Natural Language Processing (NLP) Courses and Certifications

Introduction to Natural Language Processing

5 ratings at Udacity

This section provides an overview of the program and introduces the fundamentals of Natural Language Processing through symbolic manipulation, including text cleaning, normalization, and tokenization. You'll then build a part of speech tagger using hidde…

• Udacity
• 11 hours
• Self-Paced
• Paid Course

Natural Language Processing in Python

Turn unstructured text and audio into insights: preprocess text, score review sentiment, train spaCy models, and transcribe speech with NLTK, scikit-learn, and SpeechRecognition.

• DataCamp
• 20 hours
• Self-Paced
• Free Trial Available

Computing With Natural Language

Learn advanced techniques like word embeddings, deep learning attention, and more. Build a machine translation model using recurrent neural network architectures.

• Udacity
• 25 hours
• Self-Paced
• Paid Course

Great Learning

Natural Language Processing Tutorial - NLP Training for Beginners - How Does NLP Work?

Learn NLP fundamentals by preprocessing and vectorizing text to build a language detection model.

• YouTube
• 1 hour 3 minutes
• Self-Paced
• Free Video

Graham Neubig

Introduction to Natural Language Processing - CMU Advanced NLP Fall 2024 - Lecture 1

An introduction to NLP that examines why natural language is difficult to process, then illustrates the field with a bag-of-words text classifier.

• YouTube
• 1 hour 14 minutes
• Self-Paced
• Free Video

Asia Open RAN Academy

Natural Language Processing Fundamentals - Introduction to NLP Concepts and Applications

An introductory look at how machines process human language, with NLP concepts connected to chatbots and translation tools.

• YouTube
• 1 hour 12 minutes
• Self-Paced
• Free Video

Asia Open RAN Academy

Essential Natural Language Processing (NLP) Tasks and Applications

A concise tour of the tasks that help machines process human language, from tokenization and tagging to sentiment analysis and translation.

• YouTube
• 13 minutes
• Self-Paced
• Free Video

Natural Language Processing in TensorFlow

6538 ratings at Coursera

Build NLP systems in TensorFlow: tokenize text with Tokenizer and pad_sequences, train word embeddings for movie-review sentiment, and generate poetry with RNNs, GRUs and LSTMs.

• Coursera
• 4 weeks, 6 hours a week
• Self-Paced
• Paid Course

Collecting and Preparing Textual Data for Classification

Collect and clean text data for classification: load 20 Newsgroups categories, clean with regex, remove stop words, stem, generate n-grams, and apply NER with POS tagging.

• CodeSignal
• 5 hours
• Self-Paced
• Free Certificate

Modern Tokenization Techniques for AI & LLMs

Implement rule-based and subword tokenization methods, comparing BPE, WordPiece, and SentencePiece for modern NLP models.

• CodeSignal
• 1 hour
• Self-Paced
• Free Certificate

Python ML Advanced

Apply NLP in Flask web apps by cleaning text, performing sentiment analysis, and building a movie recommendation system.

• CreativeLive
• 30 hours
• 15th Oct, 2026
• Paid Course

Career Certificate

Python Machine Learning Advanced

Build production-ready NLP applications with Flask, including sentiment analysis and a TF-IDF recommendation engine.

• VDCI
• 30 hours
• Self-Paced
• $1,895.00

Career Certificate

Introduction to Natural Language Processing

1 rating

Learn to explore and preprocess text, apply TF-IDF vectorization, and build and evaluate machine-learning classifiers in Python.

• CodeSignal
• 10 hours
• Self-Paced
• Free Certificate
• 4 courses

Natural Language Processing with Classification and Vector Spaces

4647 ratings at Coursera

This is the Course 1 of the Natural Language Processing Specialization, offered by deeplearning.ai

• Coursera
• 4 weeks, 8 hours a week
• Self-Paced
• Paid Course

Career Certificate

Natural Language Processing

6208 ratings at Coursera

Build NLP applications for sentiment analysis, question answering, machine translation and text summarization using classification, vector spaces, probabilistic models, sequence models and attention models.

• Coursera
• 12 weeks, 10 hours a week
• Self-Paced
• Paid Course
• 4 courses