本课程教你通过Python与OpenAI API/Ollama实战，掌握提示词工程、LLM链式工作流及企业级结构化输出。亲手构建智能求职Agent等商业项目，打造高薪AI工程师必备作品集，抢占2026年AI岗位机遇。
原始标题：AI Engineering Fundamentals: Build Real LLM Apps in Python
本课程通过 Python 与 OpenAI API / Ollama 的实战组合，专注于将学员培养为企业高薪急需的 AI 应用层工程师。你将从零开始掌握提示词工程、多步 LLM 链式工作流、多模态处理以及通过 Pydantic 实现企业级结构化输出的核心底层技术；并通过亲手构建诸如“智能求职 Agent”等涵盖数据抓取、分类、排序和自动化交付的完整商业级项目，搭建出能够直接向雇主证明交付能力的个人作品集，从而在2026年快速爆发的 AI 岗位潮中脱颖而出。
Published 7/2026
Created by Lukas Lechner
MP4 | Video: h264, 1920×1080 | Audio: AAC, 44.1 KHz, 2 Ch
Level: Beginner | Genre: eLearning | Language: English | Duration: 51 Lectures ( 6h 11m ) | Size: 3.8 GB
Become a job-ready AI Engineer with the OpenAI API, prompt engineering, structured outputs & real portfolio projects
What you’ll learn
⚡ Build and ship real AI applications with Python and the OpenAI API, from your very first LLM call to a finished portfolio project
⚡ Create a complete AI-powered Job Agent that scrapes job postings, classifies and ranks them with LLMs, and delivers the best matches to your inbox
⚡ Understand what AI Engineers actually do and which skills companies hire for, backed by an analysis of hundreds of real job postings
⚡ Build portfolio projects that prove your AI Engineering skills to employers, plus ideas for making your own projects stand out
⚡ Master prompt engineering: system vs. user prompts, instructions vs. input, and prompting techniques that make outputs reliable
⚡ Design multi-step AI workflows that chain LLM calls for classification, extraction, summarization, and matching
⚡ Structured Output with Pydantic
⚡ Run open-source LLMs locally on your own machine with Ollama
⚡ Work with multimodal models: analyze images, PDFs, and files, and generate images with AI
⚡ Understand tokens, model parameters, and pricing so you can choose the right model and keep API costs under control
Requirements
❗ Git Knowledge
❗ Familiar with at least one programming language. In the course we will use Python, which can be easily picked up by anybody who has at least experience in one programming language
❗ Buying $5 in Credits for the OpenAI API are recommended, but the course also shows how to use local models for free instead.
Description
“The AI engineer will likely be the highest-demand engineering job of the decade.”
That’s the prediction from the platform Latent Space.
And the data backs it up: LinkedIn’s 2026 “Jobs on the Rise” report ranks AI Engineer as the#1 fastest-growing role in the world.
Companies are desperately looking for AI Engineers. Yet most developers don’t even know what AI Engineering actually is. That’s your opportunity. And this course is designed to help you take it: it turns you from a developer into a job-ready AI Engineer.
What makes this course different?
Most AI courses are full of theory, math, statistics, and machine learning. This course is not. As an AI Engineer, you don’t train models from scratch. You build applications on top of powerful existing models. You sit on the product side of the API. So that’s what we focus on: integrating LLMs into real applications.
I analyzed hundreds of real AI Engineer job postings to find out which skills companies are actually hiring for. The best part: we run this analysis together in the very first module, with an AI-powered workflow that we build ourselves. You’ll be building with AI from day one.
What we build together
Knowing the right skills isn’t enough. To get hired, you need to PROVE you have them. And the most convincing proof is a portfolio project you have built yourself.
So we build one together, from start to finish: an AI-powered Job Agent that scrapes AI Engineering job postings, summarizes each role and company, matches every job against your personal profile, and sends the best matches straight to your email inbox.
Along the way, you will learn
✨ Talking to LLM APIs, mainly the OpenAI API
✨ Running local models on your own machine with Ollama
✨ Prompt engineering that actually improves your outputs
✨ Reliable, structured output with Pydantic
✨ Analyzing files and images, and generating images
✨ How tokens, model parameters, and costs work under the hood
I’ll also give you plenty of ideas for creating your own unique portfolio project, so you don’t just copy mine.
A living and breathing course
Right now, the course contains over 7 hours of content across more than 50 video lectures, and it keeps growing. The next modules are already in the works: a second portfolio project (an AI chatbot with tool calling and RAG), deployment on AWS, and evaluations. Once they’re live, everyone enrolled gets them automatically, for free.
Is this course for you?
This is NOT a course for absolute beginners. You should be familiar with writing code and working with git.
But it doesn’t matter whether you’re a software developer, a data scientist, or an ML engineer: if you already know one programming language, you’re ready. We’ll be coding in Python, and if Python isn’t your language yet, don’t worry, you’ll pick it up easily along the way.
About me
Hi, I’m Lukas. I’m a software developer with more than 15 years of experience, and I’ve helped over 10,000 students learn here on Udemy. Recently, I’ve gone deep into AI Engineering: I’ve built and deployed real AI apps and analyzed hundreds of job postings to understand what companies actually want.
This is the course I wish had existed when I started my own AI Engineering journey.
There’s a 30-day money-back guarantee, so you can test the course completely risk-free.
I would love to see you inside
Who this course is for
⭐ Software Developers
⭐ Data Scientists
⭐ ML Engineers
⭐ People with experience in at least one programming language
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