Masterclass Certificate in Edge Computing for Industry 4.0
-- viewing nowEdge Computing is revolutionizing Industry 4.0 by bringing computing power closer to data sources.
2,149+
Students enrolled
GBP £ 149
GBP £ 215
Save 44% with our special offer
About this course
This Masterclass Certificate program is designed for industry professionals and tech enthusiasts looking to master the art of edge computing.
Learn how to harness the power of edge computing to improve real-time decision making, reduce latency, and increase efficiency in manufacturing, healthcare, and other industries.
Discover the benefits of edge computing, including reduced bandwidth usage, lower latency, and increased security. Our expert instructors will guide you through hands-on projects and real-world examples.
Take the first step towards a future of smart industries and edge computing. Explore our Masterclass Certificate program today and start unlocking the full potential of edge computing for Industry 4.0.
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 in Industry 4.0. It also introduces key concepts such as fog computing, edge AI, and edge security. • Edge Computing Architecture
This unit delves into the design and implementation of edge computing architectures, including hardware and software components, network protocols, and data management systems. It also explores the role of edge computing in Industry 4.0 and its impact on IoT devices. • Edge AI and Machine Learning
This unit focuses on the application of artificial intelligence and machine learning at the edge, including edge-based computer vision, natural language processing, and predictive analytics. It also explores the challenges and opportunities of edge AI in Industry 4.0. • Edge Security and Privacy
This unit addresses the security and privacy concerns associated with edge computing, including data protection, authentication, and authorization. It also explores the role of edge security in preventing cyber threats and maintaining data integrity. • Edge Computing for Industry 4.0
This unit examines the application of edge computing in Industry 4.0, including its use in predictive maintenance, quality control, and supply chain management. It also explores the benefits and challenges of edge computing in Industry 4.0. • Fog Computing and Edge Computing
This unit compares and contrasts fog computing and edge computing, including their differences in architecture, applications, and use cases. It also explores the opportunities and challenges of fog computing in Industry 4.0. • Edge Computing for IoT
This unit focuses on the application of edge computing in IoT devices, including sensor data processing, real-time analytics, and device management. It also explores the benefits and challenges of edge computing in IoT applications. • Edge Computing for Autonomous Vehicles
This unit examines the application of edge computing in autonomous vehicles, including sensor data processing, object detection, and predictive analytics. It also explores the benefits and challenges of edge computing in autonomous vehicle systems. • Edge Computing for Smart Cities
This unit explores the application of edge computing in smart cities, including IoT device management, real-time analytics, and data-driven decision making. It also examines the benefits and challenges of edge computing in smart city infrastructure. • Edge Computing for Healthcare
This unit focuses on the application of edge computing in healthcare, including medical imaging analysis, patient monitoring, and personalized medicine. It also explores the benefits and challenges of edge computing in healthcare applications.
This unit covers the basics of edge computing, including its definition, benefits, and applications in Industry 4.0. It also introduces key concepts such as fog computing, edge AI, and edge security. • Edge Computing Architecture
This unit delves into the design and implementation of edge computing architectures, including hardware and software components, network protocols, and data management systems. It also explores the role of edge computing in Industry 4.0 and its impact on IoT devices. • Edge AI and Machine Learning
This unit focuses on the application of artificial intelligence and machine learning at the edge, including edge-based computer vision, natural language processing, and predictive analytics. It also explores the challenges and opportunities of edge AI in Industry 4.0. • Edge Security and Privacy
This unit addresses the security and privacy concerns associated with edge computing, including data protection, authentication, and authorization. It also explores the role of edge security in preventing cyber threats and maintaining data integrity. • Edge Computing for Industry 4.0
This unit examines the application of edge computing in Industry 4.0, including its use in predictive maintenance, quality control, and supply chain management. It also explores the benefits and challenges of edge computing in Industry 4.0. • Fog Computing and Edge Computing
This unit compares and contrasts fog computing and edge computing, including their differences in architecture, applications, and use cases. It also explores the opportunities and challenges of fog computing in Industry 4.0. • Edge Computing for IoT
This unit focuses on the application of edge computing in IoT devices, including sensor data processing, real-time analytics, and device management. It also explores the benefits and challenges of edge computing in IoT applications. • Edge Computing for Autonomous Vehicles
This unit examines the application of edge computing in autonomous vehicles, including sensor data processing, object detection, and predictive analytics. It also explores the benefits and challenges of edge computing in autonomous vehicle systems. • Edge Computing for Smart Cities
This unit explores the application of edge computing in smart cities, including IoT device management, real-time analytics, and data-driven decision making. It also examines the benefits and challenges of edge computing in smart city infrastructure. • Edge Computing for Healthcare
This unit focuses on the application of edge computing in healthcare, including medical imaging analysis, patient monitoring, and personalized medicine. It also explores the benefits and challenges of edge computing in healthcare applications.
Career path
| **Job Title** | **Description** |
|---|---|
| Edge Computing Engineer | Designs and implements edge computing systems for real-time data processing and analysis in Industry 4.0 applications. |
| IoT Developer | Develops and integrates Internet of Things (IoT) devices and systems for edge computing in Industry 4.0 environments. |
| Cloud Architect | Designs and implements cloud computing architectures for edge computing in Industry 4.0, ensuring scalability and security. |
| Data Scientist | Analyzes and interprets data from edge computing systems in Industry 4.0, providing insights for business decision-making. |
| DevOps Engineer | Ensures the smooth operation of edge computing systems in Industry 4.0, from development to deployment and maintenance. |
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
MASTERCLASS CERTIFICATE IN EDGE COMPUTING FOR INDUSTRY 4.0
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.
