
Explore prompt engineering to design clear, specific prompts that elicit useful output from generative AI and LLMs. Learn iteration, few-shot prompting, and evaluating results for workplace impact.
Understand how large language models learn from text data to predict the next word and generate responses to prompts, while noting bias and hallucinations and the need for critical evaluation.
Experiment with prompting to unlock conversational ai capabilities, crafting prompts for evaluation and training of models with bard and duet ai.
Learn how prompt engineering improves large language model outputs by writing clear, specific prompts with relevant context, using iterative refinement to guide LLMs toward useful results.
Leverage an LLM at work to boost productivity and creativity through outlines for articles, summarization, classification, extraction, translation, and editing, guided by action-oriented prompts like create, summarize, classify, and edit.
Iterative prompting and prompt engineering refine AI outputs, evaluating responses for accuracy, bias, relevance, and consistency across different LLMs.
Explore few-shot prompting and the use of multiple examples to steer LLMs, comparing zero-shot and one-shot approaches, and shaping prompts for desired style and format.
Explore prompting strategies by iterating with varied prompts to guide LLM responses. Balance creativity and specificity with context and chain-of-thought prompts, and test reactions to own outputs to improve accuracy.
Learn to craft clear and specific prompts, use few-shot prompting with examples to guide the large language model, and iterate to improve outputs for workplace tasks.
This course is part of the Google AI Essentials program. In our daily lives, the way we phrase our words directly affects how others respond; the same is true when communicating with artificial intelligence. This course introduces you to prompting, the practice of designing instructions that elicit the most useful results from generative AI. You will discover that a prompt is more than just a question; it is a text input that provides the necessary context and instructions for an AI model to generate high-quality output.
The curriculum begins with the mechanics of Large Language Models (LLMs). You will learn how these models are trained on millions of sources to identify patterns and use statistics to predict the most likely word to come next in a sequence. To help you master these tools, you will learn to "Thoughtfully Create Really Excellent Inputs" by being clear and specific about your intended task. You will explore specialized strategies like few-shot prompting, which involves providing two or more examples to guide the AI’s style and format.
Because you rarely get the perfect result on your first try, you will learn to use an iterative process: creating a prompt, evaluating it for accuracy and bias, and refining your prompt for the next draft. You will also unlock techniques for mastering complex work, such as chain-of-thought prompting - asking the AI to "show its work" by explaining its reasoning step-by-step - and prompt chaining, which breaks large projects into a series of smaller, connected tasks.
When you enroll in this course, you'll also be enrolled in the full certificate path.




