Natural Language Processing Skills
Advanced NLP course covering text preprocessing, tokenization, named entity recognition, sentiment analysis, text summarization, translation, and practical machine learning pipelines for processing and understanding human language.
Course Content (8 lessons)
Raw text is messy. It contains typos, inconsistent capitalization, special characters, and formatting that adds noise without inform
Tokenization is the process of breaking text into meaningful units called tokens. Tokens can be words, subwords, characters, or se
Named Entity Recognition (NER) identifies and classifies named entities in text—people, organizations, locations, date
Sentiment analysis determines the emotional tone, attitude, or opinion expressed in text. Opinions can be positive ("This is a
Text summarization creates concise, informative summaries from longer source material. With exponential growth in text data, summariza
Machine translation converts text from one language to another. This lesson covers translation approaches, pre-trained
Text classification assigns documents to predefined categories. Applications include spam detection, topic categorization, intent classi
Individual NLP techniques are building blocks. Real-world systems combine multiple techniques into pipelines that extract value