This course contains the use of artificial intelligence.
Python is the language of automation, data, the web, and AI — and most courses teach it like a dictionary: every keyword, no judgement, nothing built. This course is the opposite. You start at a broken installation (yes, yours — the famous PATH checkbox trap) and finish with three production-style projects, a tested REST API, an idempotent data pipeline, and the interview answers senior engineers actually give.
Learn by building, not by watching. The core ten lectures take you from setup through data types, control flow, functions, OOP done right, inheritance and the MRO, professional tooling (virtual environments, pip, imports), error handling, and safe file work — every lecture built around one worked example and the trap that bites working developers: the 0.1 + 0.2 float trap, the mutable default argument that has broken real production systems, the “w” mode that erased ten years of logs.
Then build for real. Project 1: Shipshape — a file & data automation toolkit (scan → plan → apply, dry-run first, dedupe by hash, undo log) with a pytest suite that proves it is safe to run twice. Project 2: a REST API with FastAPI — designed contract-first (resources, status codes, error shapes), built live, and hardened with a TestClient suite. Project 3: a self-running data pipeline — CSV drops cleaned, loaded into SQLite idempotently, and gated by data-quality checks, so a rerun can never double your totals.
Then crack the interview. Four whiteboard lectures take on the questions that separate senior candidates: the GIL (with real timing demos — CPU-bound vs I/O-bound, threads vs processes), the mutable default trap demonstrated live, comprehensions vs generators proven with actual memory measurements, and decorators built from scratch — plus the answer framework (clarify → naive → optimise → trade-offs) that structures every answer.
Every number in this course was produced by running the code on screen — test counts, timings, memory sizes, API responses. Nothing is asserted from memory. You also get two downloadable books (Code Examples + Practice Exercises, with verified solutions), checkpoint quizzes with a 70% mastery rule, coding exercises, and a capstone assignment.
AI disclosure: this course’s narration uses a cloned voice of the instructor, created with the instructor’s consent; all content, code, and curriculum are authored and verified by the instructor team. Music: “Frozen Star” by Kevin MacLeod — CC BY 4.0.
