Description
Prompt Engineering for Developers: The Definitive Guide. This course provides a comprehensive guide to building practical and effective AI solutions using Large Language Models (LLMs). This course teaches developers how to go beyond simple interactions and engineer automated intelligent systems. You’ll master a core framework that includes structuring each prompt with clear instructions, context, and constraints to achieve reliable results. You’ll learn advanced techniques like defining personas to create expert assistants, using logical patterns like Chain-of-Thought and Decomposition to solve complex problems, and generating structured output like JSON. You’ll also learn how to connect the model to external tools and APIs through function calls so it can perform tasks like running linters or security scanners. This course covers designing interactive workflows where AI becomes a partner by actively asking questions. Finally, you’ll learn advanced techniques like Few-Shot Prompting and Meta-Prompting to improve outputs and even use an artificial intelligence to engineer more optimized prompts.
What you will learn
- Understand core LLM mechanics such as tokenization and text windows to build efficient and cost-effective solutions.
- Use advanced Prompt Engineering patterns such as Persona, Chain of Thought, and Self-Critique to solve complex problems.
- Engineering prompts that ensure reliable, machine-readable outputs such as JSON for use in automated systems.
- Implement function calls so that your AI application can run external tools such as linters and security scanners.
- Calculate and manage API costs for complex multi-step AI conversations and workflows.
- Write vendor-independent code with LiteLLM that can easily switch between OpenAI, Anthropic, and local models.
- Using AI coding agents like GitHub Copilot to speed up the software development workflow, from skeletonization to testing.
- Building a complete AI-powered CLI tool from scratch that generates intelligent commit messages and performs code reviews.
- Write comprehensive unit tests for AI-integrated code by effectively mocking external API calls and user input.
This course is suitable for people who:
- Any developer or technical professional looking to drastically increase their productivity when working with generative AI.
- DevOps engineers, SREs, and software developers looking to build automation and custom tools powered by AI.
- Engineers who want to go beyond basic chatbots and build reliable, production-ready, and testable solutions.
- Platform and tools teams tasked with creating intelligent internal tools to increase developer productivity.
- Technical professionals who aim to become leaders in the practical application of generative artificial intelligence to engineering challenges.
Course details: Prompt Engineering for Developers: The Definitive Guide
- Publisher : Udemy
- Teacher : Lauro Fialho Müller
- Language: English
- Level : All Levels
- Lectures : 120
- Duration : 16 hours and 8 minutes
Course syllabus
Prerequisites for the Prompt Engineering for Developers: The Definitive Guide course
- Familiarity with Python programming and its ecosystem (pip, virtual environments).
- Hands-on experience with Git for version control (add, commit, diff).
Course images
Sample course video
Installation Guide
After Extract, view with your favorite player.
Subtitles: English
Quality: 720p
The 2025/12 version has increased the number of lessons by 6 and the duration increased by 13 minutes compared to 2025/7.
Download link
Downloadly
Rapidgator
File(s) password: www.downloadly.ir
File size
10.13 GB
