Introduction to AI Engineering with Python

4.840 hours782 learnersCertificate

This hands-on course introduces you to the main ideas and tools used to build modern AI-powered applications. You'll learn how to work with foundation models, create retrieval-augmented generation systems, build simple AI agents, and deploy your own AI services safely and reliably.

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JetBrains Academy

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Study at your own pace

Fit learning around your schedule. Suitable for all levels.

Learn from the experts

Short, practical text lessons by seasoned developers.

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Integrated with professional tools by JetBrains.

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What you'll learn

By the end of this course, you'll have built real-world AI projects and gained a strong practical foundation. You will learn how to:

Use key AI engineering concepts to design systems powered by foundation models;
Build RAG pipelines that store and search data, then use it to improve model responses;
Create simple agents that can use tools, APIs, and memory to complete multi-step tasks;
Work with databases and vector stores to manage context and information;
Deploy and monitor your AI applications with a focus on safety and performance;
Follow good engineering practices such as using Git, testing, and writing clear documentation.

Note: This course assumes prior knowledge of core Python topics, including variables, control flow, functions, and basic data structures. Some experience with NumPy, pandas, or scikit-learn will also be useful. If you need to review these skills, we recommend taking the "Python Fundamentals with Practical Projects" course first.

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Learn by doing

# 1

Apply knowledge into practice

You already know the theory. Now it's time to code like you do at work—in a professional IDE, with real project constraints, solving problems that actually matter. Welcome to software engineering as it should be.

# 2

Navigate complexity with surgical precision

Most developers waste months learning random concepts without seeing how they connect. Our interactive Knowledge Map fixes this. It shows exactly how every programming concept relates to others, helping you build a structured mental model of coding.

# 3

Copy the best. Then improve.

Here's what top engineers do that others don't: they study other people's code obsessively. When you get stuck on Hyperskill, you can explore solutions published by other developers. See their exact code. Understand their approach. Learn their tricks.

# 4

Code review that actually makes you better

We stripped code review down to what actually matters: does your solution work? Have you handled the edge cases? Is there a cleaner way to write this? Hyperskill acts like a competent reviewer who actually tests your code. Not genius-level analysis, not architecture debates — just solid feedback on making your code better.

Elevate your engineering mastery through real-world challenges

Master advanced engineering concepts through ambitious projects. Each project deepens your expertise and transforms you from an experienced engineer into an exceptional one.

Building the Naive RAG

Movies whisk us away to magical realms and ignite our imagination. So why settle for just watching your favourite films when you can re-imagine them? In this project, you'll feed a large language model a dataset of movie scripts to craft brand-new scenes, character dialogues, and even invent entirely new twists.

Graduate

Building a PR Review Agent

In this project, you’ll build a multi-agent AI system that taps into GitHub’s API to pull code diffs, test outcomes, and dependency data. It then uses this information to catch obvious mistakes—lint violations, missing tests, and vulnerability flags—and produces a short, clear comment for each pull request. Finally, it posts the review back to GitHub, so reviewers can dedicate their effort to the deeper review tasks.

Graduate

AI Diet and Meal Planner

We all love a well-cooked home meal, but the choice of what to prepare is the actual challenge — especially when you are short on time, ingredients, or ideas of what to have. What if you had an AI sous-chef of your own? You will develop a multi-agent AI system using FastAPI where each agent plays a role in designing the perfect recipe depending on what you have in your kitchen and your nutritional needs. You’ll create agents that analyze available ingredients, filter recipes by diet type, and plan a complete step-by-step meal—with structured JSON outputs from LLMs.

Graduate

Explore all projects

Topics covered by this course

Software development foundations

41 topics

Generative AI

41 topics

Data science

20 topics

Math

12 topics

System administration and DevOps

9 topics

Programming languages

1 topic

Backend

1 topic

Learn from the industry experts

JetBrains Academy

JetBrains Academy is a part of JetBrains, a global software company specializing in the creation of intelligent, productivity-enhancing tools for software developers and teams. With years of expertise in software development and education, JetBrains Academy empowers more than a million people worldwide to learn and teach computer science, and help organizations inspire their teams to reach their goals in tech. Professional development tools play a big role in computer science education. This is why JetBrains Academy courses offer integration with JetBrains IDEs. This integration assists learners in getting experience with real development processes to streamline their learning curve at future work.

Your peers think Hyperskill rocks

Diego Pérez Petkov

1 month ago

Definitely one of the best courses out there. Lots of updated material and great projects (except for the pgVector one, which was outright awful). In general, very worth it to start learning about embedding AI into applications, and making the most out of agentic workflows.