Reading Outline / English translations
AI Application Learning Materials and Practice Exercises
From concepts and tools to business processes and risk judgment, complete explanations, examples, comparisons, and accompanying video transcripts are provided. Learning can follow course order or be driven by specific work-related issues.
Currently 40 English translations are live, with main text, exercises, and supporting transcripts organized under corresponding courses.
- 01
AI Foundations 1: Concepts and Tools · Basic Concepts
Artificial Intelligence and Machine Learning: Concepts, Training and Workplace Applications
Understand the relationship between AI and machine learning, trace the system from data, training, models, to inference, and assess how it can assist daily tasks.
4 accompanying transcripts Chinese source: 5,600 charactersStart reading → - 02
AI Foundations 1: Concepts and Tools · Development and Applications
The Evolution and Innovation Opportunities of Artificial Intelligence
From rule-based systems to machine learning to generative AI, trace the evolution of AI, and understand how technology, data, and computational conditions jointly create application opportunities.
1 accompanying transcript Chinese source: 5,600 charactersStart reading → - 03
AI Foundations 1: Concepts and Tools · Services and Algorithms
AI Services and Algorithms: From Common Capabilities to Model Customization
Understanding Common AI Services and Algorithms, Comparing Classification, Regression, Clustering, and Model Customization, and Completing In-Depth Readings on Prompt Engineering, RAG, Fine-Tuning, Tool Calling, and Embedding.
20 accompanying transcripts Chinese source: 6,600 charactersStart reading → - 04
AI Foundations 1: Concepts and Tools · Data and Privacy
Data Foundations and Privacy: From System Evolution to Data Responsibility
From files, databases to the cloud, understanding how data systems have evolved, and how data quality, data pipelines, privacy, consent, and governance influence AI usage.
4 accompanying transcripts Chinese source: 3,500 charactersStart reading → - 05
AI Foundations 1: Concepts and Tools · Industry Applications
AI Application Scenarios: How Different Industries Create Value
Through AI use cases in healthcare, finance, retail, and manufacturing, comparing the problems organizations aim to solve, data availability, expected benefits, and constraints to verify during implementation.
4 accompanying transcripts Chinese source: 5,000 charactersStart reading → - 06
AI Foundations 1: Concepts and Tools · Practical Exercises
Exercise: Identify an AI Opportunity Worth Validating
Discover an AI application opportunity in your own work, describe the business problem, affected parties, and measurable value, and distinguish between promising hypotheses and proven outcomes.
Practice exercise Chinese source: 800 charactersStart reading → - 07
AI Foundations 1: Concepts and Tools · Responsible AI
Responsible AI: Benefits, Risks, and Trade-offs of Generative Tools
Through case studies in writing, chatbots, and content generation, understand the convenience, errors, work impacts, psychological dependence, and information risks of generative AI, and practice evaluating benefits against costs.
2 accompanying transcripts Chinese source: 3,400 charactersStart reading → - 08
AI Foundations 1: Concepts and Tools · Ethical Principles
Four AI Ethical Principles: Proportionality, Privacy, Fairness, and Transparency
Understand each of the four principles (proportionality, privacy, and data protection; fairness and bias mitigation; transparency and explainability) through case studies, regulatory comparisons, and video transcripts to assess real-world applications.
1 accompanying transcript Chinese source: 4,300 charactersStart reading → - 09
AI Foundations 1: Concepts and Tools · Practical Exercises
Exercise: Apply the Four Ethical Principles to an AI Application
Select a commonly used AI application and analyze its benefits, risks, and improvement opportunities using the principles of proportionality, privacy, fairness, and transparency, forming a reflective analysis with specific justifications.
Practice exercise Chinese source: 500 charactersStart reading → - 10
AI Foundations 1: Concepts and Tools · Generative AI
Generative AI Fundamentals: Capabilities, Applications, and First Experiment
Understand how generative AI creates text, images, audio, and code; compare common tools, suitable tasks, and limitations; and complete a step-by-step first work scenario experiment.
4 accompanying transcripts Chinese source: 4,300 charactersStart reading → - 11
AI Foundations 1: Concepts and Tools · Models and Implementation
Generative AI Models: GANs, VAEs, Transformers, and Diffusion
Compare GANs, VAEs, Transformers, and diffusion models to understand the implementation pathways, technical choices, cost considerations, and the process of moving from pilot to full-scale adoption.
4 accompanying transcripts Chinese source: 5,500 charactersStart reading → - 12
AI Foundations 1: Concepts and Tools · Practical Exercises
Exercise: Selecting the Right Generative AI for a Work Task
Compare generative AI solutions for a specific work task, specifying required content, tool selection, expected value, and experimental methods, avoiding the common pitfall of choosing a product before identifying its use case.
Practice exercise Chinese source: 500 charactersStart reading → - 13
AI Foundations 1: Concepts and Tools · Content Creation
AI Content Creation: Media Selection and Team Implementation Strategy
Compare AI-driven content creation for text, images, audio, and video; understand how personal tools, integrated platforms, and custom solutions connect to quality standards, team collaboration, and implementation phases.
2 accompanying transcripts Chinese source: 3,700 charactersStart reading → - 14
AI Foundations 1: Concepts and Tools · Risks and Responsibilities
Generative AI Risks: Personal, Social, and Environmental Responsibility
Examine generative AI risks at four levels (personal, interpersonal, social structures, and environmental), include real-world impact cases and full video explanations, and explain the limitations of historical statistics and emission extrapolation.
2 accompanying transcripts Chinese source: 2,700 charactersStart reading → - 15
AI Foundations 1: Concepts and Tools · Practical Exercises
Exercise: Investigate an AI Ethical Dilemma
Identify a real-world AI ethical dilemma, describe what happened, explain the causes, present evidence, and outline how to resolve or mitigate harm, with verifiable sources retained.
Practice exercise Chinese source: 500 charactersStart reading → - 16
AI Foundations 1: Concepts and Tools · Work and Adoption
AI in Work: Augmentation, Automation, and Daily Tasks
Compare AI augmentation and automation, analyze time, repetitiveness, data, and value in daily work, and understand evaluation criteria, personnel training, change management, and pilot implementation methods.
4 accompanying transcripts Chinese source: 3,400 charactersStart reading → - 17
AI Foundations 1: Concepts and Tools · Comprehensive Exercise
Comprehensive Exercise: Propose a Well-Justified AI Operations Plan
Propose an AI operations plan for a specific business problem, using before-and-after workflows, evaluation metrics, role changes, risks, and ethical considerations to form a coherent and logically connected argument.
Practice exercise Chinese source: 900 charactersStart reading → - 18
AI Foundations 1: Concepts and Tools · Comprehensive Lecture
Comprehensive explanation: AI concepts, prompt engineering, and semantic memory
Review AI, machine learning, and generative models in sequence according to the lecture notes, understand semantic space, prompt structure, context, and memory, and improve task descriptions using the CO-STAR framework.
Comprehensive lecture notes Chinese source: 2,800 charactersStart reading → - 19
AI Foundations 1: Concepts and Tools · Comprehensive Lecture
Comprehensive explanation: AI infrastructure, content rights, and business opportunities
Connect AI's computing location, energy, and infrastructure, content rights, and business opportunities; distinguish between technical feasibility, licensing conditions, and actual business value.
Comprehensive lecture notes Chinese source: 2,900 charactersStart reading → - 20
AI Foundations 2: Business Processes · Automation fundamentals
AI workflows: from rule-based automation to intelligent workflows
Transition from rule-based automation to AI workflows; understand triggers, conditions, actions, and feedback; compare fixed workflows, model judgments, and agent responsibilities and supervision boundaries.
1 accompanying transcript Chinese source: 2,100 charactersStart reading → - 21
AI Foundations 2: Business Processes · Extended reading
No-code and Vibe Coding: from prototypes to maintainable applications
Understand the differences between no-code, low-code, and Vibe Coding; compare interface generation, workflow connection, and code maintenance; grasp the gap between prototypes, formal applications, and validation responsibilities.
Knowledge translation Chinese source: 1,400 charactersStart reading → - 22
AI Foundations 2: Business Processes · Data engineering
AI data pipelines: collection, retrieval, and long-term maintenance
Understand the pipeline of AI data from collection, cleaning, transformation, storage to usage; compare processing tools, quality checks, retrieval, and long-term maintenance; connect the data conditions required for reliable output.
3 accompanying transcripts Chinese source: 2,500 charactersStart reading → - 23
AI Foundations 2: Business Processes · Service selection
AI service selection: supply chain, private data, and implementation conditions
Understand the AI service supply chain including models, platforms, tools, and applications; compare organizational selection, private data integration, and custom pathways; and refer to the complete technical document set shared in common.
3 accompanying transcripts Chinese source: 3,000 charactersStart reading → - 24
AI Foundations 2: Business Processes · Agents
AI Agents: goals, planning, tools, and business workflows
Understand how AI Agents combine goals, planning, memory, and tools to execute multi-step business tasks; compare workflow execution with autonomous actions; and clearly define monitoring, permissions, and human takeover.
1 accompanying transcript Chinese source: 2,200 charactersStart reading → - 25
AI Foundations 2: Business Processes · Trustworthy AI
Trustworthy AI: Ethical Frameworks, Oversight, and Responsibility
Compare ethical principles and frameworks for trustworthy AI, understanding how dignity, fairness, privacy, transparency, and accountability enter the design, adoption, and oversight, rather than remaining just slogans.
1 accompanying transcript Chinese source: 2,300 charactersStart reading → - 26
AI Foundations 2: Business Processes · Comprehensive Reference·Framework
Trustworthy AI Ethical Guidelines: Summary, Introduction, and Overall Framework
2019 Trustworthy AI Ethical Guidelines: English translation explaining the three components of legality, ethics, and robustness, as well as the overall framework from fundamental rights and principles to seven requirements and evaluation checklist.
Reference translation Chinese source: 4,400 charactersStart reading → - 27
AI Foundations 2: Business Processes · Comprehensive Reference·Principles
AI Ethical Guidelines: Fundamental Rights and Four Principles
From human dignity, freedom, democracy, and equality, understand the principles of respect for autonomy, harm prevention, fairness, and interpretability, preserving the original arguments on principle conflicts, predictive policing, and redress.
Reference translation Chinese source: 3,900 charactersStart reading → - 28
AI Foundations 2: Business Processes · Comprehensive Reference·Requirements
The Seven Requirements of Trustworthy AI: Technical, Data, and Governance Methods
Complete translation of the seven requirements of trustworthy AI, along with technical and non-technical implementation methods, explaining human oversight, robustness and safety, privacy, transparency, fairness, social well-being, and accountability.
Reference translation Chinese source: 6,700 charactersStart reading → - 29
AI Foundations 2: Business Processes · Comprehensive Reference·Evaluation
AI Risk Assessment Checklist: Governance Responsibilities and Comprehensive Review Questions
2019 Trustworthy AI Pilot Evaluation Checklist: English translation fully retaining the seven sets of questions, and explaining how management, development, procurement, quality, and daily operations collaborate.
Reference translation Chinese source: 4,800 charactersStart reading → - 30
AI Foundations 2: Business Processes · Comprehensive Reference·Context
AI Ethical Guidelines: Application Opportunities, Key Concerns, and Glossary
Translates application opportunities and key concerns in trustworthy AI for energy, transportation, health, and education; personal tracking, identity concealment, scoring, autonomous weapons, and long-term risks, with full retention of terminology explanations.
Reference translation Chinese source: 5,000 charactersStart reading → - 31
AI Foundations 2: Business Processes · Semantic Retrieval
Vector Databases and Semantic Search: Finding Information by Meaning
Explains how vector databases store embeddings and support semantic search, and how understanding chunking, encoding, similarity retrieval, and updating helps grasp the capabilities and limitations of finding information by meaning.
1 accompanying transcript Chinese source: 2,900 charactersStart reading → - 32
AI Foundations 2: Business Processes · Retrieval-Augmented Generation
What is RAG: Bringing business knowledge into response generation
Understanding RAG: How retrieval-augmented generation brings business documents into responses, step by step exploring document chunking, retrieval, context, and generation, and verifying sources, permissions, and document updates
1 accompanying transcript Chinese source: 2,600 charactersStart reading → - 33
AI Foundations 2: Business Processes · System Orchestration
MCP and API: Connecting tools, data, and AI orchestration
Understanding MCP: What it is, how it integrates with APIs to connect tools and data, differentiating capability discovery, actual execution, permissions, and orchestration, clarifying that protocols do not equate to memory or autonomous decision-making
1 accompanying transcript Chinese source: 3,400 charactersStart reading → - 34
AI Foundations 2: Business Processes · Agency and Ethics
AI Intelligence and Agency: Action, choice, and social impact
Understanding intelligence from psychological measurement, cognition, embodiment, and situational perspectives, comparing natural, biological, artificial, and human agency, and discussing goals and responsibilities in AI actions
2 accompanying transcripts Chinese source: 2,700 charactersStart reading → - 35
AI Foundations 2: Business Processes · Mixed Experts
MoE Mixed Expert Model: Routing, Specialization, and Scalability
Explaining the MoE mixed expert model's experts, routing, and sparse activation, comparing internal model structure, multi-model selection, and multi-Agent collaboration, understanding the benefits and costs of scalability
1 accompanying transcript Chinese source: 3,400 charactersStart reading → - 36
AI Foundations 2: Business Processes · Comprehensive Exercise
Comprehensive Exercise: Designing an AI Orchestration Workflow
Design an AI orchestration workflow with specific business objectives, outlining the current state, available data, tools, agent responsibilities, evaluation, and governance, demonstrating how the workflow operates through a clear process and supporting evidence
Practice exercise Chinese source: 800 charactersStart reading → - 37
AI Foundations 2: Business Processes · Reading Reflection
Reading Exercise: Advanced AI Behavior Guidelines and Risk Mitigations
Read the advanced AI behavior guidelines, select one risk mitigation, explain how it is implemented across the system lifecycle, organizational responsibilities, and specific tasks, and continue querying through the public original text
Practice exercise Chinese source: 400 charactersStart reading → - 38
AI Foundations 2: Business Processes · Complete Reference·Guidelines
Hiroshima AI Behavior Guidelines: Full English translation of Eleven Actions
Full English translation of the 2023 Hiroshima AI Behavior Guidelines, including the full substantive text, retaining scope, seven risk categories, and eleven actions, covering testing, reporting, governance, safety, and data protection
Reference translation Chinese source: 3,900 charactersStart reading → - 39
AI Foundations 2: Business Processes · Comprehensive Explanation
Comprehensive Explanation: Workflow Mapping and Organizational Knowledge
Understanding workflows, automation, and agents through the full lecture and verbal explanation, translating organizational experience into rules and relationships, and using case studies to understand ontology, operational framework, and human feedback
1 accompanying transcript Chinese source: 4,300 charactersStart reading → - 40
AI Foundations 2: Business Processes · Comprehensive Demonstration
Comprehensive Demonstration: API, MCP, and Invoice-Processing Agent
Follow a demonstration using API, MCP, image, and 3D tools, then fully review the invoice-processing agent's objectives, project instructions, execution, queries, failure, and correction processes
1 accompanying transcript Chinese source: 4,000 charactersStart reading →
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