Lesson
Introduction to Generative AI
Generative AI is a type of artificial intelligence that can create new content, such as text, images, or audio, from a given prompt. It is able to accomplish this by using Large Language Models (LLMs). LLMs operate much like a highly advanced autocomplete function. By analyzing training data, LLMs predict the next likely token in a sequence to produce a realistic output.
A token is the fundamental unit an LLM predicts. For text-based outputs, a token can be thought of as a word, but for image or video generation, a token can represent a single pixel or next frame in the video sequence.
What You Will Learn in This Course
In this course, you will discover core concepts of generative AI, prompt and context engineering, and how you can use them to help you achieve optimal performance from your AI models.
By the end of this course, you’ll be able to:
- Explain the function of a token in the context of large language models (LLMs) and generative AI
- Explain the importance of prompt engineering
- Demonstrate the most common prompt engineering techniques
- Explain the importance of context engineering
- Explain the difference between reasoning models and traditional LLMs
- Describe the key components of an Agentic AI system, including tools, memory, and planning
You can take this course individually, or as a part of the AI Fundamentals learning path. Completing the full path prepares you for the AI Foundations certification, which validates your expertise in the topic. Learn more about the Braze AI Fundamentals Certification on Braze Learning.