Certified Specialist Programme in Edge Computing for Non-Data Scientists
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- Introduction to Edge Computing: Fundamentals and Applications
- Edge Computing Architecture and Deployment Models: Fog Computing, Cloudlets
- Edge Devices and Sensors: Hardware and Software Considerations
- Data Processing at the Edge: Real-time Analytics and Data Filtering
- Security and Privacy in Edge Computing: Threats and Mitigation Strategies
- Edge Computing Use Cases and Industry Applications: IoT, AI, and Machine Learning at the Edge
- Network Infrastructure for Edge Computing: 5G, low-latency networks
- Edge Computing Management and Orchestration: Tools and Techniques
- Practical Implementation of an Edge Computing System: A hands-on project
- Case Studies in Edge Computing: Successful deployments and best practices
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Job Role Description Edge Computing Specialist Develops and implements edge computing solutions, focusing on low-latency applications and data processing near the data source.
High demand for cloud integration skills.
IoT Edge Developer Designs and builds software for Internet of Things (IoT) devices at the edge, leveraging edge analytics for real-time insights.
Strong network knowledge essential.
Edge AI Engineer Implements and optimizes artificial intelligence algorithms at the edge, focusing on efficient model deployment and performance.
Expertise in machine learning and deep learning is crucial.
Cloud Edge Architect Designs and manages the architecture of hybrid cloud and edge computing environments, ensuring seamless data flow and scalability.
Requires proficiency in cloud platforms and edge technologies .
EntryRequirements
- BasicUnderstandingSubject
- ProficiencyEnglish
- ComputerInternetAccess
- BasicComputerSkills
- DedicationCompleteCourse
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- ThreeFourHoursPerWeek
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