Summarizing & Classifing Data using IBM Granite

A significant portion of data today is text-based, including customer messages, online reviews, and reports. Because this data is unstructured, sorting through it and making sense of it can quickly become overwhelming. Generative artificial intelligence (AI) helps address this challenge by organizing, classifying, and summarizing unstructured text to gain insights that lead to better outcomes.

Welcome to this course! In this course, you'll learn how generative AI simplifies specific tasks. You'll discover how to install and run a generative AI model - in our case, IBM Granite - locally on your own laptop, without any subscriptions, accounts, or data collection. This lets you classify and summarize unstructured data such as text.

You'll also learn how to control these models effectively using prompts. Along the way, we'll explore various sample prompts that you can use directly in your own work.

The course is divided into two parts: the first focuses on summarizing text with AI, and the second focuses on classifying data.

• Classifiying & summarizing text-based data with generative AI
• IBM Granite models for classifying & summarizing data
• Prompting IBM Granite for text classification & summarization
• Simulation: Prompting IBM Granite models for text classifying & summarization

Upon course completion, you will be able to...

• Explain how to train IBM Granite models to summarize data
• Summarize the role of generative AI in simplifying data classification tasks
• Summarize and classify text-based data using an IBM Granite model
• Compare prompts for summarizing and classifying text-based data in IBMGranite models and design them to be as effective as possible

• No specific requirements necessary.