In this module, you will learn the fundamentals of prompt engineering to interact effectively with generative AI models. You'll understand the concept of few-shot prompting and practice basic prompting techniques using context and examples. Building on this, you'll learn methods for improving prompts through personas, detailed instructions, and iteration based on feedback. Finally, you'll explore more advanced skills like breaking down tasks, chaining prompts, and other useful techniques to overcome context limitations.

In this module, you will explore different types of generative AI applications, including API-based, embedded model, and multi-model systems. You'll learn the fundamentals of building robust applications using techniques like Retrieval Augmented Generation (RAG) to improve context. Through hands-on exercises, you'll gain experience testing an application locally and deploying it on the cloud.

Here, you will learn the key capabilities of the OpenAI API. You will generate images with OpenAI’s DALL-E, “fine tuning” LLM models to Reddit questions and answers and summarize videos with OpenAI’s Whisper Model.