Programming Languages for Data Engineering
Description
Essential programming skills including Python, SQL, and scripting languages required for data engineering tasks.
Learning Objectives
Learners will master Python programming for data manipulation, write complex SQL queries for data transformation, understand scripting for automation, and apply programming concepts to data engineering workflows.
Topics (6)
Advanced SQL concepts including joins, subqueries, window functions, CTEs, and optimization techniques for large datasets.
Linux/Unix shell scripting fundamentals, bash programming, and automation techniques for data workflows.
Git fundamentals, branching strategies, collaboration workflows, and best practices for data engineering code management.
Essential data structures (arrays, lists, dictionaries, trees) and algorithms for data engineering optimization.
RESTful API development, authentication, rate limiting, and integration patterns for data engineering systems.
Comprehensive Python programming including data structures, control flow, functions, and essential libraries like pandas, boto3, and requests.