Advanced Certificate in Artificial Intelligence in the Digital Economy Module 3: Natural Language Processing and Sentiment Analysis (Synchronous E-Learning)

About This Course

This module provides a comprehensive understanding of how artificial intelligence (AI) techniques can be applied to analyse and understand human language. It covers the fundamental concepts of natural language processing (NLP) including tokenisation, stemming, lemmatisation, part-of-speech tagging, and syntactic parsing. Participants will also delve into sentiment analysis which involves using NLP techniques to determine the sentiment or emotional tone behind a piece of text. They will learn about various approaches to sentiment analysis such as lexicon-based methods, machine learning based methods, and deep learning models for sentiment classification. Furthermore, this module equips participants with practical skills in implementing NLP and sentiment analysis algorithms using popular libraries such as NLTK (Natural Language Toolkit), spaCy, and TensorFlow. Through hands-on projects and case studies, participants will gain valuable experience in applying these techniques to real-world problems in areas such as social media monitoring, customer feedback analysis, market research, and more. By the end of this module, participants will have developed a strong foundation in NLP and sentiment analysis within the context of AI applications in the digital economy. They will be able to leverage these skills to extract meaningful insights from textual data that can drive informed decision-making across various industries.