Go is a language of infrastructure, and AI needs infrastructure: model gateways, inference servers, agents that run as services, operations assisted by AI. OpenAI and Anthropic publish official Go SDKs and the Model Context Protocol has an official Go SDK. None of the courses here is written in Go: their examples are mostly Python. They are on this page because they describe the layer above the one you run, and how AI enters operations.
A Go developer brings what AI projects often lack: small, fast, observable services that survive real traffic. Gateways that route between models, cost limits per client, response caching, low-latency MCP tools, agents that run as services: all of these are systems problems, not data science problems.
The risk is staying at the infrastructure level without understanding what runs on it. Someone who does not know how a model behaves, what RAG means or how answer quality is evaluated cannot design the layer underneath correctly. The courses below give you that mental model and tie it to operations, where you are already at home.
Routing between providers, retries, streaming, cost limits, caching and compliant logging: a typical Go service, with the twist that the answer is non-deterministic and cost is per token.
Internal services become tools for agents and assistants, with authentication and least-privilege permissions. The protocol is language-agnostic and has an official Go SDK.
Alert triage, root cause analysis, log and trace analysis, ChatOps and Kubernetes operations. Platform teams need to know both what these tools can do and where they must stop.
Quantization, hardware sizing and OpenAI-compatible endpoints. Whoever operates these services decides the cost and the confidentiality of the whole platform.
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 Go.
The mental model of LLMs and of AI applications, so that you design the layer underneath correctly. Language-independent, with the examples mostly in Python.
LLMs, APIs, RAG, agents, evaluation and security at concept level: the frame you need to understand what you are serving.
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/monthGateway, queue-based and sidecar patterns, streaming over SSE, circuit breakers, multi-provider fallback, rate limiting, caching and OpenTelemetry tracing: in effect the specification of a model gateway, which you then implement in Go. 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/monthProtocol fundamentals, stdio and HTTP transports, OAuth 2.1, testing, containerization with Docker and Kubernetes, and CI/CD. The example servers are in Python and TypeScript; the course itself points out that the protocol is language-agnostic and that an internal server can just as well be written in Go.
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/monthThe stage where AI enters the operation of the platform and where you answer for quality, cost and security.
Observability with OpenTelemetry, Prometheus and Grafana, anomaly detection, AI-assisted incident response and root cause analysis, AI in CI/CD and infrastructure as code, ChatOps and Kubernetes operations: the course written for platform teams.
Key modules: Intelligent Observability: OpenTelemetry, Prometheus, Grafana · Anomaly Detection and Intelligent Alerting · AI-Assisted Log and Trace Analysis · AI-Assisted Incident Response and On-Call
Read the free preview Course details This course only: €99/monthThe self-hosting half is yours: quantization for inference (GGUF, GPTQ, AWQ), serving with Ollama, vLLM and TGI behind OpenAI-compatible endpoints, and cost and hardware planning.
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/monthModel serving patterns, deployment strategies (canary, shadow, A/B testing), drift monitoring and GPU cost: the lifecycle your platform has to support.
Key modules: Experiment Tracking and Reproducibility · Data and Feature Management · Training Pipelines and Orchestration · Model Registry, Versioning, and CI/CD for ML
Read the free preview Course details This course only: €99/monthRegression tests in CI/CD, online A/B testing and quality-drift monitoring: answer quality treated like any other operational signal.
Key modules: Classic Metrics and Why They Fail on Open-Ended Text · LLM-as-a-Judge: Design, Bias and Calibration · Building Evaluation Datasets · The Evaluation Tooling Landscape
Read the free preview Course details This course only: €99/monthPrompt injection, excessive agency, supply chain, secrets and denial of service against models: the security requirements for gateways and for tools 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 integration. The course notes that code-intelligence plugins for typed languages, Go among them, let the agent catch type errors 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 Go 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 355 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 subscription by number of courses, from €99 a month for one course to €319 a month for 10 courses, VAT included; you pick the courses and can change them at every renewal. You can stop the renewal anytime from your account; access stays until the end of the period already paid for.
You pick them, with the AI Professor included, and can change them at every renewal. The whole track fits in a subscription of 10 courses (€319 a month, VAT included); with the full catalog (€499) you have every course.
Pay for the tier, then pick the courses in your account. You can change them at every renewal.
€99 a course
€99a month €990a year, 12 months of access
under €67 a course
€199a month €1,990a year, 12 months of access
under €52 a course
€259a month €2,590a year, 12 months of access
under €32 a course
€319a month €3,190a year, 12 months of access
under €24 a course
€359a month €3,590a year, 12 months of access
under €16 a course
€399a month €3,990a year, 12 months of access
under €10 a course, across all 50
€499a month €4,990a year, 12 months of access
Total prices, VAT included. Move up anytime and pay only the difference for the days left; move down at renewal. Renews automatically, you stop it anytime from your account; your progress and certificates stay. Digital content with immediate access: see the withdrawal terms.
A subscription by number of courses: 1, 3, 5, 10, 15 or 25 courses a month, or the full catalog. You pick them and can change them at every renewal. Compare all the subscriptions · The team library, priced per member · Give a month of access as a gift
The same skills, seen from each ecosystem. The languages close to Go are highlighted.
No. The examples are mostly in Python, and the MCP course also has a module in TypeScript. The courses are chosen for architecture, protocols and operating practices, which you then implement with the official Go SDKs for OpenAI, Anthropic and MCP. 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.
Yes. The AIOps course is written for operations teams, and the fine-tuning and MLOps courses cover the platform decisions: serving, cost, monitoring. The foundations give you the context, so that you do not operate blind.
The course on fine-tuning open-source LLMs: it covers open-model licenses, quantization for inference, serving with Ollama, vLLM and TGI, and cost and hardware planning. The MLOps course adds serving patterns, deployment strategies and monitoring.
All the courses recommended here are IT courses. You pick them in a subscription by number of courses: usually 3, 5 or 10 courses a month for one language and stack; there are also 15 and 25 courses, a single course and the full catalog. You pick the courses and can change them at every renewal. The subscription renews automatically, and you can stop the renewal anytime from your account. Every price, VAT included, is shown below and on the pricing page. Every course has a free preview of its first lesson, readable without an account.
9 courses, ~225 hours, all in a subscription of 10 courses: €319 per month, VAT included. You can change them at every renewal; the AI Professor is built into every lesson.
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.
ChatGPT, OpenAI, Claude, Anthropic, Gemini, Google, Microsoft 365 Copilot, Cursor, Midjourney and the other product and company names mentioned are trademarks or trade names of their respective owners. Cursuri-AI.ro is an independent training provider and is not affiliated with, sponsored by or endorsed by any of them.