// 7 courses indexed
The course directory
Every course we track across 10+ providers, in one searchable index. Want a shortlist picked for your goals? Run a free skill gap analysis.
Shipping Rust
Take a Rust crate from a "works on my machine" laptop build to a production-grade artifact that ships through a gate no one can bypass. The course walks through a real 3-crate ETL workspace — etl-core, etl-cli, and etl-bench — built around clap derive macros, a tuned `[profile.release]`, and a multi-stage Dockerfile that drops a 1.8 GB rust:latest image to a 6 MB scratch+musl container with no shell to attack. You then wire pmat, bashrs, forjar, and pv onto the standard fmt + clippy + test + 100% coverage + audit + deny stack — because a green build badge is misleading when an agent wrote half
All levels
HelixDB From Zero
Stop stitching three databases together. HelixDB is a Rust-native graph plus vector engine that holds your nodes, your embeddings, your typed edges, and your key-value documents in one process — no separate Postgres, no separate Qdrant, no separate Neo4j. This course walks a Rust-fluent engineer from helix init through a typed HelixQL schema, the helix check and helix compile pre-deploy gates, side-by-side graph traversal and vector search in the same query language, and a typed Rust client that calls a live HelixDB instance with four runtime contracts. Every primitive you meet is wired into a
All levels
Production ML with Hugging Face
Learn to deploy ML models to production using the Sovereign Rust Stack—a pure Rust implementation with zero Python runtime dependencies. This hands-on course teaches you to work with three critical model formats (GGUF, SafeTensors, APR), implement MLOps pipelines with CI/CD and observability, and deploy models across GPU, CPU, WebAssembly, and edge targets. Through real-world projects including a Python-to-Rust transpiler (Depyler), browser-based speech recognition (Whisper.apr), and LLM inference benchmarking (Qwen), you'll master format conversion, cryptographic model signing, and performan
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ETL Pipelines with Rust
Build production-grade ETL pipelines in Rust that never drop rows silently and never panic on malformed input. In five weeks you will design the Extract boundary with serde-typed readers, enforce a Transform totality contract where every row either yields a validated record or flows through a structured error channel, and emit NDJSON and CSV from the same typed pipeline using the Write trait. You will master thiserror enums, ? propagation, proptest-based property testing, round-trip invariants, and the stderr-vs-stdout separation that makes every pipeline run auditable. The course closes with
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Big O notation: Python to Rust
Big O notation: Python to Rust is a hands-on algorithmic complexity course for engineers transitioning from Python to Rust who want to reason rigorously about how their code scales. You will learn Big O, Big Theta, and Big Omega notation; analyze the time and space complexity of common operations on Python and Rust data structures (list/Vec, dict/HashMap, set/HashSet, tuple, slice, BTreeMap); and compare measured performance in both languages on identical workloads. The course covers amortized analysis, recursion and master theorem, worst case versus expected case, the cost of allocation and b
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SQLite for Rust
Use SQLite from Rust to build production-grade data tooling — the embedded, single-file SQL engine that ships in every Android phone, every iOS device, and most web browsers. You'll start with the basics of SQLite as a serverless library, then drive it from Rust with the rusqlite crate: opening file-backed and in-memory databases, running INSERT, SELECT, UPDATE, DELETE through prepared statements, and surfacing errors as `Result` rather than swallowing them. Module 2 turns the database into a real ETL stage: stream CSV with the csv crate and serde, ingest JSON with serde_json into typed column
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AWS Intelligent Applications with Amazon Bedrock
Learn to build intelligent applications with Amazon Bedrock through hands-on console exploration, API development, and autonomous agent construction. You will navigate the Bedrock model catalog, compare foundation models like Claude and Haiku side by side, and implement the Dracula pattern for cloud-to-local model portability using Ollama as a fallback. The course progresses from console-based prototyping to programmatic API development, where you build Bedrock clients in both Bash with curl and Rust with the AWS SDK. You will create and query knowledge bases backed by S3 data sources and Tita
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