Data Engineering on the Cloud
Build practical skills in data engineering on the cloud and apply key concepts, tools, and techniques to real-world business and technology scenarios.
Course Overview
Course Overview Module 1: Core Concepts • Introduction to Data Engineering on the Cloud • Designing scalable pipelines using cloud-native tools • Core concepts and terminology • Key tools, techniques and workflows Module 2: Tools & Techniques • Core concepts and terminology • Key tools, techniques and workflows • Practical exercises and use cases • Best practices and implementation considerations Module 3: Practical Implementation • Core concepts and terminology • Key tools, techniques and workflows • Practical exercises and use cases • Best practices and implementation considerations Module 4: Applied Skills • Core concepts and terminology • Key tools, techniques and workflows • Practical exercises and use cases • Best practices and implementation considerations Module 5: Real-World Application • Practical exercises and use cases • Best practices and implementation considerations • Real-world business use cases • Best practices and key takeaways
Learning Outcomes
Understand the core concepts and terminology of Data Engineering on the Cloud.
Apply relevant tools, techniques, and workflows in practical scenarios.
Analyze common problems and select appropriate approaches.
Work through real-world examples and business use cases.
Apply best practices to improve quality, efficiency, and outcomes.
Prerequisites
• Basic computer and internet skills. • Basic understanding of the relevant business or technology context. • Logical and analytical thinking. • Willingness to participate in practical exercises. • No prior experience in the specific course topic is required unless otherwise stated.
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