Your advantage
A Rust developer brings two rare things to AI: predictable performance and memory safety in the places where the most data is processed, inference, tokenization and vector indexing.
Rust has become a language of the performance layer in AI: vector databases such as Qdrant are written in it, Hugging Face maintains candle, a machine learning framework for Rust, and the Model Context Protocol has an official Rust SDK. None of the courses here is written in Rust: their examples are mostly Python. They are on this page because they give you the view from the application down, so you know what runs above the layer you optimise.
A Rust developer brings two rare things to AI: predictable performance and memory safety in the places where the most data is processed, inference, tokenization and vector indexing.
The risk is blind specialisation: optimising a kernel without knowing how the model is used, what RAG means or how quality is evaluated. The courses below are chosen to give you the top-down picture, from application to inference, and to tie your systems skills to the architecture decisions that matter.
Quantization, formats such as GGUF, hardware sizing and high-throughput serving. Whoever understands both the model and the machine designs inference services that others only configure.
Indexing, hybrid filtering and latency at scale: the problems Qdrant solves in Rust. To design them correctly you need to know what a RAG pipeline looks like from the application end.
Low-latency MCP servers that expose file systems, processes or sensor data to agents, with least-privilege permissions. The protocol has an official Rust SDK.
With the compiler and the tests as deterministic verifiers of generated code. Context, hooks and verification in CI decide whether the agent helps or gets in the way.
Each of these changes has at least one course in the track below. See the track
When you have gone through all the lessons of a course and have an average of at least 70% on its quizzes, you issue from your account, after confirming the conditions, a Certificate of Completion with a unique number and a public verification link. It is not issued automatically and it comes at no extra cost, with a plan or with single-course access.
A private attestation of course completion. It is NOT a diploma or a state-recognised qualification under Romanian Laws 198/2023, 199/2023 or Government Ordinance 129/2000; employers may take it into account at their own discretion.
In the order in which they matter. If you already have experience with model APIs, skip the foundations. For each course, the reason it matters to someone who works with Rust.
The whole picture of AI systems, so that you know what you are optimising and for whom. Language-independent, with the examples mostly in Python.
LLMs and modern architectures, APIs, RAG, agents and evaluation: the context you need before going down to the inference level.
Key modules: Machine Learning Essentials · Large Language Models and Modern Architectures · Working with LLM APIs and Integrations · AI Tools for Developers
Read the free preview Course details This course only: €99/monthStreaming, error handling, function calling, multi-model routing and productionization: the specification of a model client or gateway you would write in Rust. The examples are in Python.
Key modules: Streaming and Error Handling · Function Calling and Tool Use · Model Context Protocol (MCP) · Multi-Model Orchestration and Optimization
Read the free preview Course details This course only: €99/monthEmbeddings, chunking, hybrid search and evaluation, with a section on why Qdrant, written in Rust, performs the way it does: so that you design the indexing layer correctly, not just make it fast.
Key modules: Implementing the RAG Pipeline · Embedding Models and Document Processing · Advanced RAG · Advanced RAG Architectures
Read the free preview Course details This course only: €99/monthThe layer where Rust has the most to say: models on your own hardware, retrieval at scale, fast tools for agents.
LoRA and QLoRA, quantization for inference (GGUF, GPTQ, AWQ) and serving with Ollama, vLLM and TGI, the last of which has a Rust core: where adapted models have to run efficiently on your infrastructure.
Key modules: Data: The Foundation of Fine-Tuning · Parameter-Efficient Fine-Tuning (PEFT): LoRA · QLoRA and Quantized Training · The Fine-Tuning Toolchain
Read the free preview Course details This course only: €99/monthVector index internals (HNSW, IVF, quantization), hybrid search, sharding and embedding pipelines at scale: the data-structure end of retrieval, with Python and SQL in the examples.
Key modules: Storage and Table Formats: Parquet and Iceberg · Ingestion from Diverse Sources · ETL/ELT and Orchestration · Data Quality, Validation, and Contracts
Read the free preview Course details This course only: €99/monthProtocol architecture, transports, authentication, testing and containerization. The examples are in Python and TypeScript; the protocol is language-agnostic, and you carry the design to the Rust SDK.
Key modules: Building MCP Servers with Python · Building MCP Servers with TypeScript · Transport, Authentication and Configuration · Enterprise Patterns and Production Architectures
Read the free preview Course details This course only: €99/monthAttacks on AI systems, guardrails, supply chain and secrets: the requirements for tools and servers exposed to agents.
Key modules: Prompt Injection: The Defining Threat · Insecure Output Handling and Downstream Exploits · Guardrails: Input and Output Filtering · Securing RAG and Agents: Excessive Agency
Read the free preview Course details This course only: €99/monthAgentic coding from the terminal, headless mode, hooks and CI. The course notes that code-intelligence plugins for typed languages, Rust among them, report type errors to the agent after each edit.
Key modules: Multi-File and Large Codebases: Plan, Edit, Review and Context Management · The Full Git Workflow: Branches, Commits, Conflicts, Code Review and PRs · Headless Mode (claude -p) and Non-Interactive Automation · Subagents and Agent Teams: Orchestration, Delegation and Controlled Parallelization
Read the free preview Course details This course only: €99/monthThe course in the track that ends with a capstone project. The list comes from the real modules of the courses, not from a brochure.
What already exists, so that you do not start from zero. The courses in the track teach you what to build with it.
These are the skills you practise in the courses of the track; results depend on the time you invest and on your previous experience.
Start the Rust trackCode examples, architectures and case studies, and in some courses a capstone project at the end. Not summaries of documentation, but structured material that you go through in order, at your own pace.
You ask in the context of the lesson, by typing or by voice, and get an explanation of the concept you are on. Every lesson has its quiz: about 354 questions per course on average. The professor is an AI system, not a human teacher, included in every plan with a fair-use limit.
Agentic coding, MCP, RAG, agents, evals, LLM security, fine-tuning, AIOps, computer vision and Edge AI are whole courses in the catalog, not closing chapters.
A preview of the first lesson of every course can be read without an account. Then you choose a single course, €99 per month, or IT Pro, €399 per month, with the whole IT catalog. You can stop the renewal anytime from your account; access stays until the end of the period already paid for.
The courses on this page are IT courses. With the IT Pro plan you have the whole IT catalog, the technical learning paths and the AI Professor; if you want only one course, you buy it separately.
When you care about a single topic in the catalog
about €4 per hour of course
Developers, data engineers, architects. Code and production.
€16 per month for each of the 25 courses
The whole catalog, both tracks side by side.
€10 per month for each of the 50 courses
Subscriptions renew automatically; you can stop the renewal anytime from your account, and access stays until the end of the period already paid for. As digital content with immediate access, see the withdrawal conditions.
Compare all the plans · Plans for teams, by number of seats · Give a month of access as a gift
The same skills, seen from each ecosystem. The languages close to Rust are highlighted.
No. The examples are mostly in Python, and the MCP course also has a module in TypeScript. The courses are chosen for understanding AI systems from the top down, application, integration, inference, and for protocols such as MCP, which you then implement with the official Rust SDK. That is also why this track has two stages instead of three: it lists only the courses whose substance does not depend on the language.
On this track, the fine-tuning course, with quantization and serving, is the entry point. Outside it, in the same IT Pro plan, the Edge AI course covers model compression, on-device runtimes and microcontrollers, with examples in Python and some C.
To read it, yes: most examples in these courses are in Python. To adopt it as your main language, not necessarily.
All the courses recommended here are IT courses and open with the IT Pro plan, which includes every IT course in the catalog. It is billed monthly, and you can stop the renewal anytime from your account. There is also individual, monthly access to a single course. Every course has a free preview of its first lesson, readable without an account.
8 courses, ~200 hours, opened with IT Pro: €399 per month, VAT included, with access to all 25 IT courses. The AI Professor is included in every plan.
The courses are for educational purposes only: they are not professional advice, and completing them is not a diploma or a state-recognised qualification. The names of languages, tools and products belong to their owners and are mentioned for identification only. Details in the Terms & Conditions.
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