In this course, "End-to-End Natural Language Processing", you will learn about text data and how to process textual data using state-of-the-art AI tools. This course covers everything you need to know about natural language processing and various tasks. You will also learn about leveraging large language models for NLP, how to perform Prompt Engineering and Retrieval Augmented Generation, and how to create your own tiny AI models for specific tasks.

In this course, you will engage in hands-on activities, homework, and instructor consulting to make learning natural language processing enjoyable and rewarding. You will also be able to tackle real-world problems in natural language processing. By the end of this course, you’ll have the skills and confidence to tackle any task with natural language processing.

This course is one of 6 courses in the Foundations in AI pilot Micro-Credential pathway offered by the Translational AI Center at Iowa State University.

For more information regarding the course including: Learning Outcomes, Assessments, and a Course Outline please visit the End-to-End Natural Language Processing course page from Iowa State Online.

Prerequisite

• Basic Python programming
• Basic understanding of deep learning
• Basic PyTorch programming

Intended Audience
The course is intended for a broad audience within the spectrum of the software and technology industry, including software engineers, data scientists, data engineers, data analysts, research scientists, and software developers. The course is designed to provide a basic understanding of AI and how to use PyTorch for a broad range of audiences.