Course
Natural Language Processing (NLP) in Python
IntermediateSkill Level
Updated 07/2025PythonArtificial Intelligence4 hr13 videos42 Exercises3,550 XP6,918Statement of Accomplishment
Create Your Free Account
or
By continuing, you accept our Terms of Use, our Privacy Policy and that your data is stored in the USA.Loved by learners at thousands of companies
Training 2 or more people?
Try DataCamp for BusinessCourse Description
Build a Strong NLP Foundation
Unlock the power of Natural Language Processing (NLP) and take your text analysis skills to the next level! This course equips you with essential tools to process, analyze, and extract insights from text data. Start with the fundamentals of text processing, from tokenization to cleaning and normalizing text by removing stop words, punctuation, and applying lemmatization and stemming to improve text consistency.Extract Meaningful Features from Text
Go beyond raw text and transform it into numerical representations! Explore the Bag-of-Words representation, dive into TF-IDF vectorization, and leverage powerful word embeddings like Word2Vec and GloVe to capture semantic relationships between words.Classify and Generate Text with AI
Harness the power of state-of-the-art transformer models using Hugging Face pipelines. Learn how to perform sentiment analysis, classify content, analyze question-answer relationships, assess grammatical acceptability, and generate text using various models. Explore Named Entity Recognition (NER), Part-of-Speech (PoS) tagging, text summarization, and translation to expand your NLP toolkit.Master key NLP libraries
By the end of this course, you’ll have a strong grasp of NLP fundamentals and hands-on experience with key libraries such as nltk, sklearn, gensim, and Hugging Face’s transformers. Start your journey today and transform the way you interact with text data!Prerequisites
Python Toolbox1
Text Processing Fundamentals
Learn the essentials of text processing in Natural Language Processing (NLP). Master techniques such as tokenization, stop word and punctuation removal, and text normalization with lowercasing, stemming, and lemmatization to prepare text data for further analysis and insight extraction.
2
Feature Extraction from Text
Transform raw text into powerful numerical features. Create Bag-of-Words and TF-IDF representations to capture word importance across documents, then explore word embeddings like Word2Vec and GloVe to uncover deep semantic patterns. Visualize frequency, relevance, and similarity to bring your text data to life.
3
Text Classification with Hugging Face
Harness the power of pre-trained models to perform advanced text classification tasks. Use Hugging Face pipelines for sentiment analysis, topic classification, and natural language inference. Evaluate semantic similarity and grammatical correctness with state-of-the-art models, all without building anything from scratch.
4
Token Classification and Text Generation
Dive into the core of modern NLP applications with token classification and text generation techniques. Learn to extract meaningful entities and grammatical structures using NER and PoS tagging. Master both extractive and abstractive question answering, and explore advanced generation tasks including summarization, translation, and language modeling using Hugging Face pipelines.
Natural Language Processing (NLP) in Python
Course Complete
Earn Statement of Accomplishment
Add this credential to your LinkedIn profile, resume, or CVShare it on social media and in your performance reviewEnroll Now
FAQs
What will I learn in this course?
You'll master essential NLP techniques from text preprocessing to advanced transformer models. Learn tokenization, lemmatization, feature extraction with TF-IDF and embeddings, and apply Hugging Face models for sentiment analysis, classification, and text generation.
Who is this course intended for?
This course suits Data Analysts, Data Scientists, Machine Learning Scientists, and Programmers seeking NLP skills. Intermediate Python knowledge is recommended for optimal learning outcomes.
What is Natural Language Processing, and why is it important?
NLP enables computers to understand and process human language. It powers chatbots, sentiment analysis, content classification, and text-based insights that drive modern business decisions across industries.
How will this course help me in my career?
You'll gain skills to analyze customer feedback, build recommendation systems, and create AI-powered text applications. NLP expertise is highly sought as organizations increasingly leverage text data for competitive advantage.
What Python libraries will I use in this course?
You'll work with industry-standard tools including NLTK for preprocessing, scikit-learn for feature extraction, and Hugging Face Transformers for implementing modern language models in real-world applications.
Join over 19 million learners and start Natural Language Processing (NLP) in Python today!
Create Your Free Account
or
By continuing, you accept our Terms of Use, our Privacy Policy and that your data is stored in the USA.Grow your data skills with DataCamp for Mobile
Make progress on the go with our mobile courses and daily 5-minute coding challenges.