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Agent Foundations and Prompt Engineering · LearnSpace
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Agent Foundations and Prompt Engineering

Курс от Board Infinity
Средний≈ 21.2 чАнглийский
О курсеНавыкиПрограммаПреподаватели

О курсе

Agent Foundations and Prompt Engineering is designed for learners eager to master the emerging field of AI agents and advanced prompt engineering. You'll learn how to design, build, and deploy intelligent AI agents using large language models (LLMs), craft high-quality prompts for various tasks, and automate complex workflows through programmatic execution and chaining. To begin with, you'll explore the fundamentals of AI agents, including their structure, behaviors, and real-world applications. You'll understand how LLMs enable agent intelligence and compare different agent architectures from reactive systems to sophisticated tool-using agents. The next module focuses on prompt engineering, where you'll learn to craft effective prompts using proven patterns like few-shot learning, chain-of-thought reasoning, and role prompting. You'll master the art of structuring prompts for optimal model performance and develop systematic evaluation strategies. In the third module, you'll advance to programmatic prompt execution and chaining. You'll build multi-step workflows, integrate Python code with LLM APIs, handle errors gracefully, and create production-ready prompt systems with proper debugging and monitoring. The final module teaches you to automate research and summarization tasks. You'll build end-to-end pipelines for collecting, processing, and summarizing information, implement both extractive and abstractive summarization methods, and evaluate outputs using comprehensive quality metrics. By the end of this course, you will confidently: • Design and implement AI agents for real-world automation and decision-making tasks • Craft effective prompts using advanced patterns and systematic evaluation methods • Build chained prompt workflows with robust error handling and programmatic control • Develop automated research and summarization systems with quality assessment frameworks Disclaimer: This is an independent educational resource created by Board Infinity for informational and educational purposes only. This course is not affiliated with, endorsed by, sponsored by, or officially associated with any company, organization, or certification body unless explicitly stated. The content provided is based on industry knowledge and best practices but does not constitute official training material for any specific employer or certification program. All company names, trademarks, service marks, and logos referenced are the property of their respective owners and are used solely for educational identification and comparison purposes.

Навыки, которые вы освоите

Prompt EngineeringAI OrchestrationAgentic systemsLLM ApplicationAgentic WorkflowsArtificial Intelligence and Machine Learning (AI/ML)DebuggingQuality AssuranceLarge Language ModelingVerification And ValidationGenerative AI AgentsTool CallingPrompt PatternsAI Workflows

Программа курса

4 модулей · 71 учебных материалов

01Introduction to AI Agents and Prompt-Driven Systems18 материалов

What Are AI Agents?

Introduction to Agentic AI ВидеоEvolution of AI Systems ВидеоCore Characteristics of Agentic SystemsВидеоAgent Loop Patterns and AbstractionsЧтение

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Board Infinity

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Agent Foundations and Prompt Engineering
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Обучение откроется на Coursera
в новой вкладке

Обучение на Coursera

≈ 21.2 ч

4 модулей

Язык: Английский

Субтитры: Арабский, Французский, Итальянский, Бразильский португальский, Корейский, Испанский, Японский

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AI Agent Ecosystem & Career PathwaysЧтение
Practice Quiz : What Are AI Agents?Задание

Agent Architectures and Behaviors

Real-World Use Cases ВидеоAgent Loop Overview ВидеоDeep Dive Into Each Loop Stage ВидеоArchitecture Patterns Cheat-SheetЧтениеPractice Quiz : Agent Architectures and BehaviorsЗадание

Applications of AI Agents

Core Components: Policy, Memory, Tools, Environment ВидеоAgent Architectures Explained ВидеоBuild a Minimal Agent in Python ВидеоPractice Quiz : Applications of AI AgentsЗаданиеApplied Agent Case StudiesЧтениеGraded Quiz : Introduction to AI Agents and Prompt-Driven SystemsЗаданиеQuick Course Check-InPLUGIN
02Fundamentals of Prompt Engineering19 материалов

Prompt Structures and Templates

What Makes a Good Prompt?ВидеоPrompt Structure: Role, Task, ConstraintsВидеоFew-Shot Prompting: Learning from ExamplesВидеоPractice Quiz : Prompt Structures and TemplatesЗаданиеPrompt Templates Library & ExamplesЧтение

Prompt Patterns and Strategies

Chain-of-Thought: Guiding ReasoningВидеоWhy Structure Matters in PromptsВидеоFunction-Based Prompts for Tool UseВидеоPractice Quiz : Prompt Patterns and StrategiesЗаданиеReasoning Prompt Patterns Quick ReferenceЧтение

Evaluating Prompt Quality

What Makes a Prompt “Good” or “Bad”?ВидеоConsistency, Accuracy, and ReliabilityВидеоCommon Prompt Failure Patterns ВидеоPrompt Eval Checklist & TrackerЧтениеSystematic Prompt Debugging Видео Why Prompt Libraries MatterВидео
03Programmatic Prompt Execution and Chaining19 материалов

Prompt Chaining Basics

What Is Prompt Chaining?ВидеоWhen and Why to Use Prompt ChainsВидеоHands-On: Sequential Chaining in Python (Notebook Demo)ВидеоPractice Quiz : Prompt Chaining BasicsЗаданиеReading - Chaining Patterns & Code SnippetsЧтение

Dynamic Prompting with APIs

Building Your First ChainВидеоWhy Agents Need ToolsВидео Tool-Using Agent DemoВидеоPractice Quiz : Dynamic Prompting with APIsЗаданиеReading - API Chaining CookbookЧтение

Error Handling in Prompt Workflows

Why Memory MattersВидеоAdding Memory in PracticeВидеоWhy Chained Systems FailВидеоPractice Quiz : Error Handling in Prompt WorkflowsЗаданиеReading - Debugging Checklist & TemplatesЧтениеVisualizing and Debugging ChainsВидео
04Optimization, Debugging, and Observability15 материалов

Debugging RAG Pipelines

Project Overview & ArchitectureВидеоUnderstanding the Data LayerВидеоData Access Layer (Scraper)ВидеоPractice Quiz : Debugging RAG PipelinesЗаданиеReading - Building Text Summarizers Чтение

Observability and Tracing Tools

Review Analysis & Comparison with the SummarizeВидеоData Models Are ImportantВидеоThe Research AgentВидеоPractice Quiz : Observability and Tracing ToolsЗаданиеReading - Automating Research Workflows Чтение

Response Optimization

Running the SystemВидеоTesting & EvaluationВидеоPractice Quiz : Response OptimizationЗаданиеReading - Evaluating Summarization QualityЧтениеGraded Quiz : Optimization, Debugging, and ObservabilityЗадание
Organizing and Reusing Prompts Видео
Practice Quiz : Evaluating Prompt QualityЗадание
Graded Quiz : Fundamentals of Prompt EngineeringЗадание
Designing the Chained AgentВидео
End-to-End Build & RunВидео
Graded Quiz : Programmatic Prompt Execution and ChainingЗадание