The 9 best Natural Language Processing courses in 2026

This course introduces the foundational concepts of large language models (LLMs) and deep learning techniques for text analysis, a critical skill set in today’s AI-driven landscape. As organizations increasingly rely on intelligent systems to process and interpret language data, understanding these technologies has become essential for modern professionals. Throughout the course, learners will explore how deep learning models analyze and extract meaning from textual data, gaining practical insights into real-world NLP applications. By studying the architecture and working principles of transf

The Machine Learning and NLP Basics course is a learning resource designed for individuals interested in developing foundational knowledge of machine learning (ML) and natural language processing (NLP). This course is ideal for students, data scientists, software engineers, and anyone seeking to build or strengthen their skills in machine learning and natural language processing. Whether you are starting your journey or seeking to reinforce your foundation, this course provides practical skills and real-world applications. Throughout this course, participants will gain a solid understandin

Are you curious about how chatbots hold conversations or how ChatGPT generates human-like responses? This course in Natural Language Processing (NLP) is your gateway into the fascinating world where language meets AI. Designed for students and professionals alike, the course blends essential theory with hands-on experience to equip you with the skills needed to build intelligent language systems. We start by unravelling what makes language so complex—and why teaching machines to understand it is such a challenging task. You’ll explore the inner workings of Natural Language Understanding (NLU)

The field of natural language processing (NLP) aims at getting computers to perform useful and interesting tasks with human language. This course introduces students to the 3 pillars underlying modern NLP: probabilistic language models, simple neural networks with a focus on gradient based learning, and vector-based meaning representations in the form of word embeddings. At the end of the course, students will be able to implement and analyze probabilistic language models based on N-grams, text classifiers using logistic regression and gradient-based learning, and vector-based approaches to wo

Five courses on neural networks, CNNs, sequence models, and ML strategy from DeepLearning.AI.

Build and train neural networks with TensorFlow for vision, NLP, and time series.

Free, top-down deep learning course — build state-of-the-art models from lesson one.

Sentiment analysis, machine translation, and attention models with DeepLearning.AI.

Free course on transformers, tokenizers, and fine-tuning models with the Hugging Face ecosystem.