Courses
Data Engineering Curriculum
Morphera Lab offers a comprehensive, hands-on data engineering curriculum designed to take you from beginner to professional.
Complete Learning Path
Our curriculum is structured in 10 progressive parts, plus front matter and appendices, covering the current data engineering book structure.
00 Thinking Like a Data Engineer
Level: Beginner
Build the mindset and systems view needed before going deep into tools.
- The data engineer's mindset
- The modern data stack
- Reliability, ownership, and systems thinking
01 SQL: The Language of Data
Level: Beginner to Intermediate
Master database fundamentals and analytical query techniques.
- SQL fundamentals
- Joins and aggregations
- Window functions
- Schema design and stored procedures
02 Python: The Engineer's Tool
Level: Beginner to Intermediate
Learn programming essentials and data pipeline implementation.
- Python basics
- Dictionaries and string handling
- File handling, CSV, and JSON
- NumPy and Pandas
03 Orchestration: Apache Airflow
Level: Intermediate
Build and reason about orchestrated data workflows.
- Workflow orchestration
- DAG concepts
- Scheduling and production patterns
04 Engineering Practices
Level: Intermediate
Implement CI/CD, automation, and delivery practices for data work.
- Docker for data engineers
- CI/CD with GitHub Actions
- Bash scripting
05 Agentic Data Engineering
Level: Advanced
Explore AI-assisted data engineering workflows and intelligent automation patterns.
- The AI-assisted data engineer
- Claude Code and Cursor for data engineering
- Agentic pipelines
06 Cloud Warehousing: Snowflake + dbt
Level: Intermediate to Advanced
Learn cloud warehousing and transformation workflows with Snowflake and dbt.
- Snowflake architecture and setup
- Loading data into Snowflake
- dbt foundations and production practices
07 Real-Time Data: Apache Kafka
Level: Advanced
Build foundations for real-time streaming pipelines.
- Topics and partitions
- Event streaming concepts
- Real-time architecture basics
- Change data capture
08 AWS for Data Engineers
Level: Intermediate to Advanced
Deploy and reason about data solutions on Amazon Web Services.
- IAM and security
- Cloud data infrastructure
- Serverless and warehouse concepts
09 Azure for Data Engineers
Level: Intermediate to Advanced
Implement storage and data platform foundations on Microsoft Azure.
- Azure storage
- Medallion architecture with ADF and Databricks
- Azure Fabric and Synapse Analytics
Program Details
- Format: Self-paced with recommended milestones
- Current structure: 43 chapters plus appendices
- Support: Community resources and project-oriented practice