Programming experience.
The course is for developers, software architects, tech leads and other IT professionals who want to use AI effectively in their everyday work and take their skills to the next level. It suits both those who are just starting with AI tools and more advanced users.
Want to speed up their work, automate routine tasks and build modern AI-first applications.
Design systems and want to understand how to integrate AI and multi-agent patterns into them.
Lead teams and need to move them towards an AI-first approach to building software.
DevOps, QA and others – everyone who wants to stay in the field and grow with AI.
The course is taught online, so you can join from anywhere. Lessons combine explanation, demonstrations and practical exercises, and video recordings of all lessons are available for you to return to at any time.
You try out new skills right away on real-world tasks.
All lessons are available in the e-learning platform for unlimited playback.
You work with tools such as GitHub Copilot, Cursor or Windsurf directly during lessons.
Between lessons you can work on assignments with feedback from lecturers.
A space for questions, sharing solutions and communicating with other participants.
Every lesson is focused on immediate use in a real project.
Teaching is intensive, twice a week, with a regular evening rhythm that fits well with work and your own preparation between lessons.
We explore how LLMs work and the anatomy of agents. We compare current models and code assistants and look at new trends such as MCP, subagents and working with tools.
We focus on comparing and configuring vibe-coding tools. We learn to work with agents.md, define Skills and commands, and control subagents directly from the CLI.
We discuss agent collaboration based on the latest studies and show the practical use of Worktrees, working with Git, running Codex in Docker and implementing MCP and LLM Gateways. We also learn to use the context window effectively and the TOON method, handle context forking, compare single- vs. multi-agent strategies and apply advanced prompting techniques.
We explain the differences between agents’ short-term and long-term memory. We introduce the process of introducing RAG and the principles of how vector databases work.
No theory in this lesson. We use the skills we have acquired to create a complete full-stack application, debug it and try combining several tools in practice.
We learn to use SDKs to extend the capabilities of Claude and Codex. We focus on designing multi-agent workflows and integrating AI features into external applications.
We look at AI-first projects, code review and architecture design. We show how to integrate AI into CI/CD, automation in Jira and support in operating systems.
We dive into areas beyond pure development. We show how applications can be deployed to complex cloud environments with AI, and how to debug and operate them.
After completing the course you will not just be a user of AI, but an architect of AI-driven development. Specifically, you will be able to:
While others talk about AI in general, we teach you the specific tools that professional developers around the world use today:
It doesn’t end with the course. Even after completing it, you keep plenty of benefits you can rely on:
An official Turing Institut certificate documenting your newly acquired skills.
Recordings of all lessons and study materials remain yours forever – come back to them whenever you need.
A Discord full of people like you, a newsletter with IT news and exclusive members-only events.
There is currently no scheduled date for this course. Write to us or give us a call — we will let you know as soon as a new date is announced, and we are happy to arrange a date that suits you.
The course is for people who already have programming experience – you don't have to be a senior, but you should understand the basics of development and be able to find your way around code. We teach you everything about AI tools, agents and their orchestration from the basics to advanced techniques.
We teach online and hands-on from the first lesson. We alternate clear theory with live demonstrations in which we build real applications together using tools such as Claude, Codex and Cursor. Besides the lessons you have access to e-learning and a Discord community where you can ask questions between lessons too.
Yes, that is exactly the goal of the course. We don't teach about AI in general, but the specific tools and practices professional developers use today: orchestrating subagents, context management, RAG over your own data and integrating AI into CI/CD. By the end you will be able to design, build and deploy your own AI-first application.
These two courses sit side by side in the catalogue and both work with agents, but they teach different skills.
This course is about developing software with AI. From someone who writes code by hand you become an architect and orchestrator: you use Claude, Claude Code, Codex and Cursor, direct subagents, manage context, connect an MCP Gateway and build full-stack applications that you then deploy. RAG and vector databases serve development here — so that agents know your code and data. You learn how to bring AI into code review, CI/CD and the whole software lifecycle. The course is shorter (8 lessons, approx. 16 hours) and assumes programming experience.
AI Agent Developer teaches you to build autonomous agentic systems as a product. You take ready-made language models as the brain of an application and teach them to act: plan steps, use tools, look up information in company data (RAG), remember context and cooperate with other agents. It covers LangChain, LangGraph, MCP, Kubernetes, the NVIDIA stack and preparation for the NCP-AAI certification. You try it in a real environment on GPU instances. It is a longer, deeper course (approx. 50 hours).
The courses meet at terms such as agent, RAG and MCP, but in a different context. Here the agent is a helper in the developer workflow — it writes, reviews and deploys code. In AI Agent Developer, the agent is the application itself that you build, run and scale.
A simple guide: if you want to change the way you develop software and master tools such as Cursor, Claude and Codex — stay here. If you want to build and run production agentic systems and aim for NVIDIA certification — go for the AI Agent Developer course. They build on each other, but neither is a prerequisite for the other.
A more detailed comparison of all AI courses by goal can be found in the article Which AI course should I choose?.