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Courses and labs

Guided lessons built from public university exercises, upstream examples, and safe hands-on data.

These lessons teach the reasoning behind a workflow, not only which operation to click. Every lab uses synthetic or documentation-safe data, runs locally in the browser, and links to installable solution recipes.

Encoding, encryption, and hashing

Learn why these transformations solve different problems, then compare reversible and one-way workflows. Start lesson

Decode until you understand

Work through nested representations and learn when to use Magic versus an explicit recipe. Start lab

Compose and debug workflows

Build multi-step recipes, inspect intermediate values, and correct ordering mistakes. Start lesson

Structured data lab

Move among JSON, YAML, CSV, XML, and Jsonata queries. Start lab

Indicators and network data

Extract, normalize, defang, and parse common investigation values without contacting them. Start lab

Binary and file triage

Use signatures, strings, compression, hex, and disassembly to form static-analysis hypotheses. Start lab

Time and identifiers

Normalize timestamps and explain UUIDs, permissions, URIs, and IPv6 addresses. Start lab

Analyst capstone

Triage a synthetic alert by decoding a command, extracting indicators, and documenting a reproducible result. Start capstone

Teaching approach

  • Begin with a question and a sample, not an operation name.
  • Predict the output type before adding the next operation.
  • Inspect intermediate values with breakpoints or step execution.
  • Replace exploratory Magic results with an explicit, reviewable recipe.
  • Record assumptions about encodings, time zones, keys, delimiters, and trust.
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