Course curriculum

Data engineering syllabus

Seven courses and two end-to-end projects — 90 modules taught live over 16 weeks.

Courses: 7
Modules: 90
Projects: 2

Get the complete syllabus

Every module and topic, plus the 12-page branded PDF.

Module-by-module topics for all 7 courses
Both end-to-end project briefs
Downloadable PDF to keep

Courses in the program

Open a course to see its modules.

Snowflake

31 modules · Store

From account setup and virtual warehouses to Snowpipe, Streams and Tasks, performance tuning, governance and data sharing.

Introduction to Snowflake
Virtual Warehouses
Pricing & Cost Management
Roles & Users
+ 27 more modules

Snowflake syllabus

SQL

8 modules · Query

Query foundations through joins, subqueries, CTEs and window functions, finishing with project-style deduplication and validation practice.

Query foundations
Tables & data operations
Functions & expressions
Aggregations
+ 4 more modules

SQL syllabus

dbt

20 modules · Transform

Build, test, document and deploy transformation models on Snowflake with dbt Cloud and GitHub — through incremental models, snapshots and scheduled jobs.

Introduction to dbt
Snowflake & dbt Cloud Setup
Project Structure & GitHub Integration
Sources & Source Freshness
+ 16 more modules

dbt syllabus

Azure Data Factory

9 modules · Ingest

Build parameterised ADF pipelines that load source data into Snowflake — full and incremental — and hand off to Airflow.

Introduction & Core Concepts
Connections & Integration Runtime
Datasets & File Configuration
Pipelines & Copy Activity
+ 5 more modules

Azure Data Factory syllabus

Fivetran

5 modules · Ingest

Configure managed connectors and syncs that land source data in Snowflake, then validate it and use it as dbt sources.

Introduction & ELT Architecture
Source & Destination Setup
Initial & Incremental Syncs
Sync Configuration & Monitoring
+ 1 more modules

Fivetran syllabus

Python

10 modules · Ingest

Write Python that extracts data from REST APIs — with pagination, retries and error handling — and loads it into Snowflake, ready for Airflow.

Python Setup & Basics
Lists & Dictionaries
Conditions & Loops
Functions & Modules
+ 6 more modules

Python syllabus

Apache Airflow

7 modules · Orchestrate

Orchestrate the whole pipeline as Airflow DAGs — trigger ADF or Fivetran, run dbt after ingestion, and handle failures safely.

Introduction & Setup
DAGs, Tasks & Dependencies
Creating Workflows
Scheduling Pipelines
+ 3 more modules

Apache Airflow syllabus

Capstone

Two end-to-end projects

Every course comes together in two complete pipelines with different ingestion tools and business requirements.

Project 1

ADF
Snowflake
dbt
Airflow

1.Extract and load source data using ADF.
2.Organize data into raw, transformation, and reporting layers in Snowflake.
3.Build dbt models, incremental transformations, and data quality tests.
4.Schedule and monitor the workflow using Airflow.
5.Connect final reporting tables to Power BI or Tableau.

Project 2

Fivetran
Snowflake
dbt
Airflow

1.Configure managed ingestion using Fivetran.
2.Handle initial and incremental syncs into Snowflake.
3.Apply a different set of business requirements through dbt transformations.
4.Coordinate ingestion and transformation runs using Airflow.
5.Prepare validated reporting models for Power BI or Tableau.

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