Production Python +
PySpark + Databricks
Go from Zero to Production-Ready Data Engineer in 12 Weeks
The full syllabus below stays published so you can judge the depth before the next batch opens. If you want to start learning now, the Agentic AI Portfolio course is currently enrolling.
Every Session, Same Format
Consistent structure for maximum learning efficiency
settle In
Quick recap + 1 common mistake from homework
concept
Real-world scenario with 3-5 slides max
live Build
Code the solution together (37 min hands-on)
gotchas
What breaks in real production systems
homework
Task that builds toward your capstone
Your Starting Point Matters
Jump in at the right week based on your experience
Start from
Week 1
No programming experience
Start from
Week 5
Python developer, new to data
Start from
Week 7
Data analyst with SQL + Python
Start from
Week 11
Experienced engineer, needs Databricks
10 Modules, 12 weeks
From Python fundamentals to production-ready Databricks pipelines
Week 1: Core Python Essentials
- Environment Setup: Terminal, Python, VS Code & Virtual Environments
- Variables, Data Types, Strings & Type Conversion
- Lists, Loops & Conditional Logic
- Dictionaries, Sets & Tuples
Week 2: Intermediate Python
- Functions, Arguments, Scope & Modules
- File I/O: CSV, JSON & Text Files
- Comprehensions, Generators & Lambda Functions
- Error Handling, Custom Exceptions & Logging
4 Portfolio-Ready Projects
Build real production systems that demonstrate your skills
Python, Pandas, APIs, Git, error handling
Testing, config, logging, retries, project structure
Spark transforms, joins, windows, performance, testing
Delta, Databricks, medallion, CI/CD, governance
12-Week Learning Path
Your weekly topic breakdown at a glance
| Week | Mon | Tue | Wed | Thu |
|---|---|---|---|---|
W1 | Terminal & Setup | Variables & Types | Lists & Loops | Dicts & Sets |
W2 | Functions | File I/O | Comprehensions | Error Handling |
W3 | OOP & Dataclasses | Git Basics | Git Workflows | Packages |
W4 | Pandas Basics | Pandas Advanced | REST APIs | Async Python |
W5 | SQL Fundamentals | Advanced SQL | Data Modeling | Dimensional Design |
W6 | Pydantic & Types | Config & Logging | Pytest | Project Structure |
W7 | Cloud Storage | Docker | Resilience Patterns | Data Quality |
W8 | Spark Intro | DataFrame Ops | Aggregations | Schemas & Formats |
W9 | Joins | Windows | Complex Types | Spark SQL |
W10 | Spark Internals | Performance Tuning | Caching Lab | Streaming |
W11 | Databricks | Delta Lake | MERGE Patterns | Optimization |
W12 | Unity Catalog | Auto Loader | Medallion | Capstone |
Launch Your Data Engineering Career
Graduate with the skills top companies are hiring for
Ready to Become a Data Engineer?
48 live sessions, 4 portfolio projects, zero to production-ready data engineering in 12 weeks.
We keep cohorts in sync rather than letting people join a half-finished syllabus. The next batch has not been dated yet.
Questions? Contact us at hello@thrivewithai.com