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AI Closed Loop Management Architecture Fundamentals
Closed loop automation is a crucial element of any service provider’s automation. It will be essential for minimizing operational expenses, improving productivity, and increasing scalability while enhancing the end-user experience.
The traditional network and service operations cannot continue to operate with its current labor intensive approach, due to the dynamic nature of the new networks.
With 5G, virtual network functions (VNFs), cloud native network functions (CNFs) and software-defined networking (SDN), it means that the rate at which these networks can scale up or down is growing exponentially. This associated complexity creates the need for AI driven automated management.
In this course, you will learn about an AI Closed Loop Automation Reference Architecture and process flows around key use cases, including the Closed Loop Anomaly Detection and Resolution Automation (CLADRA) reference architecture. You will gain knowledge on how to define and automate anomaly detection and resolution through standard functions, components and interfaces.
This one-day course is offered in expert-led virtual or in-person session to ensure a balance of classroom style education and interactive, hands-on exercises to maximize your learning.
Level: Fundamentals
Pre-requisites: AI and Automation – Deploying in ODA Overview is recommended
Duration: 1 day
Access period: *30 days (default) from date of enrolment.
*Note:
1) Does not apply for enterprise deals (they have fixed end-date)
2) Simultaneous multiple course or bundle enrolment will grant 30 days x #courses for all courses simultaneously enrolled (e.g. 2 courses = 60-day access, 3 courses = 90 days, etc.)
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Take this course in-person (onsite or virtual):
Download the datasheet for this course.
Who should attend?
This course is suitable for:
- Anyone tasked with ensuring autonomous network within telecoms delivers value to the business
- Data Scientists working for enterprise application providers or integrators
- Anyone working at the practical level of data research and analytics and its impacts on the 5G rollouts
- Engineers and Architects working on learning how to implement new AI solutions into networks
- Anyone investigating the field of AI and its challenges and practicalities in its rollout.
What will you learn?
- The basic principles and definitions of a closed loop system
- Business drivers and benefits of AI closed loop implementations for industry, CSPs and different parties
- The use of closed loop within the wider autonomous network architectures and standards
- The underlying AI closed loop model and its relationship to the CLADRA architecture
- Applying closed loop solutions in the real world through case studies
- The challenges of implementation of closed loop solutions
Course Syllabus
- Module 1 AI closed loop – introduction & drivers
- Module 2 Principles & Closed Loop Architecture overview
- Module 3 AI Closed Loop Modelling (AI-CLM) & CLADRA
- Module 4 Case studies of AI closed loop
- Module 5 Challenges of AI closed loop management implementation
- Module 6 Summary & next steps
Certification
A course attendance certificate is issued on satisfactory completion of the course. There is a knowledge certification exam also associated with the course material. Passing this exam counts towards the TM Forum Skill certification. Find out more here.