Lemmatization Courses and Certifications

NLP - Natural Language Processing with Python

19719 ratings at Udemy

Learn to use Machine Learning, Spacy, NLTK, SciKit-Learn, Deep Learning, and more to conduct Natural Language Processing

• Udemy
• 11 hours 25 minutes
• On-Demand
• Paid Course

Natural Language Processing (NLP) in Python

Master text analysis with essential NLP techniques from preprocessing to advanced transformer models.

• DataCamp
• 4 hours
• On-Demand
• Free Trial Available

Microcredential

Token Classification in NLP using spaCy

7 ratings at CodeSignal

Master token classification techniques using spaCy, from building NLP pipelines to implementing practical applications. Learn linguistics fundamentals and apply your skills to real-world case studies.

• CodeSignal
• 7 hours
• On-Demand
• Free Certificate
• 3 courses

Foundations of NLP Data Processing

Master text cleaning, vectorization techniques (TF-IDF, embeddings), modern tokenization, and scalable data pipelines for NLP and LLMs through hands-on practice.

• CodeSignal
• 1 hour
• On-Demand
• Free Certificate

Building an NLP Pipeline with spaCy for Token Classification

Master essential NLP concepts and build efficient pipelines using spaCy, covering tokenization, POS tagging, and lemmatization while working with the Reuters corpus for practical token classification tasks.

• CodeSignal
• 3 hours
• On-Demand
• Free Certificate

U&P AI - Natural Language Processing (NLP) with Python

1149 ratings at Udemy

Become an NLP Engineer by creating real projects using Python, semantic search, text mining and search engines!

• Udemy
• 5 hours 50 minutes
• On-Demand
• Paid Course

Natural Language Processing (NLP) for Beginners Using NLTK

794 ratings at Udemy

Explore NLP fundamentals using NLTK, covering corpus usage, frequency distribution, stemming, lemmatization, and tokenization for beginners.

• Udemy
• 43 minutes
• On-Demand
• Free Online Course

The Ultimate Beginners Guide to Natural Language Processing

662 ratings at Udemy

Learn step-by-step the main concepts of natural language processing in Python! Build a sentiment classifier!

• Udemy
• 6 hours 5 minutes
• On-Demand
• Paid Course

Machine learning and Lexicon approach to Sentiment analysis

50 ratings at Udemy

Machine learning and Lexicon based approach to Sentiment analysis using Twitter API

• Udemy
• 3 hours 25 minutes
• On-Demand
• Paid Course

Edureka Microcredential

Mastering NLP: Tokenization, Sentiment Analysis & Neural MT

7 ratings at Coursera

Master essential and advanced NLP techniques from tokenization to neural translation, building intelligent language-aware systems for real-world applications.

• Coursera
• 16 weeks, 5 hours a week
• On-Demand
• Paid Course
• 3 courses

Edureka

Natural Language Processing Essentials

Discover NLP fundamentals through hands-on Python programming, covering text preprocessing, feature extraction, and building models for classification and entity recognition.

• Coursera
• 12 hours 55 minutes
• On-Demand
• Paid Course

Packt Microcredential

Applied NLP and Generative AI

Master practical NLP and Generative AI skills using Python, from text preprocessing to transformer fine-tuning and deploying real-world applications like chatbots.

• Coursera
• 4 weeks, 10 hours a week
• On-Demand
• Paid Course
• 3 courses

Packt

NLP – Embeddings & Text Preprocessing in Python

Master the essentials of NLP with text preprocessing techniques, vector models, and neural word embeddings. Learn to transform raw text into usable formats for machine learning through hands-on Python implementations.

• Coursera
• 9 hours 22 minutes
• On-Demand
• Paid Course

EDUCBA

Chatbots with Keras & NLP: Build & Evaluate

Master chatbot development using Keras & NLP techniques, from text preprocessing to advanced neural architectures with attention mechanisms for real-world AI applications.

• Coursera
• 7 hours 19 minutes
• On-Demand
• Paid Course

EDUCBA

Apply Natural Language Processing Techniques in Python

Master NLP fundamentals and advanced text preprocessing techniques, then integrate machine learning algorithms to build effective models for real-world language problems.

• Coursera
• 4 hours 42 minutes
• On-Demand
• Paid Course