Module 5: Cohere Medium In-Context Learning via Prompt Engineering

This module focuses on utilizing the Cohere Medium foundation model to achieve in-context learning. This involves leveraging the model's natural language understanding (NLU) capabilities to personalize user's responses and improve their performance.

In this module, you will learn step-by-step how to perform NLU tasks using Cohere Medium. Specifically, you will learn how to engineer prompts that enable Cohere Medium to learn in-context and improve its performance, such as identifying named entities via few-shot learning. This will enhance the model's ability to infer context and answer questions, providing better responses to the user.

Overall, this module provides an excellent opportunity to explore the capabilities of Cohere Medium in solving NLU tasks, such as text summarization, abstractive question answering, named entity recognition, and other related tasks through the lens of in-context learning for the benefit of the user.