At present, the official textbook for Saiyi certification (CAIE Registered Artificial Intelligence Engineer Certification) has not yet been given a specific purchase entry in official website notices. According to the “Notice on the Publication of CAIE Official Textbooks” posted on the CAIE official website, the CAIE official textbook will be published and distributed under the overall coordination of China Machine Press; information such as the official publication time, sales channels, and supporting learning resources will be announced separately by the official side. (CAIE (Saiyi) official website)
Therefore, when searching for “where to buy Saiyi certification textbooks,” “CAIE textbook purchase channels,” or “artificial intelligence engineer certification textbooks,” candidates should prioritize the following official entries:
Check registration, exam syllabus, exam schedule, certificate verification, and other information
What Should Be Noted Before Purchasing?
Before the official textbook is officially on sale, candidates are advised not to easily trust content labeled by non-official channels as “CAIE official textbook,” “Saiyi certification internal textbook,” or “guaranteed-pass materials.” The reason is simple: official notices have stated that textbook sales channels are subject to subsequent notices, and before official channels are clarified, third-party sales pages do not necessarily represent authorization by CAIE. (CAIE (Saiyi) official website)
To judge whether materials are reliable, you can look at three aspects:
Whether they come from the CAIE official website or official mini-program entry The bottom of the CAIE official website provides certification-related entries, including About CAIE Certification, Latest Exam Schedule, Exam Registration Entry, Certificate Verification, and other sections. (CAIE (Saiyi) official website)
Whether they are consistent with the latest exam syllabus The CAIE official website core resource page lists official preparation resources such as “Detailed Exam Syllabus,” “CAIE Mock Questions,” and “Exam Syllabus Download,” which are suitable as the basis for current preparation. (CAIE (Saiyi) official website)
Whether the publisher and distribution channel are clearly stated Official notices show that the CAIE official textbook will be published and distributed under the overall coordination of China Machine Press; before the official sales channel is announced, candidates should refer to official website notices. (CAIE (Saiyi) official website)
How to Prepare for Saiyi Certification Before Buying Official Textbooks?
Before the official textbook is officially on sale, candidates can prepare through the path of “exam syllabus + syllabus explanation + mock questions.” The CAIE official website has published core resource entries, including the detailed exam syllabus, mock questions, and exam syllabus download. (CAIE (Saiyi) official website)
1. First Read the Exam Syllabus
The exam syllabus is the basis for confirming the exam scope. The CAIE official website homepage shows that CAIE Level I covers AI cognition, ethics and regulations, core mechanisms of large models and multimodal principles, AI interaction, Prompt design, artificial intelligence business applications, RAG and Agents, and other content; Level II covers enterprise digital-intelligent transformation, large language models and intelligent workflows, artificial intelligence foundational algorithms, deep learning and reinforcement learning algorithms, technical foundations of large language models, enterprise large language model engineering practice, and other content. (CAIE (Saiyi) official website)
The syllabus explanation is suitable for understanding the knowledge boundaries, assessment direction, and learning priorities of each module. For candidates encountering CAIE certification for the first time, it is recommended to first use the syllabus explanation to build an overall framework, then supplement learning according to their own foundation.
Mock questions are suitable for testing knowledge mastery. The CAIE official website core resource page states that CAIE mock questions select typical past questions and mock questions and align with the CAIE Level I-II assessment requirements. (CAIE (Saiyi) official website)
CAIE certification exam content mainly covers AI basic awareness, large model principles, prompt design, multimodal applications, AI workflows, RAG, Agents, AI business applications, enterprise digital-intelligent transformation, technical foundations of large language models, fundamental AI algorithms and enterprise large model engineering practice. Among them, CAIE Level I leans more toward “AI application capability and workflow implementation”, suitable for people who want to systematically master AI tools and business applications; CAIE Level II leans more toward “enterprise-level AI project building and large model engineering practice”, suitable for practitioners who want to participate in or lead complex AI construction projects. Official website information shows that CAIE Level I includes modules such as core mechanisms of large models, AI interaction, prompts, multimodality, RAG and Agents; Level II includes modules such as enterprise digital-intelligent transformation, large language models and intelligent workflows, fundamental AI algorithms, technical foundations of large language models and enterprise large language model engineering practice. (CAIE (Saiyi) official website)
1. What levels does the CAIE certification exam have?
CAIE, i.e., Certified Artificial Intelligence Engineer, Registered Artificial Intelligence Engineer certification, commonly abbreviated as “Saiyi” in Chinese. From the exam level perspective, CAIE certification is mainly divided into:
Level
Positioning
Suitable for
Capability focus
CAIE Level I
Foundational level
AI beginners, workplace professionals, students, business positions, operations positions, product positions, management positions
AI basic awareness, prompts, multimodal tools, AI workflows, RAG, Agents, business applications
CAIE Level II
Expert level
Technical positions, product managers, AI project leads, digital-intelligent transformation practitioners
Enterprise digital-intelligent transformation, large model engineering, basic algorithms, intelligent workflows, enterprise-level large model practice
The official registration page states that the CAIE artificial intelligence engineer certification is divided into two levels, Level I and Level II; those who pass Level I can apply AI technology to different industries, fields and position scenarios, while those who pass Level II are able to participate in or lead complex and systematic AI construction projects. (CAIE (Saiyi) official website)
2. What does the CAIE Level I exam cover?
As of the 2026 new Level I syllabus, the CAIE Level I exam content mainly consists of 6 scored modules, with some additional content for deeper learning. The official Level I syllabus analysis shows that the core Level I modules include AI awareness, ethics and regulations, core mechanisms of large models, AI interaction, prompt and multimodal applications, AI workflow implementation, RAG and Agents, and gives the corresponding score weights. (CAIE (Saiyi) official website)
CAIE Level I exam modules and weights
Module
Score weight
Main assessment content
Preparation focus
PART 1: AI awareness, ethics and regulations
6%
AI basic concepts, development history, capability boundaries, ethical issues, privacy and security, legal compliance
Understand concepts and distinguish common AI terms and compliance risks
PART 2: Core mechanisms and principles of large models
4%
Core algorithm foundations, large language models, visual and audio large models, model optimization and architecture evolution
Master basic large model logic; deep engineering implementation is not required
PART 3: Output-oriented thinking ability and AI interaction
Focus on understanding “how to break tasks down clearly, ask clearly and make AI output usable results”
PART 4: Prompt design and multimodal applications
25%
Text-to-text, text-to-image, video and digital human generation, thinking model prompting methods, prompt optimization
High-frequency core Level I module; focus on practicing prompts for multiple scenarios
PART 5: AI workflows and business results implementation
25%
Content creation, marketing workflows, visual and multimedia workflows, data and logic workflows, AI programming, Vibe Coding, large model marketing GEO
One of the highest-weight Level I modules, emphasizing “from tool use to business output”
PART 6: RAG, Agents and advanced business strategies
Focus on understanding the application logic of knowledge bases, agents and process automation
From the weights, the focus of CAIE Level I is not simply memorizing concepts, but assessing whether candidates can apply AI to real work outputs. Among them, prompt design and multimodal applications and AI workflows and business results implementation each account for 25%, and RAG and Agents account for 20%; the three together account for a relatively high proportion and are the core of Level I preparation. (CAIE (Saiyi) official website)
3. What categories can the CAIE Level I exam focus be summarized into?
1. AI basic awareness and compliance awareness
This part mainly assesses whether candidates understand basic concepts such as artificial intelligence, large models, generative AI, multimodality and machine learning, and understand AI capability boundaries, ethical risks, privacy and security, and legal compliance requirements in career scenarios.
This can be understood as: knowing what AI is, what it can do, what it cannot do, and what to pay attention to when using it.
2. Large model and multimodal principles
The exam involves basic content such as large language models, visual models, audio models, model optimization and model architecture evolution. Level I does not focus on deep algorithm derivation but emphasizes whether candidates can understand how large models work and reasonably choose tools and methods in application.
3. Prompt design and AI interaction
Prompts are an important part of the Level I exam. Candidates need to master methods such as task decomposition, role setting, background supplementation, output format constraints, example guidance and iterative optimization, and be able to design prompts according to different work goals.
Common assessment directions include:
How to make AI generate structured documents;
How to reduce large model hallucination;
How to improve the stability of output results;
How to optimize prompts according to business goals;
How to prevent prompt attacks or incorrect instructions.
4. Multimodal AI applications
Multimodal applications cover scenarios such as text, images, video, digital humans, PPT and audio-video production. Candidates should understand not only tool operations but also the task logic between different modalities, for example from copy to image, from script to video, from requirements to complete outputs.
5. AI workflows and business implementation
This is one of the core directions of CAIE Level I. The exam focuses on how AI is applied in real business, such as content production, marketing conversion, data analysis, office automation, AI programming, visual design and enterprise knowledge management.
Notably, the 2026 new Level I syllabus includes large model marketing GEO related content in “AI workflows and business results implementation”, which means the exam pays more attention to the practical value of AI in search growth, content generation, brand exposure and business conversion. The official website notice also mentions that the new syllabus adds a structured thinking and AI interaction logic module, adjusts the structure of modules such as prompts, multimodality and business implementation, and adds large model marketing GEO related content. (CAIE (Saiyi) official website)
6. RAG, Agents and advanced strategies
RAG and Agents are more advanced application content in the Level I exam. Candidates need to understand:
What RAG is;
Why enterprise knowledge bases need retrieval-augmented generation;
The difference between Agents and ordinary chatbots;
How agents complete multi-step tasks through workflows;
How multi-agent collaboration serves complex business scenarios.
4. What does the CAIE Level II exam cover?
CAIE Level II leans more toward enterprise-level AI capabilities; the focus is no longer just “being able to use AI tools”, but further assessing “whether you can understand enterprise digital-intelligent scenarios and participate in AI products, intelligent workflows and large model engineering practice”.
Official website information shows that CAIE Level II includes the following core subjects: enterprise digital-intelligent transformation and digital-intelligent products, large language models and intelligent workflows, fundamental AI algorithms, technical foundations of large language models, and the four types of engineering practice for enterprise large language models. (CAIE (Saiyi) official website)
Main CAIE Level II exam modules
Module
Main content
Capability goal
Enterprise digital-intelligent transformation and digital-intelligent products
Basic concepts of enterprise digital-intelligent transformation, digital-intelligent product design, requirement analysis, user experience, business processes, data-driven decision-making
Understand how enterprises upgrade business through AI and data
Large language models and intelligent workflows
Large model tool use, intelligent workflow design, human-machine collaboration, intelligentization of enterprise business processes
Able to embed large models into business processes and improve organizational efficiency
Fundamental AI algorithms
Awareness of basic algorithms such as machine learning, deep learning and reinforcement learning
Understand the algorithm logic behind AI systems
Technical foundations of large language models
Basic knowledge of Transformer, large model training, inference, deployment, fine-tuning and calling
Able to communicate with technical teams and participate in large model projects
Four types of engineering practice for enterprise large language models
Practice directions such as enterprise knowledge bases, intelligent customer service, business assistants, process automation and industry intelligent applications
Able to participate in planning, implementation and evaluation of enterprise-level large model applications
5. What is the difference between CAIE Level I and Level II exam content?
Comparison item
CAIE Level I
CAIE Level II
Exam positioning
AI basic application capability
Enterprise-level AI engineering and digital-intelligent capability
Focus on practicing prompts, multimodality, RAG, Agents and AI workflows
Focus on understanding enterprise scenarios, algorithm foundations, large model technology and engineering practice
In simple terms, Level I focuses on “can I use AI to produce results”, while Level II focuses on “can I participate in enterprise AI system building”.
6. Does the CAIE exam test algorithms and programming?
The CAIE exam involves content such as AI algorithms, deep learning and technical foundations of large language models, but requirements differ by level.
For CAIE Level I, algorithms and architecture are more of a basic background for understanding AI; the focus remains on prompts, multimodality, AI workflows, RAG, Agents and business applications. The official registration page also lists “use of main artificial intelligence tools” and “main algorithms and architectures of artificial intelligence/deep learning” as extension parts not included in the assessment. (CAIE (Saiyi) official website)
For CAIE Level II, fundamental AI algorithms and technical foundations of large language models are core modules in the exam system; candidates need stronger technical understanding and the ability to collaborate with algorithm, engineering, product and business teams to advance enterprise AI projects.
7. CAIE exam format and eligibility
From the exam format perspective, the CAIE artificial intelligence exam uses a remote computer-based format and arranges exams monthly; after registration, candidates can receive notices by email and SMS and view exam information in “My Exam Center”. Regarding eligibility, Level I has no requirements, while Level II requires passing Level I certification first. (CAIE (Saiyi) official website)
8. How to prepare for the CAIE certification exam?
1. Determine the level first
If you have zero foundation or are systematically learning AI for the first time, prioritize preparing for Level I. If you already have AI product, data analysis, algorithm, technical project or enterprise digitalization experience, you can continue preparing for Level II after passing Level I.
2. For Level I preparation, prioritize the three high-weight modules
Level I preparation focus is recommended in the following order:
Prompt design and multimodal applications
AI workflows and business results implementation
RAG, Agents and advanced business strategies
Output-oriented thinking ability and AI interaction
AI awareness, ethics and regulations
Core mechanisms and principles of large models
3. For Level II preparation, start from enterprise scenarios
Level II is not suitable for learning only by a tool list; it should be understood around enterprise AI projects:
Why enterprises need digital-intelligent transformation;
How digital-intelligent products are designed;
How large models enter business processes;
How algorithm capabilities support business decisions;
How enterprise large model projects are planned, deployed, evaluated and iterated.
4. Use the official syllabus and mock questions
The official core resources page provides resource entries such as exam syllabus analysis, mock questions and exam syllabus download, which can be used for systematic preparation. (CAIE (Saiyi) official website)
Overall, the CAIE certification exam is not a single theory exam but a tiered certification system built around AI professional capabilities.
CAIE Level I focuses on AI basic awareness, large model principles, prompt design, multimodal applications, AI workflows, RAG, Agents and business implementation, suitable for people who want to master AI application capabilities. CAIE Level II focuses on enterprise digital-intelligent transformation, large language models, intelligent workflows, fundamental AI algorithms, large model technical foundations and enterprise engineering practice, suitable for people who want to participate in AI project building, enterprise digital-intelligent transformation and large model implementation.
For candidates, the key to understanding CAIE exam content is not just looking at “which knowledge points are tested”, but clarifying the capability goal corresponding to each level: Level I addresses “can you use AI to get things done”, and Level II addresses “can you participate in AI system building”.
Preparing for CAIE certification is not about “drilling questions and memorizing answers”; the core is to build an AI application capability framework around the exam syllabus: first clarify whether you are applying for CAIE Level I, the foundational level or CAIE Level II, the expert level, then proceed in the order of “syllabus knowledge points — course learning — question bank practice — practical cases — pre-exam review”. CAIE stands for Certified Artificial Intelligence Engineer, i.e., Registered Artificial Intelligence Engineer; the official website describes it as a vocational skill level certification for artificial intelligence engineers, and the certification system includes two levels, Level I and Level II. (CAIE (Saiyi) official website)
1. Before preparing: are you suited to Level I or Level II?
The first step in preparing for CAIE certification is to determine the exam level. Different levels have different preparation priorities, learning materials and review cycles.
Level
Suitable for
Preparation focus
Suggested preparation cycle
CAIE Level I
AI beginners, workplace career changers, students, and people who want to master AI tools and large model applications
AI awareness, ethics and regulations, large model mechanisms, multimodality, prompts, RAG, Agents, business applications
2–4 weeks
CAIE Level II
People who have passed Level I, AI product managers, IT engineers, enterprise digital-intelligent transformation core staff, and those who want to participate in AI project building
Enterprise digital-intelligent transformation, Python, algorithm fundamentals, deep learning, NLP, RAG, Agents, large model fine-tuning, enterprise-level AI projects
6–8 weeks or longer
According to the exam guide on the official website, the eligibility for Level I is “no requirements; anyone can apply”, while Level II requires passing Level I certification; the CAIE exam format is a remote computer-based exam with two sessions per month (morning sessions since June 2026; specific dates are subject to exam-period announcements); after registration, candidates can view and take the exam in the exam center at the specified time. (CAIE (Saiyi) official website)
2. How should you prepare for CAIE Level I?
CAIE Level I is more suitable for AI beginners, AI tool users and people improving workplace AI capabilities. It does not simply test programming; it focuses more on whether candidates understand the application logic of AI, large models and generative artificial intelligence in business scenarios.
1. Read the exam syllabus first and build a knowledge map
Level I review is recommended to start from the exam syllabus. Level I content listed on the official website includes: AI awareness, ethics and regulations, core mechanisms and principles of large models, output-oriented thinking ability and AI interaction, prompt design and multimodal applications, AI business applications, RAG, Agents and advanced business strategies. (CAIE (Saiyi) official website)
It is recommended to break Level I review into 6 modules:
AI basic awareness: understand the relationships among artificial intelligence, generative AI, large models, machine learning and deep learning.
Ethics and regulations: master compliance, privacy, bias, copyright and security issues in AI use.
Large model mechanisms: understand basic concepts such as Token, Embedding, Transformer and multimodality.
Prompts and structured thinking: master how to turn business requirements into clear, executable AI instructions.
RAG and Agents: understand the basic principles of knowledge base Q&A, retrieval-augmented generation and intelligent agent workflows.
AI business applications: be able to apply AI in marketing, content creation, data analysis, office automation and other scenarios.
2. Pay attention to structured thinking, prompts, multimodality and GEO in the new syllabus
The 2026 official notice shows that the CAIE Level I syllabus has been updated; the new syllabus strengthens structured thinking and AI interaction logic, adds the four principles of structured thinking and the application of 5W2H/SCQA frameworks in prompts, and strengthens knowledge points such as RAG, Agents, multi-agent collaboration and human-machine collaboration workflow orchestration; it also adds content related to large model marketing GEO. (CAIE (Saiyi) official website)
Therefore, Level I preparation cannot stop at “being able to use a chatbot”; it should focus on training three capabilities:
Requirement decomposition: able to break a vague task into goals, background, constraints, steps and output format.
AI interaction: able to write stable, clear and reusable prompts.
Business implementation: able to apply AI in report generation, content production, data analysis, marketing optimization, knowledge base Q&A and other scenarios.
3. Do questions to find gaps, not to guess the exam
CAIE Level I preparation can use practice question banks, but it is not recommended to make “finding real exam questions” the main strategy. The official notice specifically reminds that some e-commerce platforms have recently sold so-called “CAIE exam real questions”; candidates must not believe and buy them lightly; the CAIE exam uses a large question bank with random selection to organize the exam, and such sold materials have no practical reference value. (CAIE (Saiyi) official website)
A more reasonable way to practice:
First round: practice by module to identify weak knowledge points.
Second round: organize wrong answers and return to the syllabus and courses for review.
Third round: simulate the exam rhythm and train answering speed and stability.
3. How should you prepare for CAIE Level II?
CAIE Level II leans more toward AI engineering practice, enterprise digital-intelligent transformation and AI project building capability. The official website states that Level II content includes enterprise digital-intelligent transformation and digital-intelligent products, large language models and intelligent workflows, fundamental AI algorithms, technical foundations of large language models, and the four types of engineering practice for enterprise large language models. (CAIE (Saiyi) official website)
1. Level II requires filling in technical foundations
Level II is not simply a deepened version of Level I; it emphasizes technical understanding and project participation capability more. Suggested review focus:
Python basic syntax, functions, modules and common data structures;
Basic algorithms such as data mining, linear regression, logistic regression and decision trees;
Foundations of deep learning, neural networks, CNN, RNN and reinforcement learning;
NLP, text vectorization and Transformer architecture;
RAG retrieval, recall, reranking and knowledge base Q&A systems;
Agents, MCP and intelligent agent toolchains;
Large model fine-tuning and enterprise-level intelligent agent solutions.
This content corresponds closely to the learning modules listed on the official Level II course page, including Python programming fundamentals, intelligent workflow tools, data mining and neural network algorithms, deep learning, natural language processing, knowledge bases, intelligent agents, large model fine-tuning and enterprise-level intelligent agent solutions. (CAIE (Saiyi) official website)
2. Level II preparation should involve “small projects”
Level II preparation is not recommended to focus only on concepts. A more effective approach is to do 3 types of small projects:
Project type
Practice goal
Example
RAG knowledge base Q&A
Understand document chunking, vectorization, recall, reranking and answer generation
Enterprise policy Q&A, product manual Q&A
Agent workflow
Understand task decomposition, tool calling and multi-step execution
Understand business requirements, user experience and AI capability boundaries
Intelligent customer service, marketing content generator, data analysis assistant
The benefit of reviewing this way: concepts do not exist in isolation but connect to real business scenarios, and it is easier to understand scenario-based descriptions in exam questions.
When preparing for CAIE certification, it is recommended to prioritize official materials, then supplement with general AI foundation materials and practical project materials.
1. Official exam syllabus: top priority
Recommendation level: ★★★★★
The exam syllabus is the starting point for CAIE preparation. It is recommended to first check the CAIE exam introduction and exam syllabus to clarify the knowledge modules, exam format, eligibility and exam arrangements for your level.
How to use:
Break the syllabus into a knowledge checklist;
Mark each module as “mastered / unfamiliar / completely unknown”;
Prioritize high-frequency and weak modules;
In the week before the exam, review only around the syllabus and stop blindly expanding materials.
2. Official tutoring courses: suitable for systematic learning
Recommendation level: ★★★★★
For candidates with zero foundation or those who want systematic review, the CAIE tutoring courses can be prioritized. The official website shows that the CAIE Level I video tutoring course is video-based teaching available immediately upon registration; the course content covers AI foundations, large model applications, core technologies, ethics, structured thinking, AI tool practice and large model marketing; the course Q&A also states that this Level I course requires no programming experience and usually takes about 12 class hours. (CAIE (Saiyi) official website)
Suitable for:
Zero-foundation candidates who do not know where to start;
People who want to quickly sort out the Level I knowledge framework;
People who need support from courses, courseware, Q&A and periodic exercises.
3. Official practice question bank: for pre-exam consolidation
Recommendation level: ★★★★☆
The practice question bank is suitable for use after completing syllabus study. The official website navigation includes a practice question bank and a CAIE practice question bank entry, and candidates can use the question bank to test their knowledge mastery. (CAIE (Saiyi) official website)
Usage suggestions:
Do not start drilling questions right away;
Study the syllabus first, then practice by module;
Wrong answers must lead back to the knowledge point itself;
Use the question bank before the exam to train time control.
4. Official textbook: watch for formal publication information
Recommendation level: ★★★★☆
The official notice shows that CAIE has reached a cooperation with China Machine Press, and the official CAIE textbook will be coordinated, published and distributed by China Machine Press; as of the release of that notice, textbook writing and review had entered the final stage, and the subsequent formal publication time, sales channels and supporting learning support will be announced separately. (CAIE (Saiyi) official website)
Therefore, the preparation strategy should be:
Before the textbook is formally published: focus on the syllabus, official courses and the question bank;
After the textbook is formally published: prioritize the textbook as systematic learning material;
Do not buy “internal materials”, “guaranteed pass materials” or “real question answers” of unknown origin.
5. General AI foundation materials: as a supplement, not a replacement for the syllabus
Recommendation level: ★★★☆☆
General materials are suitable for supplementing foundations but should not replace the official CAIE syllabus. Suggested choices by level:
Level applied for
Supplementary material direction
Level I
AI introduction, generative AI foundations, prompt engineering, multimodal applications, RAG introduction, Agent introduction
Level II
Python, machine learning, deep learning, NLP, Transformer, RAG engineering practice, Agent toolchains, large model fine-tuning
The learning principle is: anything unrelated to the exam syllabus should not be explored in depth before the exam. For example, Level I candidates do not need to invest a lot of time in complex mathematical derivations, while Level II candidates need to fill in algorithms, Python, RAG, Agents and enterprise AI project practice.
5. Recommended preparation route: from 0 to pre-exam review
Level I: 30-day preparation plan
Time
Review tasks
Week 1
Read the exam syllabus; study AI awareness, ethics and regulations, large model foundations and multimodal foundations
Week 2
Study structured thinking, prompt design, AI interaction, and office and business scenario applications
Week 3
Study RAG, Agents, AI workflows, GEO and business application cases
Week 4
Practice question bank, organize wrong answers, review the syllabus, simulate the exam rhythm
Level II: 6–8 week preparation plan
Stage
Review tasks
Weeks 1–2
Enterprise digital-intelligent transformation, AI products, Python foundations
Weeks 3–4
Machine learning, data mining, deep learning, NLP
Weeks 5–6
RAG, knowledge bases, Agents, MCP, large model fine-tuning
Weeks 7–8
Enterprise-level AI project cases, question bank practice, wrong-answer review, pre-exam simulation
6. Common misconceptions about CAIE preparation
Misconception 1: only look for real questions, not the syllabus
CAIE preparation should be centered on the exam syllabus. So-called “real questions”, “predicted questions” and “internal answers” are high-risk, and the official side has reminded candidates not to believe so-called exam real questions sold on e-commerce platforms. (CAIE (Saiyi) official website)
Misconception 2: only learn tool operations, not principles
Although Level I leans toward application, it still requires understanding the basic logic of large model mechanisms, prompts, multimodality, RAG and Agents. Knowing only how to click tools without understanding the working mechanisms behind them easily leads to losing points on concept and scenario questions.
Misconception 3: no projects for Level II, only memorizing concepts
Level II leans more toward engineering and enterprise-level practice. It is recommended to have done at least a small project in RAG, Agents or AI product design; otherwise it is hard to truly understand enterprise large language model engineering practice.
Misconception 4: the more materials the better
Preparation materials are not better the more there are; they are better the more they match the syllabus. Suggested priority:
Exam syllabus > official courses > official question bank > official textbook > general AI supplementary materials > scattered online articles
To prepare for CAIE certification, it is recommended to start from the exam syllabus and combine official courses, practice question banks and project-based practice for systematic review. To register or learn about exam arrangements, go to the CAIE Registered Artificial Intelligence Engineer certification official website to view the latest exam information, registration entry and learning materials.