Engineering LLM Output Size

Overview

This intermediate course focuses on manipulating output sizes from large language models (LLMs). From generating concise single words to expansive articles, learners will explore techniques for precise control over the length and detail of AI-generated content. This is crucial for tailoring responses to fit specific requirements in content creation, coding, and beyond.

Syllabus

Unit 1: Core Principles of Getting the Right Size from One Try

Transforming a Simplistic Prompt into a Structured Advertisement Tagline Prompt
Refining a Vague Request into a Detailed Guide for Eco-Friendly Brand Naming
Defining AI-Powered Tutoring in Three Sentences

Unit 2: Refining Prompts for Binary Code Verdicts

Analyzing Python Code for Palindrome Check
Confirm Keyword Presence in Python Code
Single-Word Response Evaluation Task

Unit 3: Crafting Single-Sentence Summaries with LLMs

Crafting a Single-Sentence Summary of Market Reactions to Interest Rate Hike
Generating a One-Sentence Explanation of Memoization's Impact on Fibonacci Calculations
Summarizing Sales Data Insights