge of Machine Learning concepts.

The most ordinary NLP job titles include: NLP Researcher. NLP Analyst. NLP Scientist. NLP Engineer.

Yes, the need for NLP assistance is anticipated to rise due to the increased demand for improving customer experiences and building personalized relationships.

Natural language processing (NLP) refers to the department of computer science—and more particularly, artificial intelligence or AI—to give computers the ability to understand Text and spoken words in broadly the same way human beings can.

What you'll learn

  • In this course, you will learn to: basics of Natural Language Processing, techniques to access or alter some file types, Words Modelling and Tokenization of Text, Transforming Text to vector operating word frequency count, tf-idf etc, Semantic Analysis and its usage in processing context-aware Semantic Content and more.

Requirements

  • Python programming good understanding of Machine Learning concepts.

Curriculam

you will learn the concept of text mining and the ways of extracting and reading data from some common file types, including NLTK corpora.

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
Install NLTK Packages using NLTK Downloader
Accessing operating system using the OS Module in Python
Reading & Writing .txt Files
Reading & Writing .docx Files
Working with the NLTK Corpora

you will know text extraction and cleaning using NLTK

Tokenization
Frequency Distribution
Different Types of Tokenizers
Bigrams, Trigrams & Ngrams
Stemming
Lemmatization
Stopwords
POS Tagging
Named Entity Recognition
Tokenization: Regex, Word, Blank line, Sentence Tokenizers
Bigrams, Trigrams & Ngrams
Stopword Removal
POS Tagging
Named Entity Recognition (NER)

you will discover how to analyze a sentence structure using words to create phrases and sentences using NLP and English grammar rules.

Syntax Trees
Chunking
Chinking
Context-Free Grammars (CFG)
Automating Text Paraphrasing
Parsing Syntax Trees
Chunking
Chinking
Automate Text Paraphrasing using CFG’s

you will study text classification, vectorization techniques and processing using scikit-learn

Machine Learning: Brush Up
Bag of Words
Count Vectorizer
Term Frequency (TF)
Inverse Document Frequency (IDF)
Demonstrate Bag of Words Approach
Working with Count Vectorizer
Using TF & IDF

you will understand to build a Machine Learning classifier for text classification.

Converting Text to features and labels
Multinomial Naive Bayes Classifier
Leveraging Confusion Matrix
Converting Text to markers and labels
Demonstrate text classification using Multinomial NB Classifier
Leveraging Confusion Matrix

grasp Sentiment Classification on Movie Rating Dataset

text-processing techniques
Text Mining
Implement Machine Learning along with Text Processing
Sentiment Analysis

FAQ

NLP is one of the highest technologies in the AI Industry. After completing this course, you can improve your proficiency in the industry and land a high-paying position in the field.

Python is the perfect coding language for machine learning, NLP, and neural network connections. Python can be operated even if you are new to AI development as it is flexible and comes with pre-existing libraries like Pandas, SciPy, and NLTK. Python language is praised for its easy syntax and minimal codes.

The earnings of prospects in this position range from a low of $140,000 to a high of $200,000, with median earnings of $180,000.

To better comprehend the study, one must understand as per the curriculum.

Natural Language Processing Engineer responsibilities include: Designing and developing NLP applications and using effective text representation techniques and classification algorithms. Training and evaluating models.

According to research, conversational AI, chatbots, and document AI are expected to bring high to very high business benefits while promising to become mainstream in less than two years.

You will receive CertZip Natural Language Processing with Python certification on completing live online instructor-led classes. After completing the course module, you will receive the certificate.

By enrolling in the Natural Language Processing with Python Certification course and completing the module, you can get CertZip Natural Language Processing with Python Certification.

CertZip Support Unit is for a lifetime and is available 24/7 to help with your queries during and after the completion of the course.

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Training Course Features

Assessments
Assessments

Every certification training session is followed by a quiz to assess your course learning.

Mock Tests
Mock Tests

The Mock Tests Are Arranged To Help You Prepare For The Certification Examination.

Lifetime Access
Lifetime Access

A lifetime access to LMS is provided where presentations, quizzes, installation guides & class recordings are available.

24x7 Expert Support
24x7 Expert Support

A 24x7 online support team is available to resolve all your technical queries, through a ticket-based tracking system.

Forum
Forum

For our learners, we have a community forum that further facilitates learning through peer interaction and knowledge sharing.

Certification
Certification

Successfully complete your final course project and CertZip will provide you with a completion certification.

Natural Language Processing with Python Certification Course

A Microsoft Natural Language Processing with Python certificate is a certification that verifies that the holder has the knowledge and skills required to work with Azure technology.

Yes, Access to the course material will be available for a lifetime once you have enrolled in Edita Natural Language Processing with Python Certification Course.

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