After completing a PhD in Astrophysics in 2018, Algimantas transitioned into data science and now works at IBM’s Client Innovation Center. His focus areas are natural language processing and large language models, and his work has led to both scientific publications and a US patent in machine learning. Learners at Turing College benefit from his blend of research depth and applied industry experience, especially in NLP and AI innovation.
AI Engineering online course
Europe's first AI Engineering course that gets you job-ready in 3 to 4 months, or helps you found your own AI startup. The programme is taught in German or English.
“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
Data/research focused
- ML researchermodels trainingevals
- ML engineer / Data scientistmodels deploymentdata preparation
- AI engineerchains/agentsinfrastructure
- Fullstack engineerproductplatform
Product/user focused
Repeatedly recognised 4 years in a row
- Best Data Science Bootcamp, Course Report 2022
- Best Data Science Bootcamp, Course Report 2023
- Best Data Science Bootcamp, Course Report 2024
- Best European Bootcamp, Course Report 2025
- Best AI/ML Bootcamp, Course Report 2025
- Best Digital Marketing Bootcamp, Course Report 2025
- Best Data Science Bootcamp, Course Report 2025
- Best Online Bootcamp, Course Report 2025
- Best Coding Bootcamp, Course Report 2026
- Best AI/ML Bootcamp, Course Report 2026
- Best Online Bootcamp, Course Report 2026
Featured in
Highly rated
4.9/5
Graduates hiring rate
88%
of graduates get hired 6+ months after graduation*
*Germany, as of July 2026. Includes learners whose programme ended at least six months earlier and whose employment status could be confirmed. Unconfirmed outcomes were excluded.Open the door to the most in-demand tech career
Turing College's 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.
8x
Jobs requiring specialised AI skills are growing almost 8x faster than the overall jobs market
62%
Professionals with AI skills earn an average wage premium of 62%
How the programme prepares you for AI engineering roles
A portfolio employers can review
Build four AI applications and get technical feedback on each one. The last is a capstone of your own design, taken from concept to a deployed, end-to-end LLM application. All four are hosted and documented, so you can show employers working projects, not just a certificate.
1:1 reviews, stand-ups and group sessions
Each project gets a 1:1 review with a Senior Team Lead, an experienced AI engineer who gives you technical feedback on what to improve. Between reviews, you can join open sessions, group calls where you discuss your projects, the course material and questions about working in AI. You can also join workshops on specific AI tools and processes. You get used to explaining your work and solving problems with others, the way you would in an engineering team.
Study around your current job
Set your own pace, with 24/7 access to materials, so you can keep working while you build the skills for an AI engineering role.
The tools you'll build with
Languages
- Python
- JavaScript
Frameworks
- LangChain
- LangGraph
- Streamlit
- Next.js
Models
- OpenAI GPT
- Google Gemini
- Meta Llama
- Anthropic Claude
Methods
- RAG
- MCP
- AI agents
- Prompt engineering
- Vector databases (ChromaDB)
AdmissionsLearningProjectProject reviewSprints
Work through learning materials at your own pace.
On-demand learning materials that fit your weekly plan
At least 10 hours a week over 3 to 4 months
Build and test a working application.
Four AI applications, including a capstone of your own design
Get 1:1 feedback and use it in your next sprint.
One-to-one technical project reviews with a Senior Team Lead
Project reviews and open sessions give you personal feedback and support.
On completion: your certificate and project portfolio
Share four completed, documented projects with employers, or link them from your CV and GitHub.
Programme outline
Co-created with industry AI experts, this course combines four modules and 15 sprints of hands-on practice, spread over 3 to 4 months at around 10 hours a week.
1Foundations of LLM application development
1
Foundations of LLM application development
Understand how large language models work in practice: capabilities, limitations, and ethical considerations. Set up your development environment and integrate APIs from OpenAI, Anthropic, and Google. Master prompt engineering, including few-shot prompting and system message design.
Python / JavaScriptOpenAI APIAnthropic APIGoogle GeminiPrompt engineering
2Building applications with LangChain and RAG
2
Building applications with LangChain and RAG
Build LLM-powered applications that connect to external data sources using retrieval-augmented generation. Use ChromaDB for vector storage and LangChain to structure LLM workflows, then build your first full-stack app with Streamlit or Next.js.
LangChainRAGChromaDBStreamlitNext.js
3AI agents
3
AI agents
Design and build AI agents that carry out multi-step tasks autonomously. Use LangGraph for agent development, and implement short- and long-term memory so agents retain context over time.
LangGraphAI agentsMemory systemsMCP
4Capstone project
4
Capstone project
A self-directed project of your own design, taken from concept to a deployed, end-to-end LLM application.
Our 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.
What our learners build
AI Engineering graduates complete a self-directed capstone project as the final stage of the programme. Each project is built independently, using the tools and techniques covered throughout: LLMs, LangChain, RAG, vector databases, and AI agents. Projects are reviewed 1:1 by a senior industry mentor before completion.
wae.
Explains the Korean cultural nuance that YouTube subtitles miss.
Created by Gain Choe · AI Engineering
Card Battle Auto-Balancer
A team of AI agents plus simulation balances a card game automatically.
Created by Oleg Reva · AI Engineering
Plantopia
A plant-health agent that asks questions before it diagnoses.
Created by Felix Bögge · AI Engineering
Find the right Turing College AI course for you
Compare the programmes to find one that fits your experience and the work you want to do. The durations and weekly hours shown are for self-funded study.
AI Engineering
- Duration
- 3 to 4 months
- Pace
- ~10 hours/week
- Who it's for
- Developers who want to use their coding skills to build, evaluate and deploy LLM applications and AI agents
- Experience required
- At least 1 year of Python or JavaScript
- What you'll build
- Applications that answer questions using external data (RAG), agents that carry out multi-step tasks, and an independently designed AI application
- LangChain
- LangGraph
- RAG
- ChromaDB
- MCP
Living in Germany? AI Engineering can be 100% funded with a Bildungsgutschein. AI Engineering with a Bildungsgutschein
Learn from senior AI professionals
Our Senior Team Leads are experienced AI engineers, data scientists, and machine learning professionals currently working at companies like IBM, Vinted, and Telia. They bring real industry expertise into every session, reviewing your projects 1:1, giving personalised technical feedback, and helping you think like a professional engineer.
When you submit a project, you book a 1:1 review directly from their availability calendar. Open Sessions work the same way. With a wide pool of industry experts available, each session is a chance to learn from someone actively building AI systems in the field today.
With more than 15 years of experience in machine learning and AI, Andrius has worked on projects ranging from computer vision and deep learning to fraud detection and large language models. At Vinted, he develops algorithms that protect the platform from malicious threats and ensure a safe experience for millions of users. Learners at Turing College benefit from his deep technical expertise and his passion for mentoring the next generation of data scientists.
Augustinas is a Senior Data Engineer at the Scandinavian telecom company Telia. With over 8 years of Python experience and previous roles at Gjensidige, PwC, Ignitis, and other leading companies, he has worked across data and software engineering. At Turing College, he emphasises project structure, code readability, and quality, helping learners develop the habits of writing clean, reliable, and professional code.
Gedmantas brings over five years of experience working with data across logistics, oil and manufacturing. At Continental, he builds forecasting models and automates operational tasks. With a background in applied mathematics, he draws on his industry work to help Turing College learners approach data problems and put mathematical concepts into practice.
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 programme 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 programme matches your goals, we'll invite you to a 20 to 30-minute consultation. This is your chance to ask anything, understand exactly how the programme 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 programme. It should be your personal goal, and you should have specific reasons for wanting to improve your skills.
Coding experience
Coding experience
You need a minimum of 1 year of coding experience with Python or JavaScript.
German or English at B2+
German or English at B2+
You need German or English proficiency at B2 level or above, depending on your chosen teaching language.
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.
Flexible financing options
Upfront payment
Learners who want the lowest total price by paying upfront
€3,500
Save 17%- Self-paced, flexible schedule
- Flexible, 3-4 months
- 10+ h per week
- 30-day money-back guarantee
Instalments
Learners who prefer to split self-payment into monthly instalments
€1,055× 4 months
0% INTEREST- Self-paced, flexible schedule
- Flexible, 3-4 months
- 10+ h per week
- 30-day money-back guarantee
We have limited seats. Apply now!
What our AI Engineering graduates say
Delegation Team Coordinator @ Siemens Energy
Staff Engineer, Eurowings Digital (Lufthansa Group)
AI Engineering learner
AI Engineering graduate
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AI Engineering salaries in 2026
What AI engineers earn across Europe, based on ERI SalaryExpert, Robert Half, Glassdoor, Bitkom, and the Stack Overflow Developer Survey 2025.
Germany
€64k to €103k+
- Entry
- €64k
- Mid
- €90k
- Senior
- €103k+
Germany is one of Europe's fastest-growing markets for AI engineers. Bitkom's latest study puts the current shortage at 109,000 unfilled IT positions nationally, with AI specialist roles among the hardest to fill.
Source: ERI SalaryExpert, July 2026; Bitkom, Der Arbeitsmarkt für IT-Fachkräfte 2026
United Kingdom
£50k to £90k
- Entry
- £50k
- Mid
- £66k
- Senior
- £90k
Specialist AI job postings surged 61% in the UK over the past year. In London specifically, Robert Half puts senior AI engineer salaries as high as £122,500.
Source: Robert Half UK, 2026; PwC UK 2026 AI Jobs Barometer.
Netherlands
€58k to €100k
- Entry
- €58k
- Mid
- €72k
- Senior
- €100k+
Amsterdam is one of Europe's leading tech hubs for AI roles. Skilled migrants may benefit from the Dutch 30% tax ruling, currently available for up to five years (this drops to a flat 27% for new applicants from January 2027).
Source: Glassdoor Amsterdam, 2026
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've also built adaptive AI features that personalise your learning even further, so your journey adjusts closely to your pace, needs, and progress.
FAQ
Is AI engineering the right career for you in 2026?
Is AI engineering the right career for you in 2026?
AI Engineering could be a good fit if you want to build and deploy AI applications, develop a portfolio of real projects and use those projects to demonstrate your skills to employers. It suits people who enjoy solving difficult problems, learning continuously and working through uncertainty.
You’ll need a solid coding foundation and the motivation to keep developing your technical skills. Watch the video to explore five questions that can help you decide whether AI Engineering fits your experience, working style and career plans.
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 Building with AI programme is a better starting point. 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 to €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 towards 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 programme available for unemployed people. If you're paying from your own pocket, we offer zero-interest monthly instalments or a 17% discount if you pay the full tuition upfront.
Is the programme taught in German or English?
Is the programme taught in German or English?
The programme is taught online in German or English. You need B2-level or higher proficiency in your chosen teaching language.