AI 课程体系，一门一门看。

251 门课程中的 251 门 · 700.5 接触学时

• GroundModule2 学时

  Understanding Artificial Intelligence

  Learn how AI models actually work, from tokens to probability, and why the same question can produce two different answers.

  你的产出A one-page explanation of tokens and probability in your own words

  AI Foundations·不用工具

• GroundModule1.5 学时

  Choosing the Right AI Model

  Discover the differences between frontier and small models, open and closed weights, and learn to pick the right one for a task.

  你的产出A model-selection cheat sheet for your team

  AI Foundations·Claude, GPT, Gemini, Llama

• GroundModule2 学时

  Understanding AI Limitations

  Learn where AI models fail, covering invented facts, out of date knowledge, arithmetic errors and false confidence, by making each failure happen yourself.

  你的产出A personal failure log with five real examples

  AI Foundations·不用工具

• GroundModule1.5 学时

  AI Safety and Data Handling at Work

  Learn what data can and cannot go into a prompt, which tools are approved, and what to do when something goes wrong.

  你的产出A completed data-classification decision tree

  AI Foundations·不用工具

• GroundModule2 学时

  Getting Started with AI at Work

  Build a practical daily AI habit and learn to decide which tasks to delegate to a model and which to keep.

  你的产出A weekly AI habit plan with three named tasks

  AI Foundations·Claude, Copilot, Gemini

• GroundModule2 学时

  Verifying AI Output

  Learn practical techniques for checking AI answers, including source checking and cross-model verification.

  你的产出A reusable verification checklist for your function

  AI Foundations·不用工具

• GroundModule1.5 学时

  Understanding AI Costs

  Discover how tokens, context length and model choice drive the cost of AI, and learn to estimate the price of a workflow.

  你的产出A cost estimate for one of your own workflows

  AI Foundations·不用工具

• GroundCase1.5 学时

  Redesigning Your Role with AI

  Break your job into tasks and learn to decide which to automate, which to augment and which to keep human.

  你的产出A task inventory split into automate / augment / keep

  AI Foundations·不用工具

• GroundModule1 学时

  Communicating About AI Clearly

  Learn to describe what AI systems actually do, without the hype that makes projects hard to evaluate.

  你的产出A rewritten internal update stripped of hype

  AI Foundations·不用工具

• GroundModule2 学时

  Introduction to Prompt Engineering

  Learn the parts of an effective prompt, covering the task, context, constraints, examples and output format, and why vague instructions fail.

  你的产出A before/after prompt pair with measured difference

  Prompt Engineering·Claude, ChatGPT, Gemini

• OperatorModule2.5 学时

  Intermediate Prompt Engineering

  Master six reusable prompting patterns, including role framing, few-shot examples, decomposition and output contracts.

  你的产出Six reusable prompt patterns for your function

  Prompt Engineering·Claude, ChatGPT

• OperatorModule3 学时

  Context Engineering

  Learn what to put in a model's context window and in what order, and why a large window is not permission to paste everything.

  你的产出A restructured long-context prompt with measured lift

  Prompt Engineering·Claude

• OperatorModule2.5 学时

  Prompt Chaining and Decomposition

  Discover how to split a difficult request into a sequence of simple ones, and learn where chains break down.

  你的产出A three-stage chain that beats a single prompt

  Prompt Engineering·Claude, ChatGPT

• OperatorModule2 学时

  Controlling Model Reasoning

  Learn to use extended thinking and effort budgets, and to judge when deeper reasoning is worth the extra cost.

  你的产出A cost/quality curve across three thinking budgets

  Prompt Engineering·Claude, GPT

• OperatorModule2 学时

  Managing Prompts as a Team

  Learn to version, name, own and review prompts so they become shared assets rather than private tricks.

  你的产出A versioned prompt library with owners

  Prompt Engineering·不用工具

• OperatorModule2 学时

  Prompting with Images and Documents

  Learn to work with images, PDFs, screenshots and charts as model input for contracts, invoices and reports.

  你的产出A document-to-structure workflow you use weekly

  Prompt Engineering·Claude, Gemini

• BuilderModule2.5 学时

  Writing System Prompts for Products

  Learn to write the instruction layer behind a production feature, covering tone, refusals, escape hatches and drift.

  你的产出A production system prompt with a change log

  Prompt Engineering·Claude, OpenAI

• GroundModule1.5 学时

  Introduction to Prompt Injection

  Understand why pasting untrusted content into a model is a security risk, and learn to recognise it without writing code.

  你的产出A red-flag list for your team's tools

  Prompt Engineering·不用工具

• BuilderDrill2 学时

  Structuring Model Output

  Learn to force reliable output shapes using schemas, enums and citations so downstream code can trust what it receives.

  你的产出A schema-locked prompt with a 100-case pass rate

  Prompt Engineering·Claude, OpenAI

• BuilderModule3 学时

  Working with the Messages API

  Learn to call a language model API directly, handling roles, system instructions, stop reasons, errors and retries.

  你的产出A working client with retry and timeout handling

  Building AI Applications·Claude, OpenAI

• BuilderModule3 学时

  Structured Outputs and Schemas

  Learn to extract reliably typed data from a model, covering schema design, validation and repair loops.

  你的产出An extraction service with schema validation

  Building AI Applications·Claude, OpenAI

• BuilderModule3.5 学时

  Introduction to Tool Use

  Learn to give a model access to your own functions and APIs, handling definitions, arguments, results and errors.

  你的产出A model that queries your own API correctly

  Building AI Applications·Claude, OpenAI

• BuilderModule2.5 学时

  Streaming and Responsive AI Interfaces

  Learn to stream model output token by token, with partial rendering, cancellation and good waiting states.

  你的产出A streaming endpoint with graceful cancellation

  Building AI Applications·Claude, OpenAI

• BuilderModule3 学时

  Building Multimodal Pipelines

  Learn to process images, PDFs and audio at scale, including pre-processing, page splitting and cost control.

  你的产出A document pipeline handling 200 mixed files

  Building AI Applications·Claude, Gemini

• BuilderModule2.5 学时

  Prompt Caching and Batch Processing

  Learn to cut AI costs using prompt caching, batch endpoints and request shaping, with measured results.

  你的产出A workload with a measured cost reduction

  Building AI Applications·Claude, OpenAI

• ArchitectModule3 学时

  Model Routing and Fallbacks

  Learn to route requests between cheap and expensive models and handle provider outages with circuit breakers.

  你的产出A router with a documented escalation policy

  Building AI Applications·Claude, OpenAI, OSS

• BuilderLab4 学时

  Building a Chat Application

  Build a production chat feature covering conversation state, truncation, memory, rate limits and abuse handling.

  你的产出A deployed chat feature with history and limits

  Building AI Applications·Claude, OpenAI

• BuilderLab3.5 学时

  Building Document Processing Systems

  Build a pipeline that turns contracts and forms into structured records through ingest, extract, validate and review.

  你的产出A pipeline turning contracts into structured records

  Building AI Applications·Claude

• BuilderModule3 学时

  Classification and Extraction at Scale

  Learn when a language model beats a trained classifier, and how to set thresholds, abstention and review queues.

  你的产出A classifier with a published confusion matrix

  Building AI Applications·Claude, OSS

• BuilderModule2.5 学时

  Generating Synthetic Data

  Learn to generate test cases, edge cases and training data, and to measure diversity and avoid model collapse.

  你的产出A synthetic test set with diversity metrics

  Building AI Applications·Claude, OSS

• BuilderCase2 学时

  Choosing Between Prompting, RAG and Fine-Tuning

  Learn to make the build decision for an AI feature using cost, latency and accuracy evidence rather than preference.

  你的产出A written decision memo for one real feature

  Building AI Applications·不用工具

• BuilderModule3 学时

  Introduction to Embeddings

  Learn how embeddings represent meaning as vectors, and build a working semantic search over your own documents.

  你的产出A working semantic search over your own docs

  Retrieval & RAG·OpenAI, Cohere, OSS

• BuilderModule3 学时

  Preparing Documents for Retrieval

  Learn structure aware chunking, overlap, metadata and table handling, the step that quietly decides retrieval quality.

  你的产出A chunking strategy with a retrieval score

  Retrieval & RAG·LangChain, LlamaIndex

• BuilderModule3 学时

  Working with Vector Databases

  Learn to index, filter and update vectors in production, covering multi-tenancy, namespaces and operational cost.

  你的产出A store with filters, namespaces and backups

  Retrieval & RAG·Pinecone, Weaviate, pgvector

• BuilderLab3.5 学时

  Building RAG Applications

  Build a retrieval-augmented assistant end to end, with query rewriting, grounding, citation and refusal.

  你的产出A grounded assistant with citations

  Retrieval & RAG·LangChain, Claude

• BuilderModule3 学时

  Hybrid Search and Reranking

  Learn to combine keyword and vector search with a reranker, usually the biggest available quality gain.

  你的产出A measured precision gain over pure vector search

  Retrieval & RAG·BM25, rerankers

• ArchitectModule3 学时

  Introduction to Graph RAG

  Learn to use graph databases for retrieval when relationships matter more than similarity, including multi-hop questions.

  你的产出A graph-backed answer to a multi-hop question

  Retrieval & RAG·Neo4j, LangChain

• BuilderModule3 学时

  Evaluating Retrieval Quality

  Learn to measure recall, precision and faithfulness, and to score retrieval separately from generation.

  你的产出A retrieval scorecard on your own corpus

  Retrieval & RAG·RAGAS, custom

• BuilderModule3 学时

  Building Text-to-SQL Systems

  Learn to query a warehouse in natural language, with schema context, guardrails, validation and review gates.

  你的产出A guarded query interface with a review gate

  Retrieval & RAG·Claude, dbt

• ArchitectModule2.5 学时

  Keeping Knowledge Bases Current

  Learn to detect change, re-embed efficiently and set staleness targets so answers do not silently go out of date.

  你的产出An index refresh design with staleness SLOs

  Retrieval & RAG·不用工具

• ArchitectLab3.5 学时

  Search Over Messy Enterprise Data

  Build a working index over real corporate content: duplicates, contradictions, dead policies and scanned PDFs.

  你的产出A working index over genuinely bad source data

  Retrieval & RAG·Claude, hybrid stack

• OperatorModule2 学时

  Introduction to AI Agents

  Learn what an agent actually is, namely a loop with tools and a stopping condition, and how to judge which work is worth automating.

  你的产出A written spec for one candidate agent

  AI Agents·不用工具

• BuilderModule3 学时

  Building Your First AI Agent

  Build an agent loop by hand before using a framework, covering tools, termination, iteration caps and error recovery.

  你的产出A working agent with three real tools

  AI Agents·Claude, OpenAI

• BuilderModule3 学时

  Agent Memory and State

  Learn to give an agent durable state so it survives a restart, and understand memory versus a longer prompt.

  你的产出An agent that survives a restart mid-task

  AI Agents·Claude, LangGraph

• BuilderModule3 学时

  Agent Planning Patterns

  Learn plan-and-act, reflection and decomposition patterns, and which genuinely improve results rather than burning tokens.

  你的产出A planner/executor split with a measured gain

  AI Agents·LangGraph, Claude

• ArchitectModule3.5 学时

  Building Multi-Agent Systems

  Learn supervisor, parallel and hand off patterns for multiple agents, and recognise when a single agent is the better design.

  你的产出A parallel fan-out with a synthesis stage

  AI Agents·LangGraph, CrewAI, Claude

• BuilderModule3 学时

  Introduction to Model Context Protocol (MCP)

  Learn the MCP standard for connecting models to tools and data, including primitives, transport and configuration.

  你的产出A client connected to three MCP servers

  AI Agents·MCP, Claude

• BuilderLab3.5 学时

  Building MCP Servers

  Build your own MCP server to expose an internal system as tools, covering schema design, auth and versioning.

  你的产出A published MCP server over an internal system

  AI Agents·MCP

• ArchitectModule3 学时

  Agent Permissions and Sandboxing

  Learn to scope what an agent can touch using least privilege, allow-lists, execution isolation and action gates.

  你的产出A permission matrix and an enforced sandbox

  AI Agents·Claude, containers

• BuilderModule2.5 学时

  Designing Human-in-the-Loop Approval

  Learn to design approval checkpoints people actually read, and avoid the rubber stamp that defeats the control.

  你的产出An approval flow with a measured intervention rate

  AI Agents·不用工具

• ArchitectModule3 学时

  Agent Observability and Tracing

  Learn to trace an agent run with spans, tool calls and token accounting so failures can be reconstructed.

  你的产出A traced agent run you can debug from logs

  AI Agents·LangSmith, OTel

• ArchitectModule3 学时

  Long-Running and Scheduled Agents

  Learn to run agents on a schedule or for hours, covering idempotency, resumption, drift and unattended failure.

  你的产出A scheduled agent with alerting and a kill switch

  AI Agents·Claude, queues

• OperatorLab3 学时

  Workflow Automation Without Code

  Build real business automations in a visual builder, covering triggers, branching, error paths and handover.

  你的产出A live automation replacing a manual routine

  AI Agents·n8n, Power Automate

• ArchitectModule3 学时

  Browser and Computer-Use Agents

  Learn to drive interfaces that have no API, with a candid look at reliability, cost and the security surface.

  你的产出A guarded browser task with a scoped profile

  AI Agents·Claude, Playwright

• ArchitectModule2.5 学时

  Controlling Agent Cost and Risk

  Learn to apply loop detection, spend caps, dry runs and reversibility so a bad agent run does not become an incident.

  你的产出A budget guard and a rollback plan

  AI Agents·不用工具

• OperatorModule2.5 学时

  Getting Started with AI Coding Assistants

  Learn to use AI coding assistants effectively and establish an honest baseline of your current speed.

  你的产出A measured baseline on your own repository

  AI for Software Engineering·Copilot, Claude Code, Cursor

• BuilderModule3 学时

  Spec-Driven Development with AI

  Learn to write the specification a model needs in order to produce correct code first time.

  你的产出A spec that produced working code first time

  AI for Software Engineering·Claude Code

• BuilderModule2.5 学时

  Reviewing AI-Generated Code

  Learn to review code you did not write, spotting hallucinated APIs, silent assumptions and plausible nonsense.

  你的产出A review checklist adopted by your team

  AI for Software Engineering·不用工具

• BuilderModule2.5 学时

  Generating Tests with AI

  Learn to generate tests that actually fail when the code is wrong, verified with mutation testing.

  你的产出A suite with mutation-tested quality

  AI for Software Engineering·Claude Code, Copilot

• BuilderLab3 学时

  Understanding Unfamiliar Codebases with AI

  Learn to map a large unfamiliar repository quickly, covering call graphs, dead code and hidden coupling.

  你的产出A written architecture map of an unfamiliar repo

  AI for Software Engineering·Claude Code

• ArchitectLab3.5 学时

  Large-Scale Refactoring with AI Agents

  Learn to run codebase-scale migrations with agents, covering batching, verification gates and rollback.

  你的产出A migration executed across 50+ files

  AI for Software Engineering·Claude Code

• BuilderModule3 学时

  Debugging with AI Agents

  Learn a disciplined debugging loop of reproduce, bisect, hypothesise and verify that keeps the model honest.

  你的产出A reproducible bug hunt logged end to end

  AI for Software Engineering·Claude Code

• OperatorModule2 学时

  Documenting Code with AI

  Learn to generate architecture decision records, runbooks and API documentation that stay accurate.

  你的产出Generated docs that survived a review

  AI for Software Engineering·Claude Code

• ArchitectModule3 学时

  AI in CI/CD Pipelines

  Learn to automate review, triage and release notes in your pipeline, and recognise where a bot becomes noise.

  你的产出An automated review step running on PRs

  AI for Software Engineering·GitHub Actions, Claude

• BuilderCase1.5 学时

  Knowing When Not to Use AI on Code

  Learn to define the boundary for cryptography, concurrency and regulated code paths before an incident defines it for you.

  你的产出A written no-go list for your codebase

  AI for Software Engineering·不用工具

• ArchitectCase2 学时

  Measuring Engineering Productivity

  Learn to measure AI's real effect using cycle time and change failure rate rather than lines accepted.

  你的产出A metric set your engineers do not game

  AI for Software Engineering·DORA

• BuilderModule3 学时

  AI for Data Engineering

  Learn to build pipelines and transformations with AI assistance, protected by data contract tests.

  你的产出A generated pipeline with contract tests

  AI for Software Engineering·dbt, SQL, Claude

• OperatorModule2 学时

  Introduction to AI Evaluation

  Learn why a demo is not evidence, and how to define what good means for an AI feature before you build it.

  你的产出A written quality definition for one feature

  Evaluation & Testing·不用工具

• BuilderLab3 学时

  Building Your First Eval Set

  Build a 100-case evaluation set from real examples and score your current system against it.

  你的产出A 100-case eval set with a baseline score

  Evaluation & Testing·不用工具

• BuilderModule3 学时

  Using LLMs as Judges

  Learn to automate grading with a model judge, covering rubrics, position bias and calibration against humans.

  你的产出A judge validated against human labels

  Evaluation & Testing·Claude, OpenAI

• BuilderModule2.5 学时

  Running Human Evaluation

  Learn to run annotators well, covering guidelines, inter-rater agreement, adjudication and cost per label.

  你的产出An annotation guideline with measured agreement

  Evaluation & Testing·不用工具

• BuilderModule2.5 学时

  Regression Testing for Prompts

  Learn to treat prompts as code, with version control and CI gates that block quality regressions.

  你的产出An eval gate blocking a bad prompt merge

  Evaluation & Testing·CI, promptfoo

• ArchitectModule3 学时

  Monitoring AI in Production

  Learn to measure quality live using sampling, implicit signals, drift detection and alert thresholds.

  你的产出A production quality dashboard with alerts

  Evaluation & Testing·LangSmith, OTel

• BuilderModule3 学时

  Detecting Hallucination and Measuring Grounding

  Learn to score answers for unsupported claims automatically, and to treat abstention as a feature.

  你的产出A faithfulness score wired into your pipeline

  Evaluation & Testing·不用工具

• ArchitectModule3 学时

  A/B Testing AI Features

  Learn to design experiments on systems whose output varies per call, covering variance and sample size.

  你的产出A powered experiment design for one feature

  Evaluation & Testing·不用工具

• ArchitectModule3 学时

  Evaluating AI Agents

  Learn to score an agent's trajectory rather than its answer, covering tool choice, step efficiency and partial credit.

  你的产出A trajectory rubric applied to 50 runs

  Evaluation & Testing·LangSmith

• ArchitectCase2 学时

  Running an AI Quality Review

  Learn to run a recurring forum that holds AI features to their measured numbers.

  你的产出A standing review agenda and its first minutes

  Evaluation & Testing·不用工具

• ArchitectModule3 学时

  Introduction to LLMOps

  Learn the operational lifecycle of an AI system, from prompt and model to data, evaluation, release and monitoring, and how it differs from MLOps.

  你的产出A reference architecture for your stack

  Deployment & Operations·不用工具

• ArchitectModule3 学时

  Building an AI Gateway

  Learn to put every model call behind one front door with keys, quotas, logging, routing and provider abstraction.

  你的产出A gateway with keys, quotas and logging

  Deployment & Operations·LiteLLM, gateways

• ArchitectModule3 学时

  Reducing AI Latency

  Learn where the milliseconds go and how to cut them through model choice, output length, streaming and caching.

  你的产出A P95 reduction with a documented method

  Deployment & Operations·不用工具

• ArchitectModule3 学时

  AI Cost Management

  Learn to model cost per request, per user and per outcome, and to forecast and control AI spend.

  你的产出A per-request unit economic model

  Deployment & Operations·不用工具

• ArchitectModule2.5 学时

  Managing Rate Limits and Capacity

  Learn to handle provider limits with queuing, backpressure and graceful degradation under load.

  你的产出A load plan surviving a 10x spike

  Deployment & Operations·不用工具

• ArchitectLab3.5 学时

  Self-Hosting Open Models

  Learn to serve open-weight models yourself, covering GPUs, quantisation and the true total cost.

  你的产出A served open model with a cost comparison

  Deployment & Operations·vLLM, Llama, Mistral

• ArchitectModule3 学时

  Deploying AI on Cloud Platforms

  Learn to deploy models on Bedrock, Vertex or Azure AI Foundry, covering residency, networking and procurement.

  你的产出A deployment meeting your residency rules

  Deployment & Operations·Bedrock, Vertex, Foundry

• ArchitectModule2.5 学时

  Migrating Between Models

  Learn to move to a new model version without a quality regression, using shadow traffic and staged rollout.

  你的产出A migration runbook with an eval gate

  Deployment & Operations·不用工具

• ArchitectModule2.5 学时

  Incident Response for AI Systems

  Learn to detect, contain and disclose when a model is confidently wrong at scale, then run the post-mortem.

  你的产出A runbook plus one tabletop exercise

  Deployment & Operations·不用工具

• ArchitectModule3 学时

  Privacy-Preserving AI Architecture

  Learn to design for redaction, tokenisation, residency, retention and zero-retention endpoints.

  你的产出A data-flow diagram cleared by your DPO

  Deployment & Operations·不用工具

• BuilderModule2.5 学时

  Introduction to AI Security

  Learn to threat model an AI feature, covering assets, actors and entry points, mapped to the OWASP LLM risks.

  你的产出A threat model for one live feature

  AI Security·不用工具

• BuilderLab3 学时

  Attacking Systems with Prompt Injection

  Learn direct and indirect prompt injection by breaking a system you built, then attempting to defend it.

  你的产出Three successful injections against your own app

  AI Security·不用工具

• BuilderModule3 学时

  Preventing Data Exfiltration

  Learn to recognise and break the combination of private data, untrusted content and an outbound channel.

  你的产出An audit of your tools against the trifecta

  AI Security·不用工具

• ArchitectModule3 学时

  Securing AI Agent Permissions

  Learn to scope agent capability so that a compromised agent cannot cause real damage.

  你的产出A least-privilege design for one agent

  AI Security·不用工具

• ArchitectLab3.5 学时

  Red-Teaming AI Applications

  Learn to run a structured campaign covering jailbreaks, extraction, poisoning and denial of wallet, then write it up.

  你的产出A red-team report with severity ratings

  AI Security·不用工具

• ArchitectModule3 学时

  Securing the AI Supply Chain

  Learn to vet third-party models, MCP servers, skills and packages for provenance before adoption.

  你的产出A vetting standard for third-party components

  AI Security·MCP, models, skills

• BuilderModule2.5 学时

  Handling Untrusted Model Output

  Learn to treat model output as untrusted input, preventing XSS, SQL injection and unsafe rendering.

  你的产出A hardened rendering and execution path

  AI Security·不用工具

• BuilderModule2.5 学时

  Redacting Secrets and PII

  Learn to keep sensitive data out of prompts, logs and traces, and to measure how well redaction works.

  你的产出A redaction layer with measured recall

  AI Security·不用工具

• ArchitectCase3 学时

  Building an AI Security Review Process

  Learn to design a review gate every AI feature passes, sized so that it does not become theatre.

  你的产出A review gate adopted into your SDLC

  AI Security·不用工具

• OperatorModule2 学时

  Writing an AI Acceptable Use Policy

  Learn to write an AI policy short enough to be read and specific enough to be applied.

  你的产出A one-page AI policy fit for your company

  Governance & Compliance·不用工具

• BuilderModule3 学时

  Understanding the EU AI Act

  Learn the risk tiers, obligations, timelines and roles under the EU AI Act from a deployer's perspective.

  你的产出A risk classification of your AI inventory

  Governance & Compliance·不用工具

• BuilderModule3 学时

  Introduction to ISO/IEC 42001

  Learn to build an AI management system that survives an audit without stalling delivery.

  你的产出A gap analysis against the standard

  Governance & Compliance·不用工具

• OperatorModule2.5 学时

  Building an AI Use Case Inventory

  Learn to discover, register and maintain a live inventory of every AI system in your organisation.

  你的产出A populated register with owners and tiers

  Governance & Compliance·不用工具

• BuilderModule3 学时

  Conducting AI Impact Assessments

  Learn to assess a use case before build, covering affected people, severity, reversibility and mitigation.

  你的产出A completed assessment on a real use case

  Governance & Compliance·不用工具

• BuilderModule2.5 学时

  AI Vendor Due Diligence

  Learn to assess an AI vendor on training data, retention, sub-processors, evaluations and incident history.

  你的产出A vendor questionnaire and a scoring rubric

  Governance & Compliance·不用工具

• OperatorModule2 学时

  AI, Copyright and Intellectual Property

  Learn who owns model output, what your inputs expose, and where the real legal risk sits today.

  你的产出A guidance note for your content teams

  Governance & Compliance·不用工具

• BuilderLab3 学时

  Testing AI Systems for Bias

  Learn to move from fairness principles to actual tests, covering subgroup measurement, proxies and remediation.

  你的产出A bias test report on a real system

  Governance & Compliance·不用工具

• OperatorModule2 学时

  AI Transparency and Disclosure

  Learn to tell users that AI was involved, in language that informs rather than disclaims.

  你的产出Disclosure copy shipped in a real product

  Governance & Compliance·不用工具

• BuilderModule2.5 学时

  Audit Trails for AI Systems

  Learn to log what a regulator or auditor will ask for, before they ask for it.

  你的产出An evidence pack for one AI system

  Governance & Compliance·不用工具

• BuilderCase3 学时

  Sector-Specific AI Regulation

  Learn where financial services, healthcare, public sector and employment rules bite harder than AI law.

  你的产出A sector obligation map for your business

  Governance & Compliance·不用工具

• ArchitectCase2.5 学时

  Designing an AI Governance Operating Model

  Learn to set decision rights and accountability so that governance does not become a bottleneck.

  你的产出An RACI and a decision-rights map

  Governance & Compliance·不用工具

• OperatorModule2.5 学时

  Choosing the Right AI Product Opportunity

  Learn to screen AI feature ideas on error tolerance, value of speed and availability of ground truth.

  你的产出A scored shortlist of five candidate features

  AI Product & Design·不用工具

• BuilderLab3 学时

  Writing PRDs for AI Features

  Learn to write requirements for a feature whose output varies, with acceptance criteria expressed as evaluations.

  你的产出A PRD with acceptance criteria as an eval set

  AI Product & Design·不用工具

• BuilderModule3 学时

  Designing for Uncertainty

  Learn to design confidence, ambiguity and the honest 'I do not know' as intentional interface states rather than failures.

  你的产出Three interface states designed and tested

  AI Product & Design·不用工具

• BuilderModule2.5 学时

  Designing Trust and Disclosure

  Learn to use citations, provenance, edit affordances and consent to earn trust without overclaiming.

  你的产出A trust pattern set for your product

  AI Product & Design·不用工具

• BuilderModule3 学时

  Agent User Experience Patterns

  Learn patterns for showing work, interruption, approval and undo on tasks with no progress bar.

  你的产出An agent flow prototype with approval points

  AI Product & Design·不用工具

• BuilderModule2.5 学时

  Designing AI Error Recovery

  Learn what the interface should do when a model is wrong, slow, refuses, or is unavailable.

  你的产出A recovery flow for three failure modes

  AI Product & Design·不用工具

• BuilderCase2.5 学时

  Pricing and Packaging AI Features

  Learn to price a feature with variable marginal cost, covering seats, credits, outcomes and the margin trap.

  你的产出A pricing model with a margin floor

  AI Product & Design·不用工具

• BuilderModule3 学时

  Instrumenting AI Features

  Learn to measure the funnel that matters, from invoked through completed, accepted, edited and reverted, instead of raw usage.

  你的产出An event schema and a live funnel

  AI Product & Design·不用工具

• BuilderModule2.5 学时

  Rolling Out AI Features Safely

  Learn to plan staged release, guardrails and the kill criteria you agree before launch.

  你的产出A rollout plan with pre-agreed kill criteria

  AI Product & Design·不用工具

• OperatorLab3 学时

  Prototyping AI Products

  Learn to build a throwaway AI prototype quickly, test it with users, and avoid accidentally shipping it.

  你的产出A tested prototype plus a written learning

  AI Product & Design·Claude, Replit, v0

• OperatorModule3 学时

  AI for Sales

  Learn to use AI for account research, call preparation, follow-up and proposals, with clear honesty rules.

  你的产出A live pre-call research workflow

  AI for Business Functions·Claude, Copilot, CRM

• OperatorModule3 学时

  AI for Marketing

  Learn to run a content pipeline from brief to review at volume, with brand voice and fact-checking built in.

  你的产出A content pipeline with a brand-voice check

  AI for Business Functions·Claude, Gemini

• OperatorModule3 学时

  AI for Customer Support

  Learn to use AI for draft assistance, deflection and quality assurance, and when to hand over to a human.

  你的产出A deflection design with an escalation policy

  AI for Business Functions·Claude, Zendesk

• OperatorModule3 学时

  AI for Finance

  Learn to use AI for variance analysis, commentary and reconciliation, with controls an auditor will accept.

  你的产出A reconciliation workflow with a control step

  AI for Business Functions·Claude, Excel, Copilot

• OperatorModule3 学时

  AI for Legal and Contracting

  Learn to use AI for contract review, clause extraction and first drafts, with privilege and confidentiality protected.

  你的产出A clause-review workflow with a risk register

  AI for Business Functions·Claude

• OperatorModule3 学时

  AI for Human Resources

  Learn to use AI across job design, screening, interviews and onboarding, with fairness testing built in.

  你的产出A hiring workflow that passes a bias review

  AI for Business Functions·Claude, Copilot

• OperatorModule2.5 学时

  AI for Learning and Development

  Learn to build training content, assessments and personalised paths with AI, without generating filler.

  你的产出A generated course outline with assessments

  AI for Business Functions·Claude

• OperatorModule2.5 学时

  AI for Procurement

  Learn to use AI for supplier analysis, tender review and spend analysis on real documents.

  你的产出A supplier comparison built from real documents

  AI for Business Functions·Claude, Excel

• OperatorLab3 学时

  AI for Operations

  Learn to map a process, find the AI-shaped step, rebuild it and measure what changed.

  你的产出One process re-designed and instrumented

  AI for Business Functions·n8n, Claude

• OperatorModule2.5 学时

  AI for Executive Support

  Learn to run briefings, meeting synthesis, decision logs and follow-through at executive tempo.

  你的产出A weekly executive briefing pipeline

  AI for Business Functions·Claude

• OperatorModule2.5 学时

  AI for Research and Competitive Intelligence

  Learn to run structured research with citation discipline, gaining depth without fabrication.

  你的产出A sourced competitive brief

  AI for Business Functions·Claude, Gemini

• OperatorModule2.5 学时

  AI for Project Management

  Learn to use AI for status synthesis, risk detection and reporting that reflects reality.

  你的产出A status pipeline drawn from real artefacts

  AI for Business Functions·Claude

• BuilderLab3.5 学时

  AI for Data Analysis

  Learn to take an analysis from question to query to chart to narrative, with verification at every stage.

  你的产出An analysis delivered end to end with AI

  AI for Business Functions·Claude, SQL, Python

• OperatorModule3 学时

  Creating Documents and Presentations with AI

  Learn to produce finished reports, decks and spreadsheets rather than raw text.

  你的产出Three real deliverables produced and reviewed

  AI for Business Functions·Claude, Copilot, Gemini

• GroundModule2 学时

  AI for Frontline Teams

  Learn mobile-first, low-friction AI uses for field, retail, logistics and support staff.

  你的产出A shift-level use case adopted by a team

  AI for Business Functions·Claude, Copilot

• OperatorModule2 学时

  AI for Executives

  Learn what has genuinely changed in AI, what has not, and which vendor claims to discount.

  你的产出A briefing you could give your own board

  Leadership & Strategy·不用工具

• BuilderCase3 学时

  Building an AI Strategy

  Learn to build a portfolio of AI bets across horizons, managing concentration risk and killing projects on time.

  你的产出A scored portfolio across three horizons

  Leadership & Strategy·不用工具

• BuilderCase2.5 学时

  Buy, Build or Wait

  Learn to make the three-way AI investment decision using switching cost, differentiation and time to value.

  你的产出A decision memo for one live proposal

  Leadership & Strategy·不用工具

• BuilderModule2.5 学时

  Organising Teams for AI

  Learn to choose between central, embedded and federated AI teams, and decide who owns the platform.

  你的产出A target operating model for your org

  Leadership & Strategy·不用工具

• BuilderLab3 学时

  Building the Business Case for AI

  Learn to build an AI business case that survives finance, with baselines, attribution and sensitivity analysis.

  你的产出A defensible business case with sensitivities

  Leadership & Strategy·不用工具

• OperatorModule2.5 学时

  Leading Teams Through AI Change

  Learn to handle fear, resistance and quiet non-adoption, and what not to promise.

  你的产出A communication plan and a listening loop

  Leadership & Strategy·不用工具

• BuilderModule2 学时

  Running an AI Operating Cadence

  Learn to set the review rhythms, decision forums and the few metrics leadership should actually track.

  你的产出A cadence with named owners and metrics

  Leadership & Strategy·不用工具

• BuilderCase2.5 学时

  AI Skills and Talent Strategy

  Learn to map the capability you need, decide what to build versus hire, and retain people afterwards.

  你的产出A capability map with a build/hire split

  Leadership & Strategy·不用工具

• BuilderModule2 学时

  Reporting AI Progress to the Board

  Learn to report AI progress with evidence rather than ambition, and survive the follow-up question.

  你的产出A board-ready section with real evidence

  Leadership & Strategy·不用工具

• BuilderModule3 学时

  Machine Learning Fundamentals

  Learn supervised learning, validation, leakage and metrics, the foundation that generative AI still rests on.

  你的产出A trained model with a validated metric

  Machine Learning·Python, scikit-learn

• BuilderModule4 学时

  Introduction to Deep Learning

  Learn networks, gradients, optimisation and regularisation by building and training them yourself.

  你的产出A network trained from scratch

  Machine Learning·PyTorch

• ArchitectLab4 学时

  Building a Transformer from Scratch

  Learn attention, embeddings and positional encoding by writing a working small transformer.

  你的产出A working small transformer you wrote

  Machine Learning·PyTorch

• ArchitectLab4 学时

  Fine-Tuning Language Models

  Learn supervised fine-tuning end to end, covering dataset construction, training and honest evaluation.

  你的产出A fine-tuned model beating its base on your task

  Machine Learning·PyTorch, HF

• ArchitectModule4 学时

  Preference Tuning with RLHF and DPO

  Learn how preference data and reward modelling shape model behaviour, and what alignment training really does.

  你的产出A preference-tuned model with a win rate

  Machine Learning·HF, TRL

• ArchitectModule3.5 学时

  Parameter-Efficient Fine-Tuning with LoRA

  Learn to adapt large models on modest hardware using LoRA and QLoRA, and to judge when it is enough.

  你的产出An adapter trained on a single GPU

  Machine Learning·LoRA, QLoRA

• ArchitectModule3 学时

  Model Distillation and Small Models

  Learn to teach a small model to do one job well at a fraction of the inference cost.

  你的产出A small model within 5% of a large one

  Machine Learning·HF

• ArchitectModule3 学时

  Quantization and Inference Optimization

  Learn how precision, batching and KV cache affect throughput, and where quality starts to degrade.

  你的产出A served model with a latency/quality curve

  Machine Learning·vLLM, GGUF

• ArchitectModule3 学时

  Explainable AI

  Learn attribution and probing techniques, and the honest limits of explaining a large model's behaviour.

  你的产出An explanation a regulator would accept

  Machine Learning·SHAP, probes

• BuilderCase3 学时

  Classical Methods That Still Win

  Learn where forecasting, ranking, optimisation and rules beat a language model, and benchmark it yourself.

  你的产出A benchmark where the simple model wins

  Machine Learning·Python

• GroundModule2 学时

  Introduction to Claude

  Learn to set up Claude as a working environment using projects, artifacts, memory and connectors.

  你的产出A configured workspace with three live projects

  AI Foundations·Claude

• OperatorModule2.5 学时

  Context Engineering with Claude

  Learn to work with Claude's large context window deliberately, covering document structure, ordering and caching.

  你的产出A long-context workflow with a measured lift

  Prompt Engineering·Claude

• OperatorModule3 学时

  Introduction to Claude Code

  Learn to install and configure Claude Code on your own repository, covering permissions, memory files and first tasks.

  你的产出Claude Code configured on your own repository

  AI for Software Engineering·Claude Code

• BuilderLab3.5 学时

  Claude Code in Practice

  Learn to use Claude Code for feature work, tests and refactors in an existing codebase under a real review gate.

  你的产出A merged pull request produced with Claude Code

  AI for Software Engineering·Claude Code

• BuilderLab3 学时

  Building Agent Skills with Claude

  Learn to author, package and distribute Claude Agent Skills, including executable scripts and versioning.

  你的产出A packaged skill your team can install

  AI Agents·Claude

• ArchitectModule3 学时

  Working with Claude Subagents

  Learn to delegate work to subagents and run tasks in parallel without losing the thread.

  你的产出A parallel workflow across a large task

  AI Agents·Claude Code

• BuilderModule3 学时

  Connecting Claude with MCP

  Learn to connect Claude to internal systems using MCP, covering server configuration, authorisation and scopes.

  你的产出Claude connected to three internal systems

  AI Agents·Claude, MCP

• ArchitectLab3.5 学时

  Building Secure MCP Servers

  Learn to build your own MCP server and then attack it, covering tool design, auth and injection surface.

  你的产出A reviewed MCP server exposing internal data

  AI Agents·MCP

• ArchitectLab3.5 学时

  Building Agents with the Claude Agent SDK

  Learn to build and deploy production agents with the Agent SDK, covering the loop, tools, sessions and permissions.

  你的产出A deployed agent built on the SDK

  AI Agents·Agent SDK

• GroundModule2.5 学时

  Claude for Documents and Spreadsheets

  Learn to produce finished Excel, PowerPoint, Word and PDF deliverables with Claude.

  你的产出Three finished deliverables produced end to end

  AI for Business Functions·Claude

• ArchitectModule3 学时

  Deploying Claude on Bedrock and Vertex

  Learn to run Claude inside your own cloud, covering regions, networking, IAM and quotas.

  你的产出A deployment meeting your residency requirements

  Deployment & Operations·Bedrock, Vertex

• BuilderModule2.5 学时

  Administering Claude for Business

  Learn to manage seats, roles, data controls, retention and audit logs across an organisation.

  你的产出An admin configuration with a written policy

  Governance & Compliance·Claude Enterprise

• OperatorModule2 学时

  Understanding Claude's Safety Behaviour

  Learn how Constitutional AI and the usage policy shape refusals, and how to design around them honestly.

  你的产出A refusal-handling guide for your teams

  Governance & Compliance·Claude

• BuilderModule2 学时

  Managing Claude API Costs

  Learn to reduce spend with prompt caching, batch processing, model tiering and context discipline.

  你的产出A cost reduction with cache-hit evidence

  Deployment & Operations·Claude

• GroundModule2 学时

  Claude for Non-Technical Teams

  Learn to get real work out of Claude without writing code, using projects, files and artifacts.

  你的产出A personal workflow adopted for a week

  AI Foundations·Claude

• BuilderModule2.5 学时

  Comparing and Evaluating Claude Models

  Learn to choose between Claude model tiers and thinking budgets using evaluations rather than defaults.

  你的产出A model-choice decision backed by evals

  Evaluation & Testing·Claude

• GroundModule2.5 学时

  Introduction to Microsoft Copilot

  Learn to use Copilot across Word, Excel, PowerPoint, Outlook and Teams, including its real limits.

  你的产出A weekly workflow across three apps

  AI for Business Functions·Copilot

• OperatorLab3 学时

  Microsoft Copilot in Excel

  Learn to use Copilot for analysis, formulas, cleaning and modelling, with verification built in.

  你的产出A rebuilt model with checks

  AI for Business Functions·Copilot, Excel

• BuilderLab3 学时

  Building Agents with Copilot Studio

  Learn to build, publish and govern an internal agent on Microsoft's stack.

  你的产出A published internal agent

  AI Agents·Copilot Studio

• OperatorLab3 学时

  Automating Workflows with Power Automate

  Learn to automate real business processes, including the error paths most people skip.

  你的产出A production flow with error handling

  AI Agents·Power Automate

• ArchitectModule3 学时

  Introduction to Azure AI Foundry

  Learn to deploy, filter, evaluate and monitor models in Azure AI Foundry.

  你的产出A deployed endpoint with monitoring

  Deployment & Operations·Azure

• BuilderModule2.5 学时

  Governing Microsoft Copilot

  Learn to handle oversharing, sensitivity labels and the permission clean-up a Copilot rollout requires.

  你的产出A rollout plan with permission remediation

  Governance & Compliance·Purview, Copilot

• OperatorModule2.5 学时

  GitHub Copilot for Teams

  Learn to roll out GitHub Copilot with team standards, review expectations and honest measurement.

  你的产出A team standard with measured adoption

  AI for Software Engineering·GitHub Copilot

• GroundModule2.5 学时

  Introduction to Google Gemini

  Learn to use Gemini across Docs, Sheets, Slides, Gmail and Meet for everyday work.

  你的产出A weekly workflow across Docs, Sheets and Gmail

  AI for Business Functions·Gemini

• GroundModule2 学时

  Research and Synthesis with NotebookLM

  Learn to synthesise your own sources with grounded answers and citation discipline.

  你的产出A sourced synthesis of a real document set

  AI for Business Functions·NotebookLM

• ArchitectModule3 学时

  Introduction to Vertex AI

  Learn to deploy, ground and evaluate models on Google Cloud using Vertex AI.

  你的产出A deployed model with grounding configured

  Deployment & Operations·Vertex

• BuilderLab2.5 学时

  Building Agents with Google ADK

  Learn to build and deploy multi-tool agents with the Agent Development Kit.

  你的产出A working multi-tool agent

  AI Agents·ADK

• BuilderModule3 学时

  Generative AI in BigQuery

  Learn to run embeddings and inference next to your warehouse in SQL, with cost control.

  你的产出A warehouse-native AI workflow

  Retrieval & RAG·BigQuery

• BuilderModule2 学时

  Governing Gemini in Google Workspace

  Learn to configure admin controls, data handling and retention across a Workspace tenancy.

  你的产出An admin configuration with a data policy

  Governance & Compliance·Workspace

• BuilderModule2 学时

  Introduction to Open Source AI Models

  Learn the differences between open weights and open source, and where open models genuinely win.

  你的产出A shortlist with licence notes

  AI Foundations·Llama, Mistral, Qwen, DeepSeek

• BuilderLab2.5 学时

  Running AI Models Locally

  Learn to run models on a laptop or single server with Ollama and llama.cpp, with realistic expectations.

  你的产出A local model serving your own tool

  Deployment & Operations·Ollama, llama.cpp

• BuilderModule3 学时

  Introduction to Hugging Face

  Learn to use models, datasets and pipelines from the Hugging Face Hub in working code.

  你的产出A pipeline built from hub components

  Machine Learning·Hugging Face

• ArchitectLab3.5 学时

  Serving Open Models with vLLM

  Learn to serve open models at scale, covering throughput, batching, KV cache and cost per million tokens.

  你的产出A benchmarked serving stack

  Deployment & Operations·vLLM

• ArchitectCase3.5 学时

  Building a Self-Hosted AI Stack

  Learn to design a fully self-hosted or air-gapped AI architecture, and what you take on by doing so.

  你的产出An architecture meeting an air-gap requirement

  Deployment & Operations·vLLM, pgvector

• BuilderModule2.5 学时

  Open Source Embeddings and Rerankers

  Learn to build a retrieval stack with no external API calls, and compare it to hosted alternatives.

  你的产出A retrieval stack with no external calls

  Retrieval & RAG·BGE, E5

• BuilderModule3 学时

  The AI-Native Software Lifecycle

  Learn how each phase of software delivery changes when agents write most of the code, from requirements through to maintenance.

  你的产出A map of your own lifecycle

  AI-Native SDLC & Harness·不用工具

• BuilderModule2.5 学时

  From Vibe Coding to Agentic Engineering

  Learn the difference between prompting your way to code and engineering a system that produces it, and work out where your team actually sits.

  你的产出A placement of your team on the spectrum

  AI-Native SDLC & Harness·不用工具

• BuilderCase2.5 学时

  The Factory Model

  Learn to treat your output as the system that produces code rather than the code itself, covering specifications, agents, quality gates and feedback.

  你的产出A written design for your delivery system

  AI-Native SDLC & Harness·不用工具

• BuilderModule3 学时

  Harness Engineering Fundamentals

  Learn why an agent is a model plus a harness, and what the harness is made of: instructions, tools, sandboxes, orchestration, hooks and observability.

  你的产出A harness diagram for one team

  AI-Native SDLC & Harness·Claude Code, Cursor

• BuilderLab3 学时

  Writing Rule Files for Agents

  Learn to write the instruction files that define how an agent behaves in your codebase, and to keep them short enough to stay effective.

  你的产出A reviewed rule file in your repository

  AI-Native SDLC & Harness·Claude Code, AGENTS.md

• BuilderLab3 学时

  Building Skills as Shared Capability

  Learn to turn engineering standards, workflows and debugging practice into reusable skills rather than prompts people copy between chats.

  你的产出A packaged skill your team installs

  AI-Native SDLC & Harness·Claude, Agent Skills

• BuilderModule2.5 学时

  Rules, Policies and Constraints

  Learn the difference between deterministic rules such as naming conventions and organisational policies such as data handling and approval requirements.

  你的产出A rule and policy set for one team

  AI-Native SDLC & Harness·不用工具

• ArchitectModule3 学时

  Treating Context as Code

  Learn to version, review and lint the context your agents run on, so that specifications, rules and outputs stay consistent with each other.

  你的产出A versioned context repository

  AI-Native SDLC & Harness·Spec Kit, Git

• BuilderLab3 学时

  Specification Design for Agents

  Learn to write specifications precise enough for an agent to execute without clarification, and to spot the ambiguity that causes rework.

  你的产出A specification an agent completed unaided

  AI-Native SDLC & Harness·Spec Kit

• BuilderLab3.5 学时

  Building the Agent Loop

  Learn the loop at the centre of every agent, covering perceive, plan, act, observe and iterate, by building one without a framework.

  你的产出A working loop you wrote yourself

  AI-Native SDLC & Harness·Python, Claude

• ArchitectLab3.5 学时

  Loop Engineering

  Learn to control how an agent iterates, using termination conditions, deterministic quality gates, and feedback that pushes the agent back on course.

  你的产出A loop with working quality gates

  AI-Native SDLC & Harness·Claude Code, CI

• ArchitectLab3.5 学时

  Graph Engineering for Agent Workflows

  Learn to model work as a graph of nodes and edges rather than a single loop, covering branching, joins, shared state and parallel execution.

  你的产出A graph running work in parallel

  AI-Native SDLC & Harness·LangGraph, Python

• BuilderModule2.5 学时

  Conductor and Orchestrator Modes

  Learn the two ways developers work with agents, hands on in real time and asynchronously across several agents, and when to switch between them.

  你的产出A written split of the two modes

  AI-Native SDLC & Harness·Claude Code, Cursor

• BuilderModule3 学时

  Human in the Loop Orchestration

  Learn to run a supervised chain of agents through planning, implementation, testing and review, with clarifications flowing through a person.

  你的产出An orchestration flow with approval points

  AI-Native SDLC & Harness·Claude Code

• ArchitectLab3.5 学时

  Autonomous Multi-Agent Orchestration

  Learn to run agents in parallel that coordinate through shared context, and to recognise when this is genuinely better than one agent.

  你的产出A parallel workflow with shared state

  AI-Native SDLC & Harness·Claude, subagents

• ArchitectLab3 学时

  Hooks and Deterministic Guardrails

  Learn to run your own code at fixed points in an agent's lifecycle, before a tool call, after an edit or before a commit, for the things agents forget.

  你的产出A hook set enforcing your standards

  AI-Native SDLC & Harness·Claude Code, hooks

• ArchitectModule3 学时

  Agent Sandboxing and Isolation

  Learn to contain what an agent can reach, covering isolation layers, the threats each one addresses, and how agents escape when containment is weak.

  你的产出A sandbox design with named threats

  AI-Native SDLC & Harness·Containers, Claude

• ArchitectLab3.5 学时

  Evaluating the Harness

  Learn to evaluate the system around the model across four layers, from reviewing skills for conflicts through to measuring whether real tasks succeed.

  你的产出A four layer evaluation suite

  AI-Native SDLC & Harness·LLM judge, CI

• ArchitectModule3.5 学时

  Agent Memory Architecture

  Learn how agent memory develops from simple project files through structured indexes to semantic retrieval, and how to choose the level you need.

  你的产出A memory design for your team

  AI-Native SDLC & Harness·Claude Code, memory

• ArchitectModule3 学时

  Feedback Loops and Harness Improvement

  Learn to turn production usage into signal that improves the system, using human corrections, evaluation results and retrieval tuning.

  你的产出A improvement loop with measured gain

  AI-Native SDLC & Harness·Evals, telemetry

• BuilderLab3 学时

  Connecting Agents to Your Toolchain

  Learn to give agents access to the systems they need to plan, build and ship, covering source control, tickets, design files and pipelines.

  你的产出Three connected internal systems

  AI-Native SDLC & Harness·MCP, GitHub, Jira

• ArchitectModule3 学时

  Running Agents in Parallel

  Learn the practical options for supervising many agents at once, and the coordination problems that appear as soon as you run more than a few.

  你的产出A working parallel setup

  AI-Native SDLC & Harness·Claude Code, tmux

• BuilderCase3 学时

  The Economics of Agentic Engineering

  Learn why casual prompting is cheap to start and expensive to run, and how upfront investment in context and tests reverses that.

  你的产出A cost model for your team

  AI-Native SDLC & Harness·不用工具

• ArchitectModule2.5 学时

  Intelligent Model Routing

  Learn to send each task to the cheapest model that can complete it, and to measure what routing saves without losing quality.

  你的产出A router with a measured saving

  AI-Native SDLC & Harness·Gateways

• BuilderModule2.5 学时

  The Eighty Percent Problem

  Learn why agents produce most of a feature quickly and then stall on edge cases and integration, and where to direct human attention instead.

  你的产出A written boundary for your codebase

  AI-Native SDLC & Harness·不用工具

• BuilderModule3 学时

  Reviewing Code You Did Not Write, at Volume

  Learn to keep review meaningful when most code is generated, covering what to read closely, what to automate, and how to avoid rubber stamping.

  你的产出A review process that scales

  AI-Native SDLC & Harness·GitHub, Claude

• BuilderModule3 学时

  Redesigning QA for the AI Lifecycle

  Learn how quality assurance shifts from running tests to owning the evaluation system that decides whether work can ship.

  你的产出A test strategy with automated gates

  AI-Native SDLC & Harness·CI, evals

• BuilderModule2.5 学时

  Release Management with Automated Gating

  Learn to move release decisions from manual sign off to automated gates, and to decide which gates a human still has to hold.

  你的产出A release process with defined gates

  AI-Native SDLC & Harness·CI/CD

• ArchitectCase2.5 学时

  Building a Platform Team for AI Engineering

  Learn to set up the team that owns the shared harness, covering what it builds, what it standardises and how it keeps the path easy to follow.

  你的产出A team charter and golden path

  AI-Native SDLC & Harness·不用工具

• BuilderCase2.5 学时

  Starting an AI Engineering Programme

  Learn to start with a pilot rather than a mandate, covering how to choose the first team, build the sandbox and grow adoption from results.

  你的产出A pilot plan with success criteria

  AI-Native SDLC & Harness·不用工具

• BuilderModule3 学时

  Cloud-Native DevSecOps Foundations

  Learn how security moves into every stage of delivery in a cloud-native pipeline, and where AI genuinely helps rather than adding noise.

  你的产出A map of your current pipeline

  Cloud-Native DevSecOps·不用工具

• BuilderLab2.5 学时

  Auditing Your Delivery Pipeline

  Learn to audit a pipeline for the stages where security is manual or missing entirely, and to rank the gaps by risk rather than by ease.

  你的产出A gap list ranked by risk

  Cloud-Native DevSecOps·CI/CD

• BuilderLab2.5 学时

  Catching Secrets Before They Are Committed

  Learn to detect hardcoded credentials and insecure patterns in the editor and at commit time, before they reach a repository.

  你的产出Scanning running on every commit

  Cloud-Native DevSecOps·Git, IDE plugins

• BuilderModule3 学时

  AI-Assisted Code Scanning

  Learn how contextual scanning cuts false positives by telling test credentials from production ones, and how to tune it for your stack.

  你的产出A scan with a reduced false positive rate

  Cloud-Native DevSecOps·SAST tools

• BuilderLab3 学时

  Securing Infrastructure as Code

  Learn to scan Terraform, Helm and CloudFormation for misconfiguration, and to separate deliberate overrides from genuine mistakes.

  你的产出Scanning across your templates

  Cloud-Native DevSecOps·Terraform, Helm

• BuilderModule2.5 学时

  Container and Registry Security

  Learn to audit images continuously against known vulnerabilities, and to keep base images current without blocking delivery.

  你的产出A registry with continuous auditing

  Cloud-Native DevSecOps·Docker, registries

• ArchitectLab3.5 学时

  Kubernetes Runtime Security

  Learn to establish behavioural baselines for workloads, detect anomalies at runtime, and generate network policies from observed traffic.

  你的产出Baselines and policies for one cluster

  Cloud-Native DevSecOps·Kubernetes

• ArchitectLab3 学时

  Admission Control and Policy as Code

  Learn to express security policy as code and enforce it at admission, so non-compliant workloads never reach the cluster.

  你的产出Policies blocking non-compliant workloads

  Cloud-Native DevSecOps·OPA, Kubernetes

• ArchitectModule3 学时

  Behavioural Threat Detection

  Learn to detect threats by deviation from normal behaviour rather than by signature, and to keep alert volume low enough to be useful.

  你的产出A detection baseline with alert rules

  Cloud-Native DevSecOps·CWPP tools

• ArchitectLab3.5 学时

  Building an AI Security Pipeline

  Learn to assemble security into every pipeline stage in the right order, from editor and commit through build, deploy and runtime.

  你的产出A pipeline secured end to end

  Cloud-Native DevSecOps·CI/CD, scanners

• ArchitectModule3 学时

  Securing an AI-Written Codebase

  Learn what changes when most of your code is generated, covering review depth, dependency choices and the vulnerabilities agents repeat.

  你的产出A control set for generated code

  Cloud-Native DevSecOps·不用工具

• ArchitectModule3 学时

  Autonomous Security Response

  Learn to let agents act on security findings within firm limits, covering what they may remediate alone and what always needs a person.

  你的产出A response playbook with defined limits

  Cloud-Native DevSecOps·SOAR, agents

• BuilderModule4 学时

  Deep Learning with Keras and TensorFlow

  Learn to build and train neural networks with Keras and TensorFlow, and understand where they differ from PyTorch in practice.

  你的产出A trained network

  Machine Learning·Keras, TensorFlow

• BuilderLab4 学时

  Computer Vision with Deep Learning

  Learn to build models that work on images, covering convolutional networks, transfer learning and data augmentation.

  你的产出An image classifier with a measured accuracy

  Machine Learning·PyTorch, Keras

• BuilderModule3.5 学时

  Sequence Models and Recurrent Networks

  Learn how models handle ordered data such as text and time series, and why transformers largely replaced recurrent networks.

  你的产出A working sequence model

  Machine Learning·PyTorch, Keras

• BuilderModule4 学时

  Reinforcement Learning Foundations

  Learn how an agent learns from reward rather than labelled examples, covering environments, policies, value functions and exploration.

  你的产出An agent that learns a task

  Machine Learning·Gymnasium, Python

• ArchitectLab4 学时

  Deep Reinforcement Learning

  Learn to combine reinforcement learning with neural networks, and understand why these systems are unstable and expensive to train.

  你的产出A trained deep RL agent

  Machine Learning·PyTorch, Gymnasium

• BuilderModule4 学时

  Natural Language Processing Foundations

  Learn the text processing techniques that still matter alongside language models, covering tokenisation, entities, classification and topic modelling.

  你的产出A working text pipeline

  Machine Learning·spaCy, Python

• BuilderLab2.5 学时

  Tracking Experiments with MLflow

  Learn to record parameters, metrics and artefacts for every training run, so results can be compared and reproduced later.

  你的产出A tracked set of experiments

  Machine Learning·MLflow

• ArchitectModule3 学时

  Scaling Model Training

  Learn to train larger models across multiple GPUs, covering distributed strategies, mixed precision and checkpointing.

  你的产出A training job across several GPUs

  Machine Learning·PyTorch Lightning

• BuilderLab3.5 学时

  Serving AI Models with FastAPI

  Learn to put a model behind an API that can handle real traffic, covering request validation, async handling, timeouts and containers.

  你的产出A deployed inference endpoint

  Building AI Applications·FastAPI, Docker

• OperatorModule2.5 学时

  Building Custom Assistants and GPTs

  Learn to build a configured assistant for a specific job without writing an application, and to know when this is not enough.

  你的产出A published internal assistant

  Building AI Applications·OpenAI, Claude

• BuilderCase2.5 学时

  Choosing an Agent Framework

  Learn what the main agent frameworks actually differ on, and how to choose one without rewriting your system six months later.

  你的产出A framework decision with reasoning

  Building AI Applications·LangChain, LlamaIndex, CrewAI, Haystack

• BuilderModule3 学时

  Vector Search in Your Existing Database

  Learn to add vector search to the database you already run, and to judge when a dedicated vector store is genuinely worth adding.

  你的产出Vector search running on your own database

  Retrieval & RAG·Postgres, MongoDB, Elastic

• BuilderLab3 学时

  Generative AI in Snowflake

  Learn to run generative AI next to your data in Snowflake, covering built in functions, cost control and keeping data in place.

  你的产出An AI workflow running in the warehouse

  Retrieval & RAG·Snowflake

• BuilderLab3 学时

  Building AI Agents in Snowflake

  Learn to build agents that answer questions against warehouse data, with the access controls your data team will require.

  你的产出An agent answering questions over warehouse data

  Retrieval & RAG·Snowflake

• BuilderModule3 学时

  AI on Databricks

  Learn to build and serve AI workloads on Databricks, covering notebooks, model serving and governance across the lakehouse.

  你的产出A working pipeline on Databricks

  Retrieval & RAG·Databricks

• OperatorModule2.5 学时

  AI in Business Intelligence Tools

  Learn to use the AI features built into business intelligence tools for summaries, natural language queries and anomaly detection.

  你的产出An AI assisted report

  Retrieval & RAG·Power BI, Tableau

• OperatorCase2.5 学时

  Choosing Your AI Coding Tools

  Learn what actually separates the main AI coding tools, and how to choose for your team rather than by preference or habit.

  你的产出A tool decision for your team

  AI for Software Engineering·Cursor, Windsurf, Copilot, Claude Code

• GroundLab2.5 学时

  Rapid Prototyping with AI App Builders

  Learn to build a working prototype from a description using AI app builders, and to recognise when it must be rebuilt properly.

  你的产出A working prototype

  AI for Software Engineering·Replit, v0

• OperatorModule3 学时

  AI for Consulting

  Learn to use AI across research, analysis, slide production and client deliverables, with the quality checks the work requires.

  你的产出A client deliverable produced end to end

  AI for Business Functions·Claude, Copilot

• GroundModule2 学时

  AI Ethics

  Learn the ethical questions AI raises at work, covering fairness, consent, displacement and accountability, using real cases rather than abstractions.

  你的产出A written position on three real dilemmas

  AI Foundations·不用工具

• BuilderModule2.5 学时

  Responsible AI Data Management

  Learn to manage the data behind AI responsibly, covering consent, purpose limitation, retention and what happens when someone asks for deletion.

  你的产出A data handling standard for AI use

  Governance & Compliance·不用工具

• OperatorCase2.5 学时

  AI Business Models and Monetisation

  Learn how organisations actually make money from AI, covering direct products, embedded features, cost reduction and where margins disappear.

  你的产出A monetisation model for one AI product

  Leadership & Strategy·不用工具