Text Analytics

About This Course

Most business data, such as emails, social media posts, and surveys, are text-based. These texts are treasure troves of insights waiting to be unlocked. To stay competitive, businesses must expand their analytical capabilities to include text data, especially customer feedback and social media interactions. This course provides you with the skills to analyze large volumes of textual data, uncovering themes, patterns, and insights that drive decision-making and process improvements. It covers foundational concepts and the application of advanced machine learning techniques, such as topic modeling and word embeddings. With the growing adoption of technologies like Generative AI, the course also explores how Large Language Models (LLMs) are used in text analytics. Learners will gain practical experience in applying language models to key text mining tasks such as creating vector representation of text data, classifying text documents, extracting entities, relationships, and events from text data, etc. By combining theoretical knowledge with hands-on practice, this course enhances learners’ data analysis capabilities, enabling them to implement text mining algorithms and leverage state-of-the-art frameworks for real-world text analytics using machine learning techniques and LLMs.