AI-Powered Infrastructure and Operations in Telecommunications
1h 30mIntermediate2026-05-07
Authors
Rahul Kaundal
Itelcotech
Course details
Explore the essential components of AI-powered infrastructure and operations in telecommunications through this comprehensive course. Gain insights about the fundamental concepts of generative AI and large language models, essential for tackling telecom-specific challenges. Examine how GPUs serve as a crucial power grid, enabling parallel processing and efficient resource utilization. Review the deep learning software stack and GPU virtualization, learning how to maximize efficiency in AI data centers. Learn how to manage performance and energy efficiency while navigating complex multi-GPU systems and data center architectures. Discover the significance of InfiniBand, networking, and storage solutions tailored for AI workloads. Learn how to optimize your AI infrastructure. By the end of this course, you'll be equipped with the knowledge of how to design and implement cutting-edge AI deployment strategies in the cloud, bridging the gap between theory and practice in telecom settings.
Audience
Professionals working in the telecom industry
AI engineers
Technical enthusiasts
AI engineers expanding into telecom
Tech managers and decision-makers
Students and researchers
Audience
Professionals working in the telecom industry
AI engineers
Technical enthusiasts
AI engineers expanding into telecom
Tech managers and decision-makers
Students and researchers
Concepts
Introduction
- Introduction
Understanding Generative AI, LLMs, and Foundation Models
- Understanding generative AI
- Understanding large language models
- Foundation models - The core of generative AI
GPUs and Scalable AI Compute Systems
- How generative AI solves enterprise challenges
- Why GPUs power generative AI
- Inside the GPU - The AI factory
- The power of parallel processing
- CPU vs GPU - The right tool for the job
- GPU server systems scaling beyond single GPUs
AI Software, Virtualization, and Data Centre Foundations
- GPUs - The power grid for AI
- Virtual GPU sharing - power maximizing efficiency
- GPU virtualization intelligent fleet management for AI
- Machine learning and deep learning frameworks
- The deep learning software stack
- Where does AI live
- The three pillars of AI data centres
AI Data Centre Architecture and Networking
- Managing and monitoring an AI data centre
- The modern data centre platform
- Multi GPU systems powering telecom AI
- The four networks of an AI data centre
- Networking for AI workloads
- InfiniBand - The supersonic rail system for AI
- The silent crisis of AI infrastructure
- Storage file systems for AI data centres
Performance and Cloud AI Infrastructure
- Storage performance for AI - The championship pit crew
- Energy efficiency in AI data centres
- Why GPU cooling architecture matters
- Reference architectures and AI in the cloud
- AI in the cloud
Cloud AI Deployment and Telecom Use Cases
- Conclusion
- Deploying AI in the cloud - A strategic blueprint
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