Ethereum & DeFi Analytics with Python: Web3, AMMs & RPC

Blockchain data is fully transparent — but knowing how to analyze it requires the right mental model.

In this course, you’ll learn how a public smart-contract network exposes data through blocks, transactions, receipts, and event logs — and how Python can be used to interact with those data surfaces programmatically. Rather than jumping straight into complex code or mathematical derivations, this course focuses on building a structured conceptual foundation for on-chain analytics.

We begin by understanding how transactions trigger execution inside the virtual machine, how state changes are recorded, and how logs provide an append-only record of protocol activity. From there, we explore how remote procedure calls (RPC) expose blockchain data to external applications, and how an analytics workflow transforms raw execution data into structured, analysis-ready datasets.

You’ll learn:

• What “on-chain analytics” means in practice

• The mental model of state, execution, and logs

• How blocks, transactions, and receipts relate to each other

• How event logs become the primary analytics surface

• How a simple analytics pipeline works from retrieval to transformation

This course is designed for developers, analysts, and technically curious learners entering Web3 who want clarity before complexity.

No prior blockchain experience is required. Basic familiarity with Python is helpful but not mandatory.

If you want a clean, structured introduction to blockchain data and analytics workflows, this course provides the foundation.