Data Wrangling & Data Cleaning – Preparing Data for Analytics & AI
Modern organizations rely on massive volumes of data generated from applications, devices, and digital platforms. Data engineers play a crucial role in designing systems that collect, process, store, and deliver this data for analytics and machine learning.
This course introduces the core principles of data engineering, including data pipelines, ETL processes, data lakes, data warehouses, and modern data architectures.
Learners will understand how raw data moves through data systems, how it is transformed into structured datasets, and how it becomes available for analytics and business intelligence.
Through practical examples and architectural concepts, students will gain the foundational knowledge required to build scalable and reliable data pipelines used in modern cloud data platforms.
By the end of this course, learners will understand the essential building blocks of modern data engineering and data infrastructure.
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