Learn to build data systems you can explain.
From Python and SQL to Azure, Databricks and production data platforms — learn the structure behind modern Data Engineering.
- Format
- Live · Saturdays only
- Next batch
- January 2027
- Starting from
- €10
Bronze
Raw and append-only
Silver
Cleaned, deduplicated, validated
Gold
Business-ready models
People who want to understand what they build.
This track is not a tool tutorial. It is for engineers, analysts and developers who want to understand the structure of modern data systems — not just follow steps.
Developers switching to data
You understand programming but want to move into data engineering with real Azure and cloud skills.
Analysts moving into engineering
You work with data daily but want to build the pipelines that produce it, not just consume them.
Legacy IT professionals
You have years of experience and want to translate it into the modern data engineering stack.
Students & early-career engineers
You want to build practical capability before entering the job market — not just complete an online course.
Engineering before tools.
Most courses teach you how to use a tool. We teach you why the tool exists, what problem it solves, and when you should use it.
Understanding before implementation
You will know why Bronze / Silver / Gold exists, why idempotency matters in production, and how Databricks and ADF divide responsibilities before writing a single line of code.
Build things you can defend
Every project is designed so you can explain your architecture, your technical decisions, and your trade-offs — not just that it works.
Production thinking from day one
We don't wait until session 10 to introduce CI/CD, security and monitoring. These are woven throughout — because that's how real engineers work.
Choose how deep you want to go.
Three different entry points. One consistent teaching philosophy.
Masterclass
Understand the field before committing.
- 3-hour live session
- Practical introduction to Data Engineering
- Real-world architecture walkthrough
- Live demonstrations
- Q&A with the instructor
- Ideal for exploring the field
Free for colleges & student communities
Organise a session with DataKern and the Masterclass is free for your college or student community.
Crash Course
Learn the core concepts and build something real.
- 6 live sessions (Saturdays only · 2.5 hours each)
- Practical assignments each session
- Core DE tools: Python, SQL, Azure, Databricks
- End-to-end Azure data pipeline project
- Bronze / Silver / Gold architecture
Full Course
Build, troubleshoot, evaluate and defend real engineering systems.
- 12 live sessions (Saturdays only · 2.5 hours each)
- Two major capstone projects
- Advanced Spark & Databricks internals
- Production patterns: incremental loads, idempotency, schema evolution
- CI/CD, Git, testing, security & observability
- Architecture decisions & platform trade-offs
- Guest lectures from industry experts
- Personal coaching session
- Portfolio & resume review
- Mock technical interview preparation
Not sure which level is right for you?
Understand the field. Explore what Data/AI Engineering actually is before committing to a full course.
Understand + Build. Core concepts and a complete real-world project. Valuable as a standalone course.
Engineer + Troubleshoot + Optimize + Decide + Defend. Deeper engineering, production patterns, architecture decisions and personal coaching.
You can enter at any level — Masterclass is an optional starting point. Many students begin directly at Crash Course or Full Course.
What we cover across all 12 sessions.
All classes are held live on Saturdays (2.5 hours each). Sessions 1–6 form the foundation (Crash Course + Full Course), while Sessions 7–12 go deeper into advanced architecture and capstones (Full Course only).
Loading curriculum...
Leave with work you can defend.
The Full Course includes two major project milestones. The Crash Course delivers the first.
End-to-End Azure Data Pipeline
Session 6 · Crash Course + Full Course
Problem
Ingest, clean and serve raw data for a realistic business scenario.
Architecture
Bronze → Silver → Gold on ADLS with Databricks transformations.
Technology
Python · PySpark · Databricks · ADF · ADLS · Key Vault · Git
Outcome
A working, version-controlled end-to-end pipeline you built and understand.
Production Data Platform & Architecture
Session 10 · Full Course only
Problem
Redesign an existing pipeline as a production-grade enterprise system.
Challenge
Compare Databricks, ADF, Fabric and Synapse. Defend your architecture.
Focus
Scale, cost, reliability, governance and trade-offs.
Outcome
An architecture decision package you present and defend.
What you'll work with.
We teach tools in context — you learn why each one exists and when to use it, not just how to operate it.
What you'll be able to do.
After the Crash Course
Understand the structure of modern Data Engineering and build a complete end-to-end Azure data pipeline using Python, SQL, PySpark, Databricks and ADF.
After the Full Course
Build, troubleshoot, optimise and defend production-grade data systems. Reason about architecture trade-offs, apply production patterns, and explain engineering decisions with confidence.
Which format is right for you?
| Masterclass€10 | Crash Course€55 | Full Course€99 | |
|---|---|---|---|
| Duration | 3 hours | 15 hours | 30 hours |
| Live sessions | 1 session | 6 sessions (Saturdays only) | 12 sessions (Saturdays only) |
| Schedule | Single Saturday | Saturdays · 2.5h each | Saturdays · 2.5h each |
| Practical assignments | — | ✓ Each session | ✓ Each session |
| Core concepts | Introduction | ✓ Full foundation | ✓ Full foundation |
| Hands-on project | — | Main Project 1 | Projects 1 & 2 |
| Advanced engineering | — | — | ✓ Sessions 7–9 |
| Architecture | Overview | — | ✓ In depth |
| Personal coaching | — | — | ✓ Session 11 |
| Portfolio review | — | — | ✓ Session 11 |
| Interview preparation | — | — | ✓ Session 12 |
Azure Account Setup & Costs
Will I get a huge bill? No. You start with an Azure Free Account ($200 credit / 30 days). After that, the practical exercises typically cost around €5–€15 per month on pay-as-you-go.
We teach cost management on day one: how to set budget alerts, pause clusters, and clean up resources. Managing cloud costs is a core engineering skill — we practise it actively.
Why Databricks and not Synapse / Fabric?
Databricks is currently the dominant platform for Apache Spark-based engineering in the enterprise. It's cloud-agnostic, robust, and widely used across banking, retail and healthcare.
We cover Synapse and Fabric in context during Session 10 so you understand the trade-offs — but we build in Databricks. Knowing it deeply makes every other platform easier to evaluate.
Free guides
Plan your path into data engineering.
Data Engineer Roadmap: What to Learn, and in What Order
A practical data engineer roadmap: the skills to learn, the order that works, and the projects that prove you can do the job.
Read the guide · 8 min read →Data EngineeringHow to Become an Azure Data Engineer: Skills, Tools and a Learning Plan
What an Azure data engineer does, the services and skills to learn, how to practise without a big bill, and where certification stands now.
Read the guide · 8 min read →Data EngineeringHow to Choose a Data Engineering Course: A Checklist
A practical checklist for choosing a data engineering course: the syllabus, live versus recorded, projects, the instructor, and the red flags to avoid.
Read the guide · 6 min read →Frequently Asked Questions
Is this a live data engineering course online?
Is there a data engineering course near me?
Is this an Azure data engineer course?
Do I need prior cloud experience?
Do I need to pay for Azure credits?
Will we cover Databricks?
Ready to start building?
Data Engineering and AI Engineering batches are in progress. Applications are open for the January 2027 batch.
Next masterclass expected mid-December / mid-January · Start risk-free before committing.