Production Python for Data Engineers

Build production-grade code for real Data Engineering—resilient pipelines, testing, typing, logging, concurrency, CI/CD, AI-assisted development, and interview-ready engineering practices.

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Course curriculum

1. Course Introduction - Don't Skip
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2. How to Access Reference Document
3. Setup Your Learning Environment
4. Setup Coding Assistant in the IDE
5. How to use Copilot for Coding Assistance
6. How to use Claude for Coding Assistance
7. pp4de.zip
1. Concept - Basics of Packaging and Dependency Management
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2. Hands On - How to Implement Packaging and CLI Interface
3. AI Assisted - Adding New Feature and Auditing AI Assisted Work
4. Capstone Project - Implementing Your Learnings in Project
5. Interview Preparation Guide and Interview Practice Drill
6. module-1-materials.zip
1. Concept - Basics of Type Checking and Code Quality
2. Hands On - How to Implement Type Checking and Code Quality
3. AI Assisted - Adding Data Validation and Auditing AI Assisted Work
4. Capstone Project - Implementing Your Learnings in Project
5. Interview Practice Drill
6. module-2-materials.zip
1. Concepts - Basics of Retries, Backoff, Jitter and Resilience
2. Hands On - How to implement Retries, Backoff, Jitter, and Dead Letter Path
3. AI Assisted - Adding New Feature Over the Existing Retry Apparoach
4. Capstone Project - Implementing Your Learnings in Project
5. Interview Practice Drill
6. module-3-materials.zip
1. How to use this chapter - Must Watch
2. Concepts - Idempotency and Safe Reprocessing
3. Hands On - How to implement Idempotency
4. Concepts - Testing Data Pipelines, Not Just Functions
5. Hands On - How to implement Data Pipeline Testing
6. Concepts - Logging, Observability, Debuggability
7. Hands On - How to implement Logging and Observability
8. Concepts - Basics of Concurrency and Async Calls
9. Hands On - How to Implement Concurrency and Async
10. Concepts - Configuration, Secrets, Environments
11. Hands On - How to Implement Config and Secrets Management
12. Concepts - Packaging for Deployment, CI/CD
13. Hands On - Implement Packaging and CI/CD
14. module 4 to 9 materials zip
1. Project Requirement and System Design
2. Do it Yourself - Step By Step
3. Reference Solution - End State
4. Interview Practice - System Design
5. pp4de-solution.zip

About this course

$49.00
44 lessons
12.5 hours of video content

What You’ll Learn

Production Python for Data Engineers is designed to bridge the gap between knowing Python and writing Python that actually survives in production. Learn to build resilient, testable, maintainable, and scalable data pipelines using the engineering practices expected in real-world production environments.

Most Python courses teach you syntax. This one teaches you how to build the kind of code a senior data engineer is actually expected to ship — code that survives failure, gets reviewed like a real pull request, and holds up under interview-level scrutiny.

If you already know Python but have never built a production data pipeline — one that has to run unattended, recover from failure, and be trusted by a team — this course closes that exact gap.

Build and package production-grade Python projects, not just scripts.
Apply typing, Pydantic, configuration, and secrets management for reliable data pipelines.
Implement resilient error handling, retries, dead-letter paths, and idempotency.
Write unit, integration, and property-based tests, including failure scenarios.
Add structured logging and observability for effective production debugging.
Integrate AI coding assistants while maintaining strong engineering judgment.
Implement CI pipelines with automated linting, type checking, and testing.
Practice senior-level interview scenarios, debugging, and AI-generated code reviews.
uild a complete production-style capstone project that you can confidently showcase in interviews.

Frequently Asked Questions (FAQ)

How long can I access the course material?

Course access is available for the validity period selected during enrollment (1 yr or 3 yrs), including all updates released during your active subscription.
How do you provide support?

We provide support through our dedicated learner community, where you can ask questions, participate in discussions, and learn from fellow professionals. Our team actively monitors the community to assist with course-related queries whenever required.
Do you have a refund policy?

You may request a refund within 7 days of purchase or before completing 15% of the course, whichever comes first. A 6% payment processing fee will be deducted from the refund amount.