Professional Certificate in Edge Computing for Edge Edge AI
-- viewing nowEdge Computing is revolutionizing the way data is processed and analyzed. This Professional Certificate in Edge Computing for Edge AI is designed for IT professionals, data scientists, and engineers who want to master the art of edge computing.
5,717+
Students enrolled
GBP £ 149
GBP £ 215
Save 44% with our special offer
About this course
Learn how to deploy, manage, and optimize edge computing solutions that enable real-time processing, reduced latency, and improved decision-making.
Discover the benefits of edge computing, including increased security, reduced bandwidth usage, and enhanced IoT capabilities.
Gain hands-on experience with edge computing frameworks, such as EdgeX and AIOps, and learn how to integrate AI and machine learning models into edge computing architectures.
Take your career to the next level by acquiring the skills and knowledge needed to design, deploy, and manage edge computing solutions.
Explore the Professional Certificate in Edge Computing for Edge AI today and start unlocking the full potential of edge computing!
100% online
Learn from anywhere
Shareable certificate
Add to your LinkedIn profile
2 months to complete
at 2-3 hours a week
Start anytime
No waiting period
Course details
•
Edge Computing Fundamentals: This unit covers the basics of edge computing, including its definition, benefits, and applications. It also introduces the concept of edge AI and its role in edge computing. •
Edge AI for Computer Vision: This unit focuses on the application of edge AI in computer vision, including object detection, image classification, and facial recognition. It also covers the use of deep learning models in edge computing. •
Edge AI for Natural Language Processing: This unit explores the application of edge AI in natural language processing, including text classification, sentiment analysis, and speech recognition. It also covers the use of edge AI in chatbots and virtual assistants. •
Edge Computing Security: This unit covers the security aspects of edge computing, including data encryption, access control, and secure communication protocols. It also introduces the concept of edge security threats and vulnerabilities. •
Edge AI for IoT Devices: This unit focuses on the application of edge AI in IoT devices, including sensor data processing, predictive maintenance, and anomaly detection. It also covers the use of edge AI in smart homes and cities. •
Edge Computing Architecture: This unit covers the design and implementation of edge computing architectures, including edge gateways, edge servers, and fog computing. It also introduces the concept of edge computing frameworks and tools. •
Edge AI for Autonomous Vehicles: This unit explores the application of edge AI in autonomous vehicles, including sensor data processing, object detection, and predictive maintenance. It also covers the use of edge AI in autonomous drones and robots. •
Edge Computing for Industrial Automation: This unit focuses on the application of edge computing in industrial automation, including predictive maintenance, quality control, and supply chain management. It also covers the use of edge AI in industrial IoT devices. •
Edge AI for Healthcare: This unit covers the application of edge AI in healthcare, including medical image analysis, patient monitoring, and disease diagnosis. It also introduces the concept of edge AI in telemedicine and remote healthcare. •
Edge Computing and 5G Networks: This unit explores the integration of edge computing with 5G networks, including edge computing for 5G IoT, edge computing for 5G security, and edge computing for 5G analytics.
Edge Computing Fundamentals: This unit covers the basics of edge computing, including its definition, benefits, and applications. It also introduces the concept of edge AI and its role in edge computing. •
Edge AI for Computer Vision: This unit focuses on the application of edge AI in computer vision, including object detection, image classification, and facial recognition. It also covers the use of deep learning models in edge computing. •
Edge AI for Natural Language Processing: This unit explores the application of edge AI in natural language processing, including text classification, sentiment analysis, and speech recognition. It also covers the use of edge AI in chatbots and virtual assistants. •
Edge Computing Security: This unit covers the security aspects of edge computing, including data encryption, access control, and secure communication protocols. It also introduces the concept of edge security threats and vulnerabilities. •
Edge AI for IoT Devices: This unit focuses on the application of edge AI in IoT devices, including sensor data processing, predictive maintenance, and anomaly detection. It also covers the use of edge AI in smart homes and cities. •
Edge Computing Architecture: This unit covers the design and implementation of edge computing architectures, including edge gateways, edge servers, and fog computing. It also introduces the concept of edge computing frameworks and tools. •
Edge AI for Autonomous Vehicles: This unit explores the application of edge AI in autonomous vehicles, including sensor data processing, object detection, and predictive maintenance. It also covers the use of edge AI in autonomous drones and robots. •
Edge Computing for Industrial Automation: This unit focuses on the application of edge computing in industrial automation, including predictive maintenance, quality control, and supply chain management. It also covers the use of edge AI in industrial IoT devices. •
Edge AI for Healthcare: This unit covers the application of edge AI in healthcare, including medical image analysis, patient monitoring, and disease diagnosis. It also introduces the concept of edge AI in telemedicine and remote healthcare. •
Edge Computing and 5G Networks: This unit explores the integration of edge computing with 5G networks, including edge computing for 5G IoT, edge computing for 5G security, and edge computing for 5G analytics.
Career path
| Role | Salary Range (£) | Job Market Trend (%) |
|---|---|---|
| Edge AI Engineer | £80,000 - £100,000 | 85% |
| Cloud Architect | £120,000 - £150,000 | 90% |
| Data Scientist | £90,000 - £120,000 | 95% |
| DevOps Engineer | £80,000 - £110,000 | 80% |
| Artificial Intelligence/Machine Learning Engineer | £110,000 - £140,000 | 92% |
| Cyber Security Specialist | £80,000 - £110,000 | 85% |
| Network Engineer | £60,000 - £90,000 | 75% |
| Data Analyst | £50,000 - £80,000 | 70% |
| Business Analyst | £60,000 - £90,000 | 80% |
| IT Project Manager | £80,000 - £110,000 | 85% |
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.
Why people choose us for their career
Loading reviews...
Frequently Asked Questions
Debug: False
Course fee
MOST POPULAR
Fast Track
GBP £149
Complete in 1 month
Accelerated Learning Path
- 3-4 hours per week
- Early certificate delivery
- Open enrollment - start anytime
Standard Mode
GBP £99
Complete in 2 months
Flexible Learning Pace
- 2-3 hours per week
- Regular certificate delivery
- Open enrollment - start anytime
What's included in both plans:
- Full course access
- Digital certificate
- Course materials
All-Inclusive Pricing • No hidden fees or additional costs
Get course information
Earn a career certificate
PROFESSIONAL CERTIFICATE IN EDGE COMPUTING FOR EDGE EDGE AI
is awarded to
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
Add this credential to your LinkedIn profile, resume, or CV. Share it on social media and in your performance review.
