Certified Professional in Edge Computing for Training
-- viewing nowEdge Computing is revolutionizing the way data is processed and analyzed. This Certified Professional in Edge Computing for Training program is designed for IT professionals, data scientists, and engineers who want to master the art of edge computing.
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About this course
Learn how to design, deploy, and manage edge computing systems that provide real-time insights and improve application performance.
Key topics include edge computing architecture, edge computing protocols, and edge computing applications. You'll also explore the benefits of edge computing, such as reduced latency, improved security, and increased efficiency.
Take your career to the next level with this comprehensive training program.
Explore the world of edge computing today and discover how it can transform your organization.
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Course details
•
Edge Computing Fundamentals: This unit covers the basics of edge computing, including its definition, benefits, and applications. It also introduces key concepts such as fog computing, edge AI, and edge analytics. •
Network Fundamentals for Edge Computing: This unit delves into the networking aspects of edge computing, including network architecture, protocols, and security. It also covers the role of 5G networks in edge computing. •
Edge Computing Platforms and Frameworks: This unit explores the various edge computing platforms and frameworks available, including EdgeX, AWS IoT Greengrass, and Google Cloud Edge. It also discusses their features, use cases, and deployment models. •
Edge AI and Machine Learning: This unit focuses on the application of artificial intelligence and machine learning at the edge, including edge AI frameworks, edge machine learning, and edge deep learning. •
Edge Analytics and Data Processing: This unit covers the edge analytics and data processing capabilities of edge computing, including edge data processing, edge data storage, and edge data analytics. •
Security and Privacy in Edge Computing: This unit discusses the security and privacy concerns in edge computing, including edge security protocols, edge data encryption, and edge access control. •
Edge Computing Use Cases: This unit explores various use cases of edge computing, including IoT, smart cities, industrial automation, and autonomous vehicles. •
Edge Computing Architecture and Design: This unit covers the design principles and architecture patterns for edge computing, including edge computing architecture, edge computing design patterns, and edge computing scalability. •
Edge Computing and 5G Networks: This unit discusses the integration of edge computing with 5G networks, including 5G edge computing, 5G network slicing, and 5G edge analytics. •
Edge Computing and IoT: This unit focuses on the application of edge computing in IoT, including IoT edge computing, IoT data processing, and IoT analytics.
Edge Computing Fundamentals: This unit covers the basics of edge computing, including its definition, benefits, and applications. It also introduces key concepts such as fog computing, edge AI, and edge analytics. •
Network Fundamentals for Edge Computing: This unit delves into the networking aspects of edge computing, including network architecture, protocols, and security. It also covers the role of 5G networks in edge computing. •
Edge Computing Platforms and Frameworks: This unit explores the various edge computing platforms and frameworks available, including EdgeX, AWS IoT Greengrass, and Google Cloud Edge. It also discusses their features, use cases, and deployment models. •
Edge AI and Machine Learning: This unit focuses on the application of artificial intelligence and machine learning at the edge, including edge AI frameworks, edge machine learning, and edge deep learning. •
Edge Analytics and Data Processing: This unit covers the edge analytics and data processing capabilities of edge computing, including edge data processing, edge data storage, and edge data analytics. •
Security and Privacy in Edge Computing: This unit discusses the security and privacy concerns in edge computing, including edge security protocols, edge data encryption, and edge access control. •
Edge Computing Use Cases: This unit explores various use cases of edge computing, including IoT, smart cities, industrial automation, and autonomous vehicles. •
Edge Computing Architecture and Design: This unit covers the design principles and architecture patterns for edge computing, including edge computing architecture, edge computing design patterns, and edge computing scalability. •
Edge Computing and 5G Networks: This unit discusses the integration of edge computing with 5G networks, including 5G edge computing, 5G network slicing, and 5G edge analytics. •
Edge Computing and IoT: This unit focuses on the application of edge computing in IoT, including IoT edge computing, IoT data processing, and IoT analytics.
Career path
| **Edge Computing Developer** | Job Market Trends | Salary Range (£) | Job Satisfaction |
|---|---|---|---|
| Job Description: Design, develop, and deploy edge computing systems and applications. | High demand for edge computing solutions in industries like retail, healthcare, and finance. | £60,000 - £80,000 | High job satisfaction due to opportunities for innovation and growth. |
| **Cloud Architect** | Job Market Trends | Salary Range (£) | Job Satisfaction |
| Job Description: Design and build cloud computing systems and architectures. | High demand for cloud computing solutions in industries like e-commerce, media, and entertainment. | £70,000 - £90,000 | High job satisfaction due to opportunities for innovation and leadership. |
| **Data Scientist** | Job Market Trends | Salary Range (£) | Job Satisfaction |
| Job Description: Analyze and interpret complex data to inform business decisions. | High demand for data scientists in industries like finance, healthcare, and retail. | £65,000 - £85,000 | High job satisfaction due to opportunities for innovation and impact. |
| **DevOps Engineer** | Job Market Trends | Salary Range (£) | Job Satisfaction |
| Job Description: Ensure the smooth operation of software systems and infrastructure. | High demand for DevOps engineers in industries like technology, finance, and healthcare. | £75,000 - £95,000 | High job satisfaction due to opportunities for innovation and collaboration. |
| **Artificial Intelligence/Machine Learning Engineer** | Job Market Trends | Salary Range (£) | Job Satisfaction |
| Job Description: Design and develop AI and ML models and systems. | High demand for AI and ML engineers in industries like technology, finance, and healthcare. | £55,000 - £80,000 | High job satisfaction due to opportunities for innovation and impact. |
Entry requirements
- Basic understanding of the subject matter
- Proficiency in English language
- Computer and internet access
- Basic computer skills
- Dedication to complete the course
No prior formal qualifications required. Course designed for accessibility.
Course status
This course provides practical knowledge and skills for professional development. It is:
- Not accredited by a recognized body
- Not regulated by an authorized institution
- Complementary to formal qualifications
You'll receive a certificate of completion upon successfully finishing the course.
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CERTIFIED PROFESSIONAL IN EDGE COMPUTING FOR TRAINING
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Learner Name
who has completed a programme at
London School of Planning and Management (LSPM)
Awarded on
05 May 2025
Blockchain Id: s-1-a-2-m-3-p-4-l-5-e
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