Cloud Machine Learning for Natural Language Processing Module

Natural language processing (NLP) is a critical component of artificial intelligence that enables computers to understand, interpret, and generate human language. This course builds on foundational machine learning knowledge to explore how NLP can solve complex business problems and drive innovation in various industries.

Through this course, you will gain practical experience in applying machine learning techniques to NLP tasks, from text extraction and sentiment analysis to topic modelling and generative AI.

What you will learn:

• to describe the principles and applications of natural language processing (NLP)
• to implement a machine learning pipeline for NLP tasks
• to develop solutions for text extraction, sentiment analysis, and topic modelling
• to utilise generative AI and large language models (LLMs) for advanced NLP applications

By the end of this module, you will be able to:

• design and deploy NLP models to solve business problems
• process and analyse text data for machine learning applications
• implement and optimize various NLP algorithms
• integrate generative AI and LLMs into NLP solutions

Teaching methods

This course is fully online and self-paced. Learning materials consist of pre-recorded lecture videos, hands-on lab exercises, and multiple-choice knowledge checks to ensure comprehensive understanding.

Intended audience

This intermediate-level course is intended for students pursuing careers in data science, machine learning, and artificial intelligence. To ensure success in this course, you should have:

• completed a foundational machine learning course
• intermediate skills with Python programming
• a general knowledge of applied statistics
• familiarity with ML concepts and distributed systems