Certificate in Edge Data Engineering

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The Certificate in Edge Data Engineering is a comprehensive course that equips learners with essential skills for career advancement in the rapidly evolving field of data engineering. This course focuses on the importance of edge data computing, a critical component of modern data architecture that brings computation and data storage closer to the source of data generation.

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With the exponential growth of data and the need for real-time data processing, edge data engineering has become increasingly important. This course covers the fundamentals of edge computing, data acquisition, processing, storage, and security, providing learners with the skills to design, build and maintain edge data systems. Upon completion of this course, learners will have a solid understanding of the edge data engineering landscape and be able to leverage their skills to advance their careers in data engineering, software development, and related fields. The course is designed to meet the growing industry demand for professionals with expertise in edge data engineering, providing learners with a competitive edge in the job market.

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• Introduction to Edge Data Engineering: Overview of edge computing, data processing at the edge, and the importance of edge data engineering.
• Data Collection and Processing: Techniques for collecting and processing data at the edge, including real-time data streaming and data preprocessing.
• Edge Analytics: Introduction to edge analytics, edge analytics use cases, and techniques for implementing edge analytics.
• Data Security and Privacy: Best practices for securing edge data, ensuring data privacy, and complying with relevant regulations.
• Edge DevOps and MLOps: DevOps and MLOps practices for edge computing, including continuous integration, continuous delivery, and monitoring at the edge.
• Selecting Edge Hardware: Factors to consider when selecting edge hardware, including power consumption, processing capabilities, and storage capacity.
• Designing and Deploying Edge Applications: Techniques for designing and deploying edge applications, including containerization and orchestration.
• Scaling Edge Infrastructure: Strategies for scaling edge infrastructure, including load balancing, fault tolerance, and disaster recovery.

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