AI Data Engineer: Build Production AI Systems at Scale
Master Hugging Face, LangChain, SQL, NoSQL, Graph databases and enterprise AI deployment in this 12-month apprenticeship. Progress from basic functions to production-grade multi-agent systems.
Course Information
- 📅 1st Friday of every month teaching
- ⏰Duration: 9am-5pm (12 months)
- 💰Total Investment £19,000 of which Government funds £18,050- £19,000
- 📍Location: Live Online
- 👥 10 Max Cohort Size
- 🎓Includes: 12-month portal access
From Basic Scripts to Enterprise AI in 12 Months
While others learn outdated data engineering, you’ll build real AI systems. This isn’t about ETL pipelines and SQL queries – it’s about creating intelligent, autonomous systems that transform businesses.
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Production-Ready Skills
Deploy AI to containers (Docker, Kubernetes), build with LangChain, orchestrate with LangGraph
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Real Business Projects
Build actual solutions for insurance, healthcare, retail, fintech, professional services and manufacturing.
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Progressive Mastery
Start with ‘Hello AI World’, end with multi-agent enterprise data pipeline systems
Progressive Learning: From Foundation to Expert
Level 1 (Month 1): Foundation ⭐
- Docker basics + Render deployment
- “Hello AI World” with Hugging Face + LangChain
- Simple document processing with Strapi CMS
- Project: Intelligent Document Analyzer using MongoDB
Level 2 (Months 2-4): Core Skills ⭐⭐
- MongoDB vector search & semantic embeddings
- LangChain agents with memory (MongoDB persistence)
- Conversational AI with Clerk authentication
- Projects: Smart Search Engine (Neo4j), AI Assistant (Angular frontend)
Level 3 (Months 5-8): Advanced ⭐⭐⭐
- Multi-source data pipelines with n8n
- AutoGen multi-agent workflows
- Real-time AI processing with Streamlit dashboards
- Projects: Data Processing Pipeline (DuckDB), Multi-Agent System (AutoGen + DSPy)
Level 4 (Months 9-11): Enterprise ⭐⭐⭐⭐
- Microservices on Render with Angular/Ionic frontends
- Grafana Cloud monitoring & Clerk security
- API design with Strapi + n8n orchestration
- Project: Enterprise AI Platform with MCP servers
Level 5 (Months 12-15): Expert ⭐⭐⭐⭐⭐
- ArgoCD GitOps for AI systems
- Terraform Infrastructure as Code
- Ray distributed computing & Prometheus monitoring
- Project: Production AI Platform with full observability
5 Production-Ready AI Systems in Your Portfolio
Technology Stack
AI & Data Platform:
- Hugging Face: State-of-the-art AI models
- LangChain: Agent orchestration framework
- AutoGen: Multi-agent system development
- DSPy: Advanced prompting framework
- Ray: Distributed AI computing
- MCP Servers: Model context protocol
Data & Infrastructure:
- MongoDB: Document store with vector search
- Neo4j: Graph database for learning paths
- DuckDB: High-performance SQL analytics
- Strapi CMS: Headless content management
- Render: Modern cloud hosting
- Clerk: Enterprise authentication
Development & Operations:
- Angular/Ionic: Cross-platform frontends
- n8n: Visual workflow automation
- Docker: Containerisation
- Terraform: Infrastructure as Code
- ArgoCD: GitOps deployment
- Grafana Cloud: Full-stack observability
Designed for Working Professionals
Your Learning Schedule:
- 📅 4 days per month (48 days total)
- 📍 Day 1: Theory & concepts (remote)
- 💻 Days 2-4: Hands-on project work
- 🕐 Hours: 9am-5pm UK time
- 📱 Platform: 24/7 access to resources
Learning Format:
- Live expert instruction
- Hands-on labs
- Peer programming
- Real client projects
- Industry experts
Comprehensive Support:
- 👨🏫 Expert Instructors: AWS architects & AI engineers
- 🤝 1-1 Mentoring: Bi-weekly sessions included
- 💬 Community: Slack workspace for cohort members
- 🏢 Industry Projects: Work on real problems
- 📚 Resources: 12 month access to materials
Complete 12-Month Curriculum
Who This Is For
You're Ready If:
- ✅ You have basic Python knowledge (loops, functions, libraries)
- ✅ You understand databases (SQL queries, basic schemas)
- ✅ You’re excited about building AI solutions, not just using them
- ✅ You can commit to 4 days per month for learning
- ✅ Your employer supports your development
- ✅ You want to lead AI initiatives, not just participate
This Isn't For You If:
- ❌ You’ve never written any code before
- ❌ You only want traditional data engineering (ETL, warehouses)
- ❌ You can’t commit to the full schedule
- ❌ You’re not eligible for UK apprenticeship funding
- ❌ You want to research AI, not build with it
Background That Helps:
- Data analyst wanting to advance
- Developer interested in AI
- IT professional seeking new skills
- Business analyst with technical aptitude
Prerequisites:
- Basic Python (can write simple scripts)
- Understanding of databases
- Problem-solving mindset
- Commitment to learning
Are You Eligible for Government Funding
The UK government has made apprenticeships a cornerstone of its economic strategy, committing billions in funding to help businesses train the workforce of tomorrow. There are a series of courses that the UK Government has approved for investment. The investment is 95-100%, which means that employers pay nothing or 5% of the course fees.
Its an excellent way to upskill your employees, improve business profitability and prospects.
This AI Data Engineering is an AI enhanced course based on the Data Engineer course (ST1386) which is eligible for UK Government funding.
Your Journey Starts Here
Timeline: "From application to start: 4-6 weeks"
Step 1: Apply Online
- Contact us using the contact form
- We will send an application form
- Basic Python assessment
- Confirm employer support
Step 2: Brief Interview
- 30-minute video call
- Discuss your goals
- Confirm commitment
Step 3: Employer Agreement
- We provide all paperwork
- Employer signs apprenticeship agreement
- Funding confirmed
Step 4: Welcome Pack
- Access to pre-course materials
- Set up development environment
- Join student community
AI Data Engineer FAQs
Do I need to know how to code?
Basic Python knowledge is required – you should be comfortable writing simple scripts. If you can write functions and work with libraries, you’re ready. We provide pre-course Python refreshers if needed.
How much time commitment is required?
4 days per month in structured learning (1 theory, 3 practical), plus expect 2-4 hours per week for self-study and project work. Your employer must provide this time as part of the apprenticeship.
What if I can't attend a session?
All sessions are recorded. While live attendance is strongly encouraged for the interactive elements, you can catch up via recordings and additional support sessions.
What equipment do I need?
A laptop capable of running Docker (8GB RAM minimum, 16GB recommended) and stable internet connection. You’ll need to create free accounts for GitHub, MongoDB Atlas, Render, and other platforms. We don’t provide equipment or software, but all tools have free tiers sufficient for learning. Production deployments may require paid subscriptions.
How does the government funding work?
If your employer pays the Apprenticeship Levy (0.5% of payroll over £3m), the funding comes from that. Otherwise, the government pays 95% directly. We handle all the administration.
What software costs are involved?
For learning, all software we use has free versions – MongoDB Atlas free tier, Render free hosting, open-source AI models via Hugging Face, etc. For production systems, your organisation may need paid subscriptions (typically £25-500/month depending on scale), but these aren’t required during training.