AI Masterclass for Telecom Professionals
Course Overview
As the telecom industry continues to leverage AI for optimization, predictive maintenance, customer experience enhancement and autonomous operations, it is crucial for professionals in the field to master these technological advancements.
This is an immersive course designed to equip telecommunication engineers with the necessary tools, strategies, and insights to implement AI effectively within the telecom industry. In this 5-day program, participants will navigate the AI landscape, systems architecture, and design principles, and get involved in hands-on practices such as AI programming for telecom applications.
With an ideal blend of theoretical principles and practical applications, participants will learn how to become proficient in the design and implementation of scalable and efficient AI systems.
Target Audience
- Telecom engineers and professionals who are keen on expanding their skillsets in AI
- Professionals working in roles related to network operations, service delivery, RAN engineers, and customer experience within the telecom industry
Duration & Training Format
- Classroom: 5 days
- LIVE Virtual*: 35 hours
*Note:
- A minimum of 6 or more participants are required for a company-based LIVE Virtual course to commence
- LIVE Virtual courses can be conducted for 5 hours or 7 hours daily. Please note that the number of training days will be extended if you opt for 5 hours daily.
Upcoming Course Dates
13 – 17 May 2024 (Mon – Fri), GMT +08:00
18 – 22 Nov 2024 (Mon – Fri), GMT +08:00
If you are keen on attending the above courses, please register your interest via our course enquiry form.
Course Objectives
At the end of this course, participants will be able to:
- Understand the fundamentals of AI, Machine Learning, and Deep Learning and their application in the telecoms industry
- Gain proficiency in AI tools, frameworks and Python programming for AI using critical AI libraries
- Learn to design and manage AI system architectures, focusing on telecom-specific needs and challenges, such as real-time inference and continuous learning
- Gain hands-on experience in deploying AI solutions, operating and managing AI at scale (MLOps), Machine Learning model lifecycle management, and scaling AI solutions
- Explore advanced AI topics like Large Language Models (LLMs) and their application in the Telecoms Industry, Trustworthy AI, AI ethics, and governance in the context of telecom
Course Outline
- Introduction to AI and its Role in Telecoms
- Understanding AI
- Understanding Machine Learning
- Understanding Deep Learning
- The Role of AI in Telecom
Hands-on:
- Introduction to AI/ML Tools and Frameworks
- Introduction to Python Programming Basics, Syntax, Data Structures, and Control Flow
- Demystifying AI Technologies
- AI System Design
- Exploring Natural Language Processing
Hands-on:
- Exploring Key Libraries and their usage in AI
- The High-level Structure of an AI App
- Deep Learning and Telecom-centric AI Architectures
- The AI Product and the Role of Data
- Advanced Deep Learning
- Designing Telecom AI Systems
- Hands-on: Python for Deep Learning
Hands-on:
- Python for Deep Learning
- AI Deployment, Management, and Operations
- AI Life Cycle Management
- AI Deployment in Telecoms
- Challenges in AI Implementation
- Deployment Considerations
- Scaling AI
- Microservices, Containers, Kubernetes, and Serverless Deployments
- Monitoring and Updating Models
Hands-on:
- Exploring Tools (eg. MLFlow, TensorFlow Extended, Kubeflow) and how they fit into the ML Lifecycle
- Packaging and Serving AI Models – Docker Containers, Flask, FastAPI
- Advanced AI Topics and AI Ethics
- Advanced AI Concepts
- AI and Ethics
- Trustworthy AI
- Future of AI
Hands-on:
- Python for Trustworthy AI
Note: A Certificate of Completion will only be issued upon achieving at least 75% attendance for the course.
Pre-requisites
A basic understanding of programming and telecom operations, along with a high-level understanding of how modern software works would be beneficial.
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