Showcase

This is demanding material—and that's why it works. Master the fundamental ideas of computation that shaped generations of programmers.

Master the language of AI: vectors, matrices, transformations, and eigenvalues -- with Python code to ground every concept. From NumPy basics to LoRA fine-tuning and mechanistic interpretability.

What Meta actually tests, how it evaluates, and how to think at Staff level. 27 episodes covering distributed systems fundamentals, 13 real Meta-style design problems, and capstone mock interviews.

A two-day, hands-on course on Temporal for engineers who build long-running systems — especially AI agents. You learn the execution model (history, replay, determinism, activity failure semantics) by breaking it on purpose, then build a durable agent-job runtime that survives Worker crashes, pauses for days, accepts new instructions, delegates to sub-agents, and outlives deployments. After the eleven modules you can reason architecturally about Temporal and build a serious durable agent runtime — a narrower promise than 'Temporal expert in two days', and the one this course keeps.

A two-day, hands-on course on Apache Flink for engineers who run systems that never stop — especially the infrastructure around AI models and agents. You learn the execution model (partitioned state, event time and watermarks, distributed snapshots, exactly-once) by breaking it on purpose, then operate a real-time metering pipeline for an LLM gateway that survives TaskManager deaths, late data, stalled partitions, slow dependencies and hot tenants without ever billing a minute twice. After the twelve modules you can reason architecturally about stateful stream processing and build a metering or monitoring pipeline whose numbers you would put on an invoice.