Education voucher (Bildungsgutschein)
Best for
German residents eligible for a Bildungsgutschein
Course duration
Fixed, 3 months
Time commitment
30 h per week
Price
€0Fully funded
30-day money-back guaranteeOur mentors bring first-hand experience from companies and universities such as:
The companies and institutions mentioned have no institutional affiliation or official partnership with Turing College.
“In numbers, there's probably going to be significantly more AI Engineers than there are ML engineers / LLM engineers.”
Andrej Karpathy
Founding member of OpenAI, ex-Director of AI at Tesla
Open the door to the most in-demand tech careers
The AI Engineering course gives you hands-on experience designing and building applications with Large Language Models (LLMs), LangChain, and AI agents. You'll learn the tools and gain the knowledge needed to thrive in high-demand AI roles like AI Engineer, LLM Engineer, ML Engineer, Software Engineer, Data Scientist and Backend Developer.
3.5x
Jobs requiring specialized AI skills are growing 3.5x faster than other jobs
25%
Professionals with AI expertise earn up to a 25% higher salary
What can you expect?
Self-paced learning and flexible schedule
Learn at your own pace, anytime. We recommend 8-12 hours a week to meet deadlines, but you can adjust to fit your lifestyle with 24/7 access to materials.
Experience with practical projects
Build confidence tackling real business problems with mentor feedback. In four projects (~120 learning hours), you'll leverage AI to address real-world challenges.
1:1 mentoring
Receive detailed, personalized feedback from mentors who work in the field.
AI tools and languages you'll use:
- Python
- JavaScript
- LangChain
- LangGraph
- RAG
- OpenAI GPT
- Google Gemini
- Meta Llama
- Anthropic Claude
- Prompt engineering
- Vector databases
- Streamlit
- Next.js
- AI agents
Program outline
This course, created by AI professionals, combines intensive sprints with practical, hands-on projects. Each sprint focuses on key areas of AI engineering, guiding you from foundational skills to building real-world applications.
01Foundations of LLM Application Development
01Foundations of LLM Application Development
Lay the groundwork for developing Large Language Model (LLM) applications with a focus on understanding their capabilities and ethical implications. This sprint introduces you to key LLM concepts, such as prompt engineering and LLM settings, and a development environment in Python or JavaScript. Through hands-on labs, you'll explore APIs like OpenAI, Anthropic, and others, and practice crafting and optimizing effective prompts. By the end, you'll understand how to harness LLMs responsibly and effectively for real-world applications.
02Building Applications with LangChain, RAGs, and Gradio
02Building Applications with LangChain, RAGs, and Gradio
Dive deeper into LLM-powered applications by learning to integrate external knowledge and build interactive tools. This sprint focuses on LangChain and its capabilities for enhancing LLM workflows, Retrieval-Augmented Generation (RAG) for accessing external data, and vector databases like ChromaDB for storing and retrieving embeddings. You'll gain hands-on experience building structured outputs and prototyping chatbots, culminating in LangChain + Gradio apps that combine LLMs with real-world data.
03AI Agents
03AI Agents
Master the art of creating AI agents that can perform complex, automated tasks. This sprint introduces the fundamentals of AI agents, from basic chains to advanced agents capable of executing code, interacting with APIs, and performing long-term tasks. You'll also explore memory mechanisms that let agents retain context over time. With hands-on labs and a final project, you'll be equipped to design and deploy intelligent, autonomous systems tailored to specific goals.
Is AI Engineering course for me? Yes, if:
You have a tech background (worked in roles such as developer, software engineer or product manager) and are looking to transition into AI roles.
You are a tech professional looking to explore AI-driven innovations.
New to programming?
Our beginner-friendly Software & AI Engineering course might be a better fit for you.
Kickstart your new career
We don't make empty job promises. Instead, we focus on what actually works: real-world skills, personalized career support, and a strong portfolio that shows employers what you can do.
- HR and technical mock interviews
- CV and LinkedIn optimization
- Live career sessions
A unique learning experience powered by technology
Online learning is tough when you're left on your own. That's why we built Intra, our learning platform that combines the best of both worlds: human support and smart structure. We're also developing adaptive AI features to further personalize learning so that, in the future, your journey will adjust closely to your pace, needs, and progress.
Learn from professionals
Our Senior Team Leads and mentors are experienced professionals who are 100% up-to-date with the industry trends and will provide you consultations, 1on1 project reviews, and feedback.
Flexible graduation: you set the pace
Our graduates from various countries work at
How admissions works
Our application process has two simple steps designed to help you and our team understand whether the program is the right next step for you.
- 1
Application
Tell us about your background and answer two short questions about your motivation and goals. Your application goes straight to our admissions team, who review it personally and get back to you within 24 hours on working days. - 2
Consultation
If the program matches your goals, we'll invite you to a 20-30 minute consultation. This is your chance to ask anything, understand exactly how the program works, check your financing options, and decide whether it's the right fit for you.
Basic admission requirements:
Focused hours/week
Focused hours/week
Focused hours are:
- · Working on a computer (not a smartphone)
- · Uninterrupted working time in a dedicated space
- · Rested, not overworked (not after intense cognitive work)
Strong motivation
Strong motivation
You need a clear and strong reason for joining this program. It should be your personal goal, and you should have specific reasons for wanting to improve your skills.
Up-to-date computer
Up-to-date computer
You'll need a computer that can handle large datasets smoothly and runs an actively supported and updated operating system.
Coding experience
Coding experience
You need a minimum of 1 year of coding experience with Python or JavaScript.
Good English skills
Good English skills
You must demonstrate an English proficiency of at least B2 level to join the program.
Flexible financing options
You’re resident of:
QCG
Best for
German residents eligible for QCG (Qualifizierungschancengesetz) employer-supported funding
Course duration
Fixed, 3 months
Time commitment
30 h per week
Price
Up to 100% funded
With QCG funding
30-day money-back guaranteeUpfront payment
Best for
Learners who want the lowest total price by paying upfront
Course duration
Flexible, 3-4 months
Time commitment
15+ h per week
Price
€3,500Save 17%
30-day money-back guaranteeInstallments
Best for
Learners who prefer to split self-payment into monthly installments
Course duration
Flexible, 3-4 months
Time commitment
15+ h per week
Price
€1,055x 4 months0% INTEREST
30-day money-back guaranteeUpfront payment
Best for
Learners who want the lowest total price by paying upfront
Course duration
Flexible, 3-4 months
Time commitment
15+ h per week
Price
€3,500Save 17%
30-day money-back guaranteeInstallments
Best for
Learners who prefer to split self-payment into monthly installments
Course duration
Flexible, 3-4 months
Time commitment
15+ h per week
Price
€1,055x 4 months0% INTEREST
30-day money-back guaranteeWe have limited seats. Apply now!
Starting dates
July 22nd
Deadline for applications: 2026-07-15
August 24th
Deadline for applications: 2026-08-17
Our graduates have achieved life changing growth. You can too.
Turing College has been a great experience. I loved the structure and content of the material. I had constant contact with instructors and peer learners. I find the peer and senior review concept really efficient.
Kata Hernádi
Delegation Team Coordinator @ Siemens Energy
FAQ
What is the difference between an AI Engineer and an ML Engineer or Data Scientist?
What is the difference between an AI Engineer and an ML Engineer or Data Scientist?
An AI Engineer builds products and systems using existing AI models — integrating APIs, building retrieval pipelines, designing multi-agent systems, and shipping applications that work in production. A Machine Learning Engineer works closer to the model itself, focusing on training, fine-tuning, and infrastructure. A Data Scientist analyses data to generate insights and build predictive models. The distinction that matters: AI Engineering is the applied layer — you're building with AI, not building AI. It's also the layer that doesn't require a research background or advanced mathematics to enter.
Is AI Engineering in demand in 2026?
Is AI Engineering in demand in 2026?
Yes. Machine learning and AI engineer listings are up 59% from pre-pandemic levels, while generalist software engineer postings are down 49%. The market hasn't contracted — it has split, and AI Engineering is on the right side of that split. In 2025, 88% of organisations used AI in at least one business function, up from 78% the year before, and job listings for agentic AI roles alone jumped 985% in 2024. Supply has not kept pace.
Can I become an AI engineer in 3 months?
Can I become an AI engineer in 3 months?
That depends on where you're starting from. The programme requires at least one year of coding experience in Python or JavaScript. With that foundation you can build a solid, portfolio-ready set of AI Engineering skills in 3 to 4.5 months. If you're newer to coding, our Software & AI Engineering programme builds that foundation from scratch. What the programme delivers is practical: four hands-on projects using models from OpenAI GPT, Google Gemini, Meta Llama, and Anthropic Claude, and a portfolio that shows employers exactly what you can build.
Do I need a PhD to become an AI engineer?
Do I need a PhD to become an AI engineer?
No. AI Engineering is a practical discipline, not a research one. PhDs are relevant for roles that involve developing new models or advancing the field itself. Building AI applications requires programming skills and hands-on experience, not academic credentials — and the hiring market increasingly prioritises demonstrated practical experience over formal qualifications.
Is this course suitable for career changers?
Is this course suitable for career changers?
The programme is primarily designed for software engineers, web developers, and technically grounded professionals who want to add AI Engineering skills to what they already do. If you already write code and want to start building AI-powered applications, this is built for you. By the end you can build full-stack LLM applications, design multi-agent systems, and work with the APIs and frameworks that appear in real job postings — leaving with four completed projects as your main evidence for employers.
What skills do I need before starting?
What skills do I need before starting?
You need working knowledge of Python or JavaScript — enough to write functions, work with APIs, and understand basic data structures. No prior machine learning knowledge is required, and no computer science degree is needed. A practical check: have you built something with code before, even something small? If yes, you have enough to begin.
How is AI Engineering different from traditional software engineering?
How is AI Engineering different from traditional software engineering?
Traditional software engineering builds systems from explicit logic: you write rules, the system follows them. AI Engineering adds a layer where models make decisions, generate outputs, or reason about inputs in ways that aren't fully deterministic. As an AI engineer, you work with prompts, context windows, retrieval pipelines, agent loops, and model APIs, and you think about evaluation, reliability, and orchestration — distinct skills that traditional software engineering doesn't cover.
What tools and technologies will I learn?
What tools and technologies will I learn?
The programme covers Python, LangChain, LangGraph, OpenAI GPT models, Google Gemini, Meta Llama, Anthropic Claude, prompt engineering, RAG (Retrieval-Augmented Generation), vector databases using ChromaDB, AI agents, and front-end deployment with Gradio, Streamlit, or Next.js. Each tool is taught in the context of a project rather than in isolation.
What kinds of projects will I build?
What kinds of projects will I build?
Across the programme you build four projects: a full-stack LLM application using LangChain and Streamlit or Next.js, a chatbot with RAG and a vector database, an AI agent with memory and context tracking, and a self-directed capstone LLM-powered application of your choosing. You can also see what our graduates have built in the Turing College project showcase.
What roles are available after completing the course?
What roles are available after completing the course?
Graduates move into roles such as AI Engineer, AI Developer, AI Backend Developer, and AI Solutions Engineer. The underlying work is building, integrating, and maintaining AI-powered systems. AI Engineers command an average 12% salary premium over general Software Engineers in the European market, and senior AI-specialist roles are currently filling in an average of 17 days — a reliable signal of how acute the talent shortage is.
What salary can an AI Engineer expect?
What salary can an AI Engineer expect?
Salaries vary by location, experience, and specialisation. For the European market, the average Software Engineer salary is around €74,100 in Germany and €73,200 in the Netherlands, with AI Engineers earning a ~12% premium on top. Senior AI engineers in major European hubs can reach €150,000+ in total compensation. At entry to mid level a realistic range is €55,000–€80,000, with progression typically faster than in traditional software roles given current demand.
Can I study AI Engineering while working full-time?
Can I study AI Engineering while working full-time?
Yes. No live lectures means no fixed schedule to work around. Most learners are working professionals who complete the programme alongside a full-time job at the standard pace of around 10 hours per week. The sprint structure helps — rather than one long deadline at the end, you work toward shorter milestones that keep progress visible and the workload manageable.
How do graduates find jobs?
How do graduates find jobs?
The portfolio. Four completed, documented projects you can share directly with employers or link from your CV and GitHub carry more weight than most credentials in this hiring market. Over 75% of AI job listings specifically seek domain experts with demonstrated hands-on skills.
What credential or proof of skills will I have?
What credential or proof of skills will I have?
On completion, you receive a Turing College certificate in AI Engineering. You also leave with four completed projects, hosted and documented, that function as your main evidence for employers — and for most hiring conversations, that showcase and the GitHub repositories behind it carry more weight than the certificate itself.
What are the funding options?
What are the funding options?
We believe financing should not be a blocker to knowledge. If you're a resident of Germany, Bildungsgutschein could be an option — it's a government funding program available for unemployed people. If you're paying from your own pocket, we offer zero-interest monthly installments or a 17% discount if you pay the full tuition upfront.
Next group starts on June 22nd