All course modules
Sequential by default, but skip what you know. Each module ends with a checkpoint.
Module 0: Development Environment
Set up your tools and workspace — IDE, CLI, Git, Docker, Python, and AI.
7 lessons
Module 1: Analytics Fundamentals
Analytics history, architecture framework, career roles, agile, and file types.
14 lessons
Module 2: Databases & SQL
Relational and NoSQL databases, SQL mastery, cloud databases, and DuckDB.
8 lessons
Module 3: Business Intelligence
BI tools, Tableau, data visualisation, MOLAP vs ROLAP, and dashboard design.
9 lessons
Module 4: Data Integration & ETL
ETL vs ELT, batch vs streaming, data pipelines, and orchestration tools.
2 lessons
Module 5: Cloud Computing
Cloud fundamentals, certifications, security, data in the cloud, and architecture.
7 lessons
Module 6: Cloud Data Warehouse
Redshift, Synapse, Snowflake, BigQuery, and ClickHouse.
0 lessons
Module 7: Apache Spark & Databricks
Apache Spark and Databricks for large-scale data processing.
0 lessons
Module 8: Hadoop Ecosystem
Hadoop on EMR and HDInsight with Hive.
0 lessons
Module 9: Data Lake & Lakehouse
Trino, Athena, Synapse Serverless, and Databricks with Delta Lake and Spark Serverless.
0 lessons
Module 10: Streaming
Apache Kafka, Apache Flink, Kinesis, Spark Structured Streaming, and Delta Streaming.
0 lessons
Module 11: ML Fundamentals for Data Engineers
Machine learning fundamentals tailored for data engineers.
0 lessons
Module 12: Best Practices, DevOps & Soft Skills
Best practices for data engineers including DevOps and soft skills.
0 lessons