Courses

AI 101

Claude AI Workforce Fundamentals

From generative to agentic AI: learn to judge tasks, write clear work instructions, review AI output, and produce your own Use Case.

6 hours · 中文 / English · L1 Certificate

Recommended start

AI101L

AI Workforce Applied Lab: From Work Tasks to AI Use Cases

Bring AI 101 fundamentals into real work: frame a task, prepare context, execute and review, design a workflow, and produce an AI Workforce Use Case Canvas.

6 hours · 中文 / English · L2 Certificate

AI 101 recommended first

AI 102

Context Engineering: What Should AI Know?

Move from prompts to context: learn what information an AI task needs, which sources to trust, what to retrieve on demand and what never to provide, and complete your own Context Canvas.

6 hours · 中文 / English · L1 + L2 Certificates

Recommended: finish AI 101

AI 103

Agentic AI Memory, Knowledge & Skills

Move from context engineering to agentic AI: design an agent's memory, knowledge and skills, understand memory systems, RAG, semantic chunking, metadata, knowledge architecture and context optimization, and complete your own Agent Memory, Knowledge & Skills Canvas.

6 hours · 中文 / English · L1 + L2 Certificates

Recommended: finish AI 102

AI 104

Agentic AI Workflow & Execution Design

Move from a single AI task to a repeatable agentic workflow: learn task decomposition, sequential / parallel / routing patterns, decision points, the agent loop, execution, verification and human-in-the-loop, decide which steps stay fixed and which the agent may decide, and complete your own Agentic AI Workflow Canvas.

3 hours · 中文 / English · L1 + L2 Certificates

Recommended: finish AI 103

AI 201

Model Context Protocol: Connecting AI to Tools & Trusted Data

From using AI to letting AI use tools and trusted data safely: understand MCP architecture, trace a tool call, compare MCP, APIs and RAG, and design an implementable MCP Tool Canvas.

7 hours · 中文 / English · L1 + L2 Certificates

Recommended: finish AI 101

AI 202

Agentic AI Planning & Reasoning

Move from fixed agentic workflows to agents that plan and adapt on their own: understand ReAct, search, MCTS, self-reflection and adaptive planning, learn to design how an agent chooses its next step from its goal, context, environment state and results, and complete your own Agent Planning & Reasoning Canvas.

7 hours · 中文 / English · L1 + L2 Certificates

Recommended: finish AI 104

AI 301

Multi-Agent Collaboration & Orchestration

Move from a single agent to a multi-agent system: learn to design agent roles, task allocation, delegation, communication, shared context, handoffs, conflict resolution and orchestration, decide when multiple agents are worth it, avoid overlapping responsibilities and uncontrolled information, and complete your own Multi-Agent Architecture Canvas.

8 hours · 中文 / English · L1 + L2 Certificates

Recommended: finish AI 202

AI 302

Agent Harness Engineering & Reliable Automation

Move from "the agent can finish a task" to "the agent keeps running reliably": learn state management, agent loops, state machines, checkpointing, context compaction, verification, human-in-the-loop, retry, failure recovery and observability, design agentic automation that can be interrupted, resumed and verified, and complete your own Agent Harness & Reliability Canvas.

8 hours · 中文 / English · L1 + L2 Certificates

Recommended: finish AI 202

DS 101

ESG Data Science Foundations with Python & AI

Turn ESG questions into trustworthy analysis with Python, pandas, and AI, from data inspection and calculation to visualization and verification.

6 hours · 中文 / English · L2 Certificate

No programming background required

DS 102

Data Wrangling & Data Quality

Turn readable data into analysis-ready data that is trustworthy, reproducible, and traceable: inspect, clean, reshape, integrate, and validate.

6 hours · 中文 / English · L1 + L2 Certificates

DS 101 recommended first

DS 103

Data Visualization & Data Storytelling

Turn analysis results into visual evidence that is accurate, interpretable, and useful for next actions: chart choice, scales, accessibility, annotation, and data storytelling.

6 hours · 中文 / English · L1 + L2 Certificates

DS 101 recommended; DS 102 helpful but not required

DS 104

Exploratory Data Analysis & Statistical Thinking

Build statistical thinking that separates observed differences from supported conclusions: distributions, outliers, sampling, association, and statistical significance.

6 hours · 中文 / English · L1 + L2 Certificates

DS 101 and DS 102 recommended

DS 105

Web 3.0 and Big Data Analysis in Fintech, Green and Sustainable Finance

Use Web3, fintech and sustainable-finance cases to learn how to select data, interrogate evidence with AI, challenge conclusions and make traceable human decisions. No coding required.

3 hours · 中文 / English · L1 Certificate

AI 101 or equivalent AI literacy recommended

DS 201

Predictive Analytics & Machine Learning Foundations

Build predictive-analysis judgment: use proper splits, baselines, and evaluation to decide whether a model is useful rather than merely complex.

7 hours · 中文 / English · L1 + L2 Certificates

DS 104 recommended

DS 202

AI-Assisted Data Science

Use generative AI as an accelerating but verifiable data-science collaborator, with disciplined prompting, code review, verification, and provenance.

7 hours · 中文 / English · L1 + L2 Certificates

DS 102 and DS 104 recommended

DS 301

Data Products & Analytics Workflow Engineering

Turn one-off notebooks into repeatable, observable analytics workflows and data products with validation, recovery, and human approval points.

8 hours · 中文 / English · L1 + L2 Certificates

DS 202 recommended; AI 104 also recommended

DS 302

Data Agents & Intelligent Analytics Systems

Design governed Data Agents that understand analytical intent, access data/tools safely, execute and verify analysis, explain evidence, and leave auditable traces.

8 hours · 中文 / English · L1 + L2 Certificates

DS 301 and AI 104 recommended; AI 201 also recommended

AD 101

AI Use Case Discovery

Starting from your own work, learn to separate problem from solution, spot work friction, and complete a structured AI Use Case Discovery Canvas.

3 hours · 中文 / English · L1 + L2 Certificates

AI 101L recommended first

AD 102

Process & Pain Point Discovery

Use a structured interview to dig deeper into your AD 101 Use Case: find the real process, decisions, and pain points, backed by evidence rather than guesses.

6 hours · 中文 / English · L1 + L2 Certificates

AD 101 recommended first

AD 103

AI Use Case Prioritization

Compare multiple AI Use Cases under limited resources: score Value, Feasibility, Readiness, and Risk separately, and decide the next step instead of computing an opaque total score.

3 hours · 中文 / English · L1 + L2 Certificates

AD 101 / AD 102 recommended first

IL 101

IL 101 | Industry AI Project & Value Design

Turn an already-prioritized AI use case into a project charter, value hypothesis, measurable success criteria, and a pilot scope: a decision-ready Industry AI Project Charter. Does not repeat AD 101-103's use-case discovery, pain-point understanding, or portfolio prioritization.

6 hours · 中文 / English · L2 Certificate

Real industry co-creation project · AI 101L and AD 101 recommended first

IL 201

IL 201 | Industry AI Proof-of-Value Co-creation Lab

Work with an industry sponsor and cross-domain advisors to turn a real industry problem into a testable AI solution, and use the prototype, evaluation, and business evidence to decide whether it is ready for a pilot. Proof of Value, not just proof of concept.

18 hours · 中文 / English · L2 Certificate

Requires an approved Industry AI Project Charter · Requires an industry sponsor

IL 202

IL 202 | Enterprise AI Data, Governance & Integration Readiness

Addresses the prototype-to-pilot readiness gap: data rights, security, privacy, identity/access, integration, governance, ownership, and operations: producing an Enterprise AI Readiness Review.

12 hours · 中文 / English · L2 Certificate

IL 101 recommended, IL 201 ideally completed

IL 301

IL 301 | Enterprise AI Pilot & Adoption Lab

The Industry AI Co-creation Lab's flagship course: move a validated Proof of Value into a controlled real operational setting, run a pilot, and produce a measurable adoption recommendation. The 30 hours are formal guided learning time; the recommended project duration is 6-8 weeks.

30 hours · 中文 / English · L2 Certificate

Flagship course · Requires IL 201 passed and IL 202 readiness approval

IL 302

IL 302 | Enterprise AI Transformation, Scale & Value Realization

A successful pilot does not equal enterprise transformation. IL 302 covers strategy, AI portfolio, operating model, governance, workforce, funding, value realization, and scale: producing an Enterprise AI Transformation Roadmap. Coding expertise is not required.

12 hours · 中文 / English · L2 Certificate

IL 301 recommended, or documented enterprise AI pilot experience

GoAI 101

Government Generative AI & AI Agents: Application, Governance, Procurement & Acceptance

8-hour full edition: starting from real government work, learn AI-use judgment, workflow design, trusted data, permission governance, reliability, procurement, and acceptance. A 6-hour essentials edition is also available.

8 hours · 中文 / English · L1 + L2 Certificates

GoAI 101 · 6h

Government Generative AI and AI Agents: Practical Application, Governance, Procurement, and Acceptance

6-hour essentials edition: the same eight capability facets in six modules and one Canvas, for agencies that can release six hours. An 8-hour full edition is also available.

6 hours · 中文 / English · L1 + L2 Certificates