MODULE 3

☁️Cloud & AI Infrastructure

Data centers, cloud computing, AI infrastructure, and the economics of large-scale computing.

📝5 Topics
⏱️~125 min

🎯Learning Objectives

  • Map the global data center footprint and design considerations
  • Quantify AI compute requirements and infrastructure economics
  • Evaluate sustainability, resilience, and outage scenarios
Topic 3.1
Core Concept

The Global Data Center Ecosystem

Map the worldwide network of data centers powering the internet. Understand hyperscale facilities, colocation services, edge computing, and the geographic distribution of cloud infrastructure.

⏱️30 min
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Topic 3.2
Core Concept

Data Center Architecture & Design

Dive into data center design principles. Learn about power distribution, cooling systems, networking architecture, and the engineering that keeps massive facilities running 24/7.

⏱️35 min
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Topic 3.3
Core Concept

AI Infrastructure & LLM Economics

Understand the massive compute requirements for training and running AI models. Explore GPU clusters, AI accelerators, and the economics of large language models.

⏱️35 min
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Topic 3.4
Research

Energy, Power & Sustainability

Examine the enormous energy demands of cloud and AI infrastructure. Understand power consumption patterns, renewable energy initiatives, and environmental challenges.

⏱️30 min
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Topic 3.5
Application

Cloud Economics & Resilience

Analyze cloud computing business models, pricing strategies, and infrastructure resilience. Learn about outages, disaster recovery, and the economic impact of downtime.

⏱️25 min
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