About This Path

Modern data and AI work depends on hardware — but hardware terminology can feel opaque. This path explains the key components in plain language: what they are, what they do, and how they relate to software, data, and AI. No technical background required.

  • Difficulty: Beginner
  • 8 lessons reading
  • No prior knowledge required
What You Will Learn
  • What hardware is and how it relates to software
  • What a CPU does and what cores and clock speed mean
  • How RAM works and why it differs from storage
  • The difference between HDDs, SSDs, and NVMe
  • What a GPU does and why it matters for AI
  • What bandwidth and latency mean in networking
  • How servers, virtual machines, and cloud computing work
  • How hardware components support data and AI workloads
Lesson 1

Understanding Computer Hardware

What hardware is, how it relates to software, and the main categories of components found in modern computers.

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Lesson 2

CPU Fundamentals

What a CPU does, how cores and threads work, and why processing speed matters for data and software tasks.

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Lesson 3

Memory (RAM)

What RAM is, how working memory affects performance, and how RAM differs from storage.

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Lesson 4

Storage Systems

How HDDs, SSDs, and other storage technologies work, what capacity means, and why backup matters.

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Lesson 5

GPU Fundamentals

What a GPU does, how parallel processing works, and why GPUs are frequently discussed in AI and data contexts.

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Lesson 6

Networks and Connectivity

How computers connect to each other and the internet, what bandwidth and latency mean, and how local networks work.

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Lesson 7

Servers and Cloud Computing

What servers are, how cloud computing works, what virtual machines are, and how data centres support modern infrastructure.

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Lesson 8

Hardware for Data and AI

How CPU, GPU, RAM, storage, and networking work together to support analytics, databases, AI, and cloud workloads.

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