Corporate Natural Language Processing (NLP) with Python Training Course

Edstellar's instructor-led Natural Language Processing (NLP) with Python training course equips professionals with the essentials of word tokenization and segmentation, topic extraction, and constructing a fake news classifier. The course empowers teams to process and understand natural language data, driving organizational innovation.

24 - 32 hrs

Instructor-led (On-site/Virtual)

English

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Natural Language Processing (NLP) with Python Training

About Learning Outcomes Benefits Course Outline Pricing Target Audience Pre-Requisites Trainers

Drive Team Excellence with Natural Language Processing (NLP) with Python Training for Employees

Empower your teams with expert-led on-site/in-house or virtual/online Natural Language Processing (NLP) with Python Training through Edstellar, a premier corporate training company for organizations globally. Our tailored Natural Language Processing (NLP) with Python corporate training course equips your employees with the skills, knowledge, and cutting-edge tools needed for success. Designed to meet your specific needs, this Natural Language Processing (NLP) with Python group training program ensures your team is primed to drive your business goals. Transform your workforce into a beacon of productivity and efficiency.

Natural Language Processing (NLP) with Python involves using Python programming to analyze and manipulate human language data across various applications. The course enables professionals to harness data effectively, extract valuable insights, automate tasks, and improve communication. Natural Language Processing (NLP) with Python training course is essential for organizations to enhance efficiency, understand customer sentiment, automate repetitive tasks, and gain a competitive edge.

Edstellar's instructor-led Natural Language Processing (NLP) with Python training course, conducted by industry experts with extensive experience in the field, is delivered through virtual/onsite modes. Edstellar provides practical insights into NLP techniques, a customized curriculum, and real-world applications. Professionals will learn to process, analyze, and interpret textual data using Python libraries such as NLTK, spaCy, and scikit-learn.

Key Skills Employees Gain from Natural Language Processing (NLP) with Python Training

Natural Language Processing (NLP) with Python skills corporate training will enable teams to effectively apply their learnings at work.

Advanced NLP Techniques
Sentiment Analysis
Custom Model Development
Text Summarization
Information Extraction
Decision-making

Natural Language Processing (NLP) with Python Training for Employees: Key Learning Outcomes

Edstellar’s Natural Language Processing (NLP) with Python training for employees will not only help your teams to acquire fundamental skills but also attain invaluable learning outcomes, enhancing their proficiency and enabling application of knowledge in a professional environment. By completing our Natural Language Processing (NLP) with Python workshop, teams will to master essential Natural Language Processing (NLP) with Python and also focus on introducing key concepts and principles related to Natural Language Processing (NLP) with Python at work.

Employees who complete Natural Language Processing (NLP) with Python training will be able to:

Apply advanced NLP techniques to analyze and extract meaningful insights from textual data, enhancing decision-making processes within the organization
Analyze and interpret sentiment in customer feedback, enabling more informed marketing strategies and improved customer satisfaction
Develop custom NLP models tailored to the organization's specific needs, automating repetitive tasks and streamlining workflows
Implement text summarization algorithms to efficiently distill large volumes of information into concise and actionable summaries, saving time and resources
Utilize information extraction techniques to extract structured data from unstructured text, facilitating data-driven decision-making and enhancing business intelligence capabilities

Key Benefits of the Natural Language Processing (NLP) with Python Corporate Training

Attending our Natural Language Processing (NLP) with Python classes tailored for corporations offers numerous advantages. Through our on-site/in-house or virtual/online Natural Language Processing (NLP) with Python training classes, participants will gain confidence and comprehensive insights, enhance their skills, and gain a deeper understanding of Natural Language Processing (NLP) with Python.

Learn advanced techniques in Natural Language Processing (NLP) with Python, enhancing your expertise in textual data analysis
Equip professionals with the skills to effectively process and interpret human language data using Python programming
Develop proficiency in building and deploying NLP models, empowering teams to tackle complex language-related tasks with confidence
Explore practical applications of NLP in real-world scenarios, gaining insights into sentiment analysis, text summarization, and information extraction
Gain hands-on experience with industry-relevant projects, honing your ability to apply NLP techniques to solve diverse challenges

Natural Language Processing (NLP) with Python Training Topics and Outline

Our virtual and on-premise Natural Language Processing (NLP) with Python training curriculum is divided into multiple modules designed by industry experts. This Natural Language Processing (NLP) with Python training for organizations provides an interactive learning experience focused on the dynamic demands of the field, making it relevant and practical.

Basics of Text Processing

Introduction to regular expressions
- Syntax and basic patterns
- Quantifiers and modifiers
- Character classes and groups
Tokenization of text
- Word tokenization
- Sentence tokenization
Normalization of text
- Case normalization
- Accent removal
- Punctuation removal
Substituting and correcting tokens
- Spell checking and correction
- Token normalization techniques
Applying Zipf's law to text
- Zipf's law and its implications in text analysis
Applying similarity measures using the edit distance algorithm
- Calculation of edit distance between strings
Applying similarity measures using Jaccard's coefficient
- Calculation of Jaccard similarity between sets of tokens
Applying similarity measures using Smith Waterman
- Smith Waterman algorithm for local sequence alignment

Statistical Language Modeling

Understanding word frequency
- Calculation of term frequency and document frequency
Applying smoothing on the MLE model
- Techniques for smoothing probability estimates
Develop a backup mechanism for MLE
- Implementation of backup mechanisms such as good-turing smoothing
Data interpolation
- Interpolation techniques for combining language models
Language modeling using metropolis hastings
- Application of Metropolis-Hastings algorithm for language modeling
Gibbs sampling in language processing
- Use of Gibbs sampling for estimating parameters in probabilistic models

Morphological Modeling

Introducing morphology
- Basic concepts and principles of morphology in linguistics
Understanding stemmer
- Types of stemmers
- Algorithmic details and differences between stemmers
Lemmatization
- Lemmatization versus stemming: Differences and benefits
- Algorithmic approaches to lemmatization: Dictionary-based, rule-based, and hybrid methods
Morphological analyzer
- Components of a morphological analyzer: Lexicon, rules, morphotactics
- Techniques for building and using a morphological analyzer
Morphological generator
- Generation of inflected forms from lemmas: Suffixation, prefixation, infixation
- Challenges and considerations in morphological generation

Syntactic Analysis

Introducing parsing
- Types of parsing: Top-down parsing, bottom-up parsing, chart parsing
- Parsing techniques: Recursive descent parsing, shift-reduce parsing
Treebank construction
- Annotation guidelines and standards for treebank construction
Extracting Context-Free Grammar (CFG) rules from treebank
- Conversion of treebank annotations into CFG rules
- Automatic extraction methods and tools for CFG induction
CYK chart parsing algorithm
- Overview of Cocke-Younger-Kasami (CYK) parsing algorithm
- CYK algorithm implementation and optimization techniques
Earley chart parsing algorithm
- Introduction to earley parsing algorithm
- Earley parsing chart data structure and parsing process

Semantic Analysis

Introducing semantic analysis
- Overview of semantic analysis and its importance in NLP
Named-entity recognition (NER)
- NER techniques and algorithms
- Named-entity types and classifications
NER system using the HMM
- Implementation of NER system using Hidden Markov Models (HMM)
Training NER using machine learning toolkits
- Machine learning approaches for training NER models
- Feature engineering and model selection for NER
NER using POS tagging
- NER based on part-of-speech tagging techniques
Generation of the synset ID from Wordnet
- Creation of synset identifiers from WordNet database
Disambiguating senses using Wordnet
- Sense disambiguation techniques using WordNet synsets

Sentiment Analysis

Introducing sentiment analysis
- Understanding sentiment analysis and its applications
Sentiment analysis using NER
- Incorporating NER techniques into sentiment analysis tasks
Sentiment analysis using machine learning
- Machine learning approaches for sentiment analysis
- Sentiment classification algorithms and techniques
Evaluation of the NER system
- Performance evaluation metrics for NER systems
- Error analysis and improvement strategies for NER models

Information Retrieval

Introducing information retrieval
- Overview of information retrieval and its objectives
Stop word removal
- Techniques for removing stop words from text documents
Information retrieval using a vector space model
- Vector space model representation of documents and queries
- Cosine similarity computation for document ranking
Vector space scoring and query operator interactions
- Weighting schemes and query expansion techniques
Text summarization
- Extractive and abstractive text summarization techniques
- Evaluation metrics for text summarization systems

Discourse Analysis

Introducing discourse analysis
- Introduction to discourse analysis and its relevance in NLP
Discourse analysis using centering theory
- Application of centering theory for analyzing discourse coherence
Anaphora resolution
- Techniques for resolving anaphoric references in text
- Pronoun resolution algorithms and approaches

Evaluation of NLP Systems – Analyzing Performance

The need for the evaluation of NLP systems
- Importance of system evaluation in NLP applications
Evaluation of IR Systems
- Evaluation metrics for information retrieval systems
- Relevance assessments and judgment criteria
Metrics for error identification
- Error analysis techniques and metrics for identifying NLP system errors
Metrics based on lexical matching
- Lexical similarity measures and evaluation metrics
Metrics based on syntactic matching
- Syntactic similarity measures and evaluation metrics
Metrics using shallow semantic matching
- Semantic similarity measures and evaluation metrics based on shallow semantics

This Corporate Training for Natural Language Processing (NLP) with Python is ideal for:

What Sets Us Apart?

Natural Language Processing (NLP) with Python Corporate Training Prices

Our Natural Language Processing (NLP) with Python training for enterprise teams is tailored to your specific upskilling needs. Explore transparent pricing options that fit your training budget, whether you're training a small group or a large team. Discover more about our Natural Language Processing (NLP) with Python training cost and take the first step toward maximizing your team's potential.

Request for a quote to know about our Natural Language Processing (NLP) with Python corporate training cost and plan the training initiative for your teams. Our cost-effective Natural Language Processing (NLP) with Python training pricing ensures you receive the highest value on your investment.

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Our customized corporate training packages offer various benefits. Maximize your organization's training budget and save big on your Natural Language Processing (NLP) with Python training by choosing one of our training packages. This option is best suited for organizations with multiple training requirements. Our training packages are a cost-effective way to scale up your workforce skill transformation efforts..

Starter Package

125 licenses

64 hours of training (includes VILT/In-person On-site)

Tailored for SMBs

Target Audience for Natural Language Processing (NLP) with Python Training Course

The Natural Language Processing (NLP) with Python training course is ideal for data analysts, software developers, data engineers, business analysts, researchers, and data scientists.

The Natural Language Processing (NLP) with Python training program can also be taken by professionals at various levels in the organization.

Natural Language Processing (NLP) with Python training for managers

Natural Language Processing (NLP) with Python training for staff

Natural Language Processing (NLP) with Python training for leaders

Natural Language Processing (NLP) with Python training for executives

Natural Language Processing (NLP) with Python training for workers

Natural Language Processing (NLP) with Python training for businesses

Natural Language Processing (NLP) with Python training for beginners

Natural Language Processing (NLP) with Python group training

Natural Language Processing (NLP) with Python training for teams

Natural Language Processing (NLP) with Python short course

Prerequisites for Natural Language Processing (NLP) with Python Training

Professionals with basic Python programming skills can take the Natural Language Processing (NLP) with Python training course.

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Bringing you the Best Natural Language Processing (NLP) with Python Trainers in the Industry

The instructor-led Natural Language Processing (NLP) with Python training is conducted by certified trainers with extensive expertise in the field. Participants will benefit from the instructor's vast knowledge, gaining valuable insights and practical skills essential for success in Natural Language Processing (NLP) with Python Access practices.

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Training Delivery Modes for Natural Language Processing (NLP) with Python Group Training

At Edstellar, we understand the importance of impactful and engaging training for employees. To ensure the training is more interactive, we offer Face-to-Face onsite/in-house or virtual/online Natural Language Processing (NLP) with Python training for companies. This method has proven to be the most effective, outcome-oriented and well-rounded training experience to get the best training results for your teams.

Virtual

Instructor-led Training

Engaging and flexible online sessions delivered live, allowing professionals to connect, learn, and grow from anywhere in the world.

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On-Site

Instructor-led Training

Customized, face-to-face learning experiences held at your organization's location, tailored to meet your team's unique needs and objectives.

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Off-site

Instructor-led Training

Interactive workshops and seminars conducted at external venues, offering immersive learning away from the workplace to foster team building and focus.

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Corporate Natural Language Processing (NLP) with Python Training Course

Drive Team Excellence with Natural Language Processing (NLP) with Python Training for Employees

Key Skills Employees Gain from Natural Language Processing (NLP) with Python Training

Natural Language Processing (NLP) with Python Training for Employees: Key Learning Outcomes

Key Benefits of the Natural Language Processing (NLP) with Python Corporate Training

Natural Language Processing (NLP) with Python Training Topics and Outline

Basics of Text Processing

Statistical Language Modeling

Morphological Modeling

Syntactic Analysis

Semantic Analysis

Sentiment Analysis

Information Retrieval

Discourse Analysis

Evaluation of NLP Systems – Analyzing Performance

This Corporate Training for Natural Language Processing (NLP) with Python is ideal for:

What Sets Us Apart?

Natural Language Processing (NLP) with Python Corporate Training Prices

Target Audience for Natural Language Processing (NLP) with Python Training Course

Prerequisites for Natural Language Processing (NLP) with Python Training

Assess the Training Effectiveness

Bringing you the Best Natural Language Processing (NLP) with Python Trainers in the Industry

Request a Training Quote

Training Delivery Modes for Natural Language Processing (NLP) with Python Group Training

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