Free NLP & Text Processing Learning Path

Complete natural language processing specialization covering transformers, attention mechanisms, and modern NLP techniques.

This course explores the application of Transformers in video understanding, with a focus on action recognition and instance segmentation, and covers recent developments in large-scale pre-training and multimodal learning.

This program is for finance professionals and operations managers, teaching how to apply machine learning, natural language processing, and predictive analytics to identify cost inefficiencies and develop mitigation strategies.

This course equips healthcare professionals and enthusiasts with practical AI skills to improve patient care and streamline operations. It covers AI fundamentals, machine learning, natural language processing, predictive analytics, and ethical healthcare practices. Learners will explore the application of AI in medical imaging, diagnostics, treatment planning, and personalized medicine while understanding compliance and regulatory standards.

This course teaches how to use Py Spark for streaming data processing and Natural Language Processing (NLP) applications. It is aimed at data professionals who want to build scalable data-streaming applications and perform advanced NLP tasks on large datasets.

This course focuses on using attention models in Natural Language Processing. You will learn how to build models that can focus on specific parts of an input sequence to improve performance on tasks like machine translation and text summarization.

This course explores the ethical challenges and complexities of AI's role in mental health, covering topics like bias, misinformation, privacy, and patient safety. It delves into advancements in computing, social robotics, and NLP techniques used in mental health analysis. The course is designed for mental health professionals, policymakers, and tech leaders.

This professional certificate teaches how to build and train deep learning models using PyTorch. It covers applying transfer learning and fine-tuning to pretrained models for computer vision and natural language processing.

This course teaches you how to use open-source models from the Hugging Face Hub for various tasks like NLP, audio, and image processing. You will learn to use the transformers library to perform these tasks with just a few lines of code and deploy your applications using Gradio and Hugging Face Spaces.

This course, developed in collaboration with Hugging Face, teaches the fundamentals of model quantization. You will learn to compress large models, making them more accessible and efficient, using the Hugging Face Transformers library and Quanto.

In this project-based course, students work to develop and evaluate a conversational system using a scientific approach, covering technologies like natural language processing and speech technology.

This course provides an in-depth understanding of conversational systems from both a theoretical and practical perspective. Topics include natural language processing, speech technology, multi-modal interfaces, and large language models.

Learn Transformers, explained: Understand the model behind GPT, BERT, and T5

Transformers for beginners | What are they and how do they work

Build neural networks from scratch in code. Start with backprop, build up to transformers and GPT. Former Tesla AI Director teaches you everything.

Learn TensorFlow 2.0 and Keras for deep learning. Build neural networks for computer vision, NLP, and time series prediction.

Stanford course on NLP with deep learning. Covers word embeddings, RNNs, attention, transformers, and BERT.