Rust Programming (Duke University Coursera Specialization)

2026-04-17 · 4min · Pragmatic AI Labs

Table of Contents

Five courses covering Rust end-to-end — fundamentals, data engineering in Rust, DevOps tooling, Python-to-Rust CLI migration, and Rust for LLMOps. Pure Rust, from first program through production LLM operations.

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What You Will Build

Idiomatic Rust programs with ownership and error handling, data engineering pipelines in Rust, DevOps automation replacing Python scripts, CLI tools with clap, and production Rust services for LLM operations.

Courses in This Specialization

Rust Fundamentals — Ownership, borrowing, lifetimes, traits, and the basics of idiomatic Rust.
Data Engineering with Rust — DataFusion, Polars, and high-throughput ETL in Rust.
Rust for DevOps — Replacing shell and Python scripts with type-safe Rust automation.
Python and Rust with Linux Command Line Tools — Bridging Python ergonomics and Rust performance in CLI tooling.
Rust for Large Language Model Operations (LLMOps) — Rust-native inference servers, quantization, and deployment patterns.

Who This Is For

Python and Go engineers moving to Rust for performance
DevOps engineers wanting safer, faster automation
LLM engineers building deterministic inference services

Next-Gen AI Development with Hugging Face — Rust-native fine-tuning with candle and burn
AI Tooling — Rust threads through agents, MCP, and security courses
Large Language Model Operations (LLMOps) — LLMOps complements Rust LLMOps

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