Introduction to Data Engineering Syllabus
Full curriculum breakdown — modules, lessons, estimated time, and outcomes.
A comprehensive and practical course that equips learners with essential data engineering skills for effective performance in various professional settings. This course spans approximately 17 hours of content, divided into four core modules and a final project, covering foundational concepts and practical applications in data engineering. Learners will explore the data engineering lifecycle, technologies, and best practices in governance and security, preparing them for entry-level roles in the field.
Module 1: What is Data Engineering?
Estimated time: 1 hours
- Understand the roles of Data Engineers, Data Scientists, and Data Analysts
- Learn about the responsibilities and skillsets of a Data Engineer
Module 2: The Data Engineering Ecosystem
Estimated time: 4 hours
- Explore different types of data structures, file formats, and sources of data
- Gain knowledge about data repositories such as relational and non-relational databases
- Understand data warehouses, data marts, and data lakes
- Learn about ETL and ELT processes, data pipelines, and data integration platforms
Module 3: The Data Engineering Lifecycle
Estimated time: 4 hours
- Understand the stages of the data engineering lifecycle
- Explore data generation, ingestion, transformation, storage, and serving
- Learn about big data processing tools like Apache Hadoop and Spark
Module 4: Data Governance, Security, and Compliance
Estimated time: 4 hours
- Learn about data security, governance, and compliance
- Understand the importance of data privacy and protection in data engineering
- Summarize concepts in data governance frameworks and regulatory standards
Module 5: Final Project
Estimated time: 4 hours
- Design a basic data pipeline using ETL principles
- Apply knowledge of data storage and processing technologies
- Document data governance and security considerations in your pipeline
Prerequisites
- Familiarity with basic data concepts
- Basic understanding of databases and SQL
- Interest in data management or analytics
What You'll Be Able to Do After
- List basic skills required for an entry-level data engineering role
- Discuss various stages and concepts in the data engineering lifecycle
- Describe data engineering technologies such as Relational Databases, NoSQL Data Stores, and Big Data Engines
- Summarize concepts in data security, governance, and compliance
- Apply foundational data engineering principles in practical scenarios