Kurssi · MonikielinenKeskitasoOppimispolun AI & Agent Engineering vaihe 1

Agent Engineering in Java: From LLM Foundations to Production Systems

Build agents. Understand the architecture. Engineer for production. Learn to design, build and own a production AI agent in Java, from one model call to a durable, observable, secured system you operate through real incidents.

TarjoajaTarkev
  • 16 moduulia
  • 136 oppituntia
  • 24 viikkoa
  • Monikielinen
  • Fumu jokaisella oppitunnillaKysy Fumulta millä tahansa oppitunnilla. Se selittää aineiston sen oppitunnin pohjalta, jolla olet.
  • Vahvistettu todistus profiiliisiPianLisätään julkiseen profiiliisi sinä päivänä, kun suoritat kurssin, ja liitetään vahvistettuun henkilöllisyyteesi.
Kurssin yleiskatsaus

Tietoa kurssista

Most agent courses teach you to make an agent work. This one teaches you to own one in production.

You will build one system through the whole course: the Order Support Assistant, which answers order questions, cancels and refunds within policy, retrieves return rules, and asks a person before it does anything it cannot undo. It is never thrown away. Every module adds a capability and a new way for it to break, and the capstone is the same system, hardened and run under traffic.

Every lesson asks you to make a decision, not just write code: whether a task needs an LLM, a tool, an agent, retrieval or several agents at all, and what the cheaper deterministic alternative would cost. You will list what can fail and how you would know, trace every model call and tool call from the first module, and keep the documents real teams keep: an architecture doc, an ADR log, a failure and threat register, a runbook, an evaluation set, a cost ledger and postmortems.

You build the mechanism before you use the tool that hides it. You call the provider's API directly before LangChain4j, write the agent loop, budgets and retries yourself before Spring Boot packages them, and build checkpoint and resume by hand before Temporal makes execution durable. That way you can judge when a framework helps and when it is overkill.

You are assessed the way engineering teams assess senior engineers: through decision memos, design reviews, incident drills with postmortems, and evaluation-driven changes. Code that runs is the entry ticket, not the grade.

The course has a core path and optional depth lessons, and four credentials along the way: Foundations after Module 2, Reliable Agent after Module 5, Production Agent after Module 12 and Agent Engineer after the capstone.

Opetussuunnitelma

16 moduulia · 136 oppituntia
1Orientation2 oppituntiaThe whole system in miniature before the foundations begin. In one sitting you run the starter repository, make one model call, give the model one tool, and read the trace of the run end to end. Nothing is explained in depth yet; the point is to see the destination, the Order Support Assistant you will build and own for the rest of the course, and the artifacts you will keep alongside it.
  1. 1.1 The Whole System in One HourVideo ja luettava · 48 min
  2. 1.2 Module 1 Model Answers: Lesson 1.01Luettava
2LLM Foundations12 oppituntiaWhat changes when part of a system is probabilistic. You learn how a model reads tokens and messages, how providers and APIs expose it, how prompts and structured outputs shape its behaviour, and where it fails. The module ends with the prototype of the Order Support Assistant: one traced model call that classifies a support request into a validated result, the first entry in the cost ledger, version 0 of the architecture doc, and a decision memo on whether an LLM or plain rules should do the classification.
  1. 2.1 From Traditional Software to LLM-Powered SystemsVideo ja luettava · 23 min
  2. 2.2 Tokens, Tokenization, and Context WindowsVideo ja luettava · 30 min
  3. 2.3 Messages and the LLM Conversation ModelVideo ja luettava · 25 min
  4. 2.4 How LLM Generation WorksVideo ja luettava · 20 min
  5. 2.5 Models, Providers, and LLM APIsVideo ja luettava · 28 min
  6. 2.6 Prompts, Instructions, and Model BehaviorVideo ja luettava · 32 min
  7. 2.7 Structured OutputsVideo ja luettava · 35 min
  8. 2.8 Embeddings and Semantic RepresentationVideo ja luettava · 20 min
  9. Tässä moduulissa on vielä 4 oppituntia
3Tool Calling and Structured Interaction13 oppituntiaThe model gets its first capabilities, and you decide which ones it must never have. You specify tool contracts before coding them, run the tool-calling lifecycle by hand, enforce validation, authorization and least privilege in application code, and handle errors, timeouts and retries with idempotent side effects. The failure-mode and threat register and the first evaluation cases start here. The module ends with Design Review 1 and the Foundations credential.
  1. 3.1 From Structured Output to Tool CallingVideo ja luettava · 25 min
  2. 3.2 Tool Definitions, Descriptions, and SchemasVideo ja luettava · 30 min
  3. 3.3 The Tool Calling LifecycleVideo ja luettava · 28 min
  4. 3.4 Returning Tool Results to the ModelVideo ja luettava · 28 min
  5. 3.5 Designing Good Tools for LLMsVideo ja luettava · 17 min
  6. 3.6 Validation and AuthorizationVideo ja luettava · 37 min
  7. 3.7 Least Privilege and the Tool PolicyVideo ja luettava · 33 min
  8. 3.8 Tool Errors, Timeouts, Retries, and IdempotencyVideo ja luettava · 34 min
  9. Tässä moduulissa on vielä 5 oppituntia
4Agent Fundamentals9 oppituntiaWhen a single call is not enough, and when an agent is too much. You learn what makes a system agentic, choose between an LLM call, a workflow and an agent, and build the observe–decide–act loop with stopping conditions and an execution budget written before the loop is coded. Every step is traced, so loop count and budget use are visible. The module ends with the Order Support Assistant's agent loop and an ADR on workflow versus agent for the return flow.
  1. 4.1 What Makes a System AgenticVideo ja luettava · 25 min
  2. 4.2 LLM Application, Workflow, or Agent: Choosing the ShapeVideo ja luettava · 25 min
  3. 4.3 The Observe–Decide–Act LoopVideo ja luettava · 16 min
  4. 4.4 Agent State, Goals, and ObservationsVideo ja luettava · 18 min
  5. 4.5 Stopping Conditions and Execution BudgetsVideo ja luettava · 27 min
  6. 4.6 Bounded Autonomy and When Not to Use an AgentVideo ja luettava · 24 min
  7. 4.7 Building the Order Support Agent LoopVideo ja luettava · 37 min
  8. 4.8 Module 4 Model Answers: Lessons 4.01–4.04Luettava
  9. Tässä moduulissa on vielä 1 oppituntia
Vielä 12 moduulia · 100 oppituntia
Tämän kurssin jälkeen

Seuraavaksi oppimispolulla AI & Agent Engineering

Tämä kurssi on vaiheessa 1/2: Foundation.

Agent Engineering in Java: From LLM Foundations to Production SystemsNäytä koko oppimispolku