This NLP Zero to Hero course introduces the fundamental concepts of Natural Language Processing (NLP) and demonstrates how deep learning techniques can be used to understand and generate human language. It is designed for beginners who want to learn how modern AI systems process text data.
The course starts with tokenization, one of the most important NLP preprocessing techniques. You will learn how text is broken into tokens and transformed into a format that machine learning models can understand. It then covers sequencing, where sentences are converted into numerical representations suitable for neural network training.
As the course progresses, you will build a sentiment analysis model capable of identifying positive and negative emotions within text data. This provides hands-on experience with one of the most common NLP applications used in business and social media analytics.
The course also introduces Recurrent Neural Networks (RNNs), which are designed to process sequential data such as text. You will learn how Long Short-Term Memory (LSTM) networks improve the ability of models to capture long-range dependencies within language.
In the final project, you will train an AI model to generate poetry, demonstrating how neural networks can create human-like text. By the end of the course, you will understand key NLP concepts and how deep learning powers modern language applications.
