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Prompt Engineering Foundations · LearnSpace
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Prompt Engineering Foundations

Курс от Packt
Средний≈ 6.2 чАнглийский
О курсеНавыкиПрограммаПреподаватели

О курсе

This course features Coursera Coach! A smarter way to learn with interactive, real-time conversations that help you test your knowledge, challenge assumptions, and deepen your understanding as you progress through the course. In this comprehensive course, you will gain a solid foundation in prompt engineering, learning how to work with large language models (LLMs) effectively. You'll explore the power of prompt engineering and how to build AI-powered tools by interacting with APIs such as OpenAI and Anthropic. Through real-world examples and hands-on projects, this course will help you master the art of developing prompts that maximize the capabilities of AI models. As you move through the course, you will be guided step by step through key concepts, including setting up development environments, making your first API calls, and managing API costs. You will also delve into advanced techniques for controlling output, managing authentication, and optimizing large language models for real-time applications. Each section is designed to build your skills progressively, ensuring that you gain the practical experience needed to excel. The course culminates in a project where you will apply what you’ve learned by creating your own AI-powered tools using the skills and knowledge gained throughout the course. By the end of the course, you will have built the foundation for an AI toolbox and will have the expertise to use prompt engineering in your own projects. This course is ideal for anyone interested in learning prompt engineering, whether you're an aspiring AI developer, a data scientist, or someone who wants to gain hands-on experience in using APIs for AI-driven applications. It requires a basic understanding of programming but is accessible to beginners with a technical background. By the end of the course, you will be able to set up your development environment, make API calls, use the OpenAI Python library, build command-line interfaces, and create AI-powered tools using best practices.

Навыки, которые вы освоите

OpenAI APIDevelopment EnvironmentOpenAIKey ManagementApplication Programming Interface (API)Anthropic ClaudeLarge Language ModelingToken OptimizationLLM ApplicationCommand-Line InterfaceVirtual EnvironmentAuthenticationsPrompt EngineeringPrompt Engineering ToolsPython Programming

Программа курса

4 модулей · 38 учебных материалов

01Getting Started with Prompt Engineering8 материалов

Getting Started with Prompt Engineering

Introduction to the Course 'Prompt Engineering Foundations'ЧтениеFull Specialization ResourcesЧтениеWelcome and Course OverviewВидеоThe Value of Prompt Engineering SkillsВидео

Учитесь у экспертов

Packt - Course Instructors

Преподаватель курса

Prompt Engineering Foundations
В каталоге вашей программы

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Начать на Coursera

Обучение откроется на Coursera
в новой вкладке

Обучение на Coursera

≈ 6.2 ч

4 модулей

Язык: Английский

Субтитры: Арабский, Французский, Итальянский, Бразильский португальский, Корейский, Немецкий, Пушту, Индонезийский, Испанский, Дари, Японский

Часть программы вашего университета
Setting ExpectationsВидео
Introducing the Course ProjectВидео
Exploring the Project ModulesВидео
Overview of OpenAI API CostsВидео
02Setting Up Your Development Environment6 материалов

Setting Up Your Development Environment

Section OverviewВидеоConfiguring Your Local Python EnvironmentВидеоSetting Up Your OpenAI Account and KeysВидеоSetting Up Your Anthropic Account and KeysВидеоSetting Up Python and API Keys for OpenAI & AnthropicDIALOGUESetting Up Your Development Environment - AssessmentЗадание
03OpenAI Python Library Crash Course13 материалов

OpenAI Python Library Crash Course

Section OverviewВидеоEnvironment SetupВидеоManaging API Authentication SecurelyВидеоMaking Your First API Call to a Chat ModelВидеоSimplifying LLM Calls with LiteLLMВидеоConnecting to Anthropic Models via LiteLLMВидеоUnderstanding and Parsing the API ResponseВидеоControlling Creativity and Length with Temperature and max_tokensВидеоFine-Tuning Output with stop, n, and response_formatВидеоImplementing Real-Time Responses with StreamingВидеоHow to Run Large Language Models Locally with OllamaВидеоComparing Blocking vs. Streaming API Calls with OpenAI and lightLLMDIALOGUEOpenAI Python Library Crash Course - AssessmentЗадание
04Project Module #1: Building the AI Toolbox Foundation11 материалов

Project Module #1: Building the AI Toolbox Foundation

Module Overview and GoalsВидеоCreating the Initial Project StructureВидеоA Guided Tour of the Starter CodeВидеоBuilding the Command-Line Interface with ClickВидеоImplementing an AI-Powered "Hello World"ВидеоWriting Your First Test for the AI FeatureВидеоScaffolding and Enhancing a Modern Python AI CLI ProjectDIALOGUEConclusion to the Course 'Prompt Engineering Foundations'ЧтениеProject Module #1: Building the AI Toolbox Foundation - AssessmentЗаданиеFull Course Practice AssessmentЗаданиеFull Course AssessmentЗадание