IBM watsonx Generative AI Engineer Associate (C1000-185) Certification Sample Questions

The purpose of this Sample Question Set is to provide you with information about the IBM watsonx Generative AI Engineer v1 - Associate exam. These sample questions will make you very familiar with both the type and the difficulty level of the questions on the C1000-185 certification test. To get familiar with real exam environment, we suggest you try our Sample IBM watsonx Generative AI Engineer Associate Certification Practice Exam. This sample practice exam gives you the feeling of reality and is a clue to the questions asked in the actual IBM Certified watsonx Generative AI Engineer - Associate certification exam.

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IBM C1000-185 Sample Questions:

01. Which two statements about approximate nearest-neighbour search in a vector store such as Milvus or Elasticsearch are accurate?

(Choose two.)

a) It guarantees the same results as an exhaustive search every time

b) It answers far faster than checking every stored vector

c) It removes the need to choose an embedding model carefully

d) It may occasionally miss a genuinely nearest match

02. A team using InstructLab can generate as many instruction-response pairs as it likes from its seed examples, and has a few hundred human-written ones.

Which two principles should govern the mix?

(Choose two.)

a) The synthetic portion should be generated by the model being tuned

b) The two kinds should be kept in separate training runs

c) The human-written examples should anchor the cases that matter most

d) Generated volume should not be allowed to swamp the verified examples

03. Why do ingestion pipelines commonly let consecutive chunks share some text at their boundaries?

a) So the embedding model always receives inputs of a consistent overall length

b) So duplicate passages can be detected and removed at query time

c) So an answer spanning a boundary is not split across two chunks

d) So the total number of chunks held in the index is reduced substantially

04. An endpoint reports healthy throughout an incident in which every answer it returned was an error message from the model provider. Which two properties should the health check have had?

(Choose two.)

a) It checks the shape of what comes back, not merely that something did

b) It asserts that the answer is factually correct before reporting healthy

c) It runs the full production prompt on every check

d) It exercises the model call rather than only the process being up

05. Where should the API credential an application uses to call a model endpoint be kept?

a) In the application source code, restricted to the private repository it lives in

b) In a secret store the application reads at run time

c) In the deployment configuration file that is committed alongside the code

d) In the prompt template, so every call carries it consistently

06. A retrieval-backed assistant answers in about four seconds. The vector search returns in under a hundred milliseconds and the network round trip is negligible. Where is the time going?

a) Generating the response tokens

b) Embedding the incoming query before the search

c) Searching the vector store for matching passages

d) Transporting the request and response across the network

07. Which two statements about running AI guardrails on a deployed endpoint are accurate?

(Choose two.)

a) They add processing time to every request they inspect

b) They remove the need for a prompt that states acceptable behavior

c) They make the underlying model incapable of producing the filtered content

d) They can inspect what goes in as well as what comes out

08. A tuned model is in production. Users report a handful of wrong answers each week, and the team fixes them by adjusting prompts and retuning. What should be done with each reported failure?

a) Add it to a held-out set that every future version is measured against before release

b) Add it to the training data so the next run learns the correct answer for that case

c) Record it in the incident log and close it once the answer has been corrected

d) Discard it once fixed, since a corrected case no longer represents a defect

09. The passages returned for a question are all about the right topic, and none of them contains the specific figure the user asked for, which does exist in the corpus. Which component should be examined first?

a) The generation model

b) The document extraction step

c) The prompt template

d) The retriever

10. A corpus holds five years of released product manuals, and questions about the current release keep returning passages from superseded ones. What is the fix at ingestion time?

a) Retrieve more chunks so the current release appears somewhere among them

b) Re-embed the corpus so the newer manuals produce stronger matches

c) Attach the release and publication date to each chunk so retrieval can prefer the current one

d) Remove the older manuals from the corpus entirely

Answers:

Question: 01 Answer: b, d	Question: 02 Answer: c, d	Question: 03 Answer: c	Question: 04 Answer: a, d	Question: 05 Answer: b
Question: 06 Answer: a	Question: 07 Answer: a, d	Question: 08 Answer: a	Question: 09 Answer: d	Question: 10 Answer: c

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