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 | Automatic weekly report generation, customer profile analysis, travel planning assistant |
| AI product design | 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.
4. Recommended CAIE certification learning materials
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.
Recommended entries:
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.
You can follow: CAIE official textbook publication notice
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.
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