Qlik AI Specialist (QAIS) Certification Exam Sample Questions

Get QAIS Dumps Free, Qlik AI Specialist Certification PDF and Dumps, and QAIS Free Download for comprehensive exam preparation.Welcome! Preparing for the Qlik AI Specialist (QAIS) certification exam can be a daunting task, but we're here to make it easier for you. Here are the sample questions that will help you become familiar with the Qlik QAIS exam style and structure. We encourage you to try our Demo Qlik AI Specialist Certification Practice Exam to measure your understanding of the exam structure in an environment that simulates the actual test environment.

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Qlik QAIS Sample Questions:

01. A revenue operations team wants to forecast next quarter's sales volume for each product line from several years of historical, structured sales data.
Which statement about the fit of Qlik Answers for this task is most accurate?
a) Qlik Answers is a poor fit only because it is structurally unable to process numbers of any kind, structured or unstructured
b) Qlik Answers is the best fit as long as the historical sales data is first converted into a set of written narrative summaries
c) Qlik Answers is a poor fit, since this is a structured-data prediction task better suited to a predictive machine learning approach
d) Qlik Answers is the best fit, since generative assistants are generally more accurate than predictive models at any numeric forecasting task
 
02. In a retrieval augmented generation pipeline, a specific step occurs immediately before the language model composes its final response: relevant passages are located within an indexed knowledge source based on the user's question.
Which step of the RAG pattern does this describe?
a) Retrieval, the step where relevant content is located in the knowledge source before being added to the prompt
b) Fine-tuning, the step where model weights are adjusted using labeled examples drawn from the knowledge source over several training passes
c) Deployment, the step where a finished application is made available for end users to access
d) Tokenization, the general step where text is broken into smaller units before any further processing begins
 
03. When a Qlik Answers assistant returns an answer along with references to the specific source documents it drew from, what is the main purpose of including those references?
a) To reduce the amount of computing time the underlying model needs to generate each individual response
b) To let a reader verify the answer against the original source material and judge its grounding
c) To automatically correct any grammatical errors that appear within the generated answer text itself
d) To permanently remove the referenced source documents from the knowledge base once they are cited
 
04. A team has just finished collecting and cleaning a raw dataset of customer records for a new predictive model, and no modeling work has started yet.
Which activity typically comes next in the machine learning workflow?
a) Deploying the trained model into a live production environment for end users to access immediately
b) Monitoring the live model for signs of degrading accuracy over an extended period of time
c) Publishing the final evaluation report comparing the chosen model against a business benchmark figure
d) Engineering and selecting the features that will be used as model inputs
 
05. A generative AI assistant at Driftwood Analytics confidently states a specific statistic that sounds plausible but does not actually appear anywhere in its source material.
Which limitation of AI does this best illustrate?
a) Hallucination, where the model produces fluent but factually unsupported output
b) Underfitting, where a model is too simple to capture real patterns in the data
c) Overfitting, where a model memorizes its training data too closely to generalize well
d) Latency, where a response takes longer than expected to arrive
 
06. Shoppers using Bellcastle Retail's new AI shopping assistant abandon the chat when responses take more than a few seconds to appear, even though the answers themselves are accurate and well grounded.
Which lever should the team prioritize to address this specific complaint?
a) Expanding usefulness by giving the assistant access to a new inventory-lookup tool
b) Reducing latency, for example through a smaller model, response caching, or streamed output
c) Adapting the data pipeline to add more source documents to the knowledge base
d) Increasing the size of the underlying model so that answer quality improves even further than it already has
 
07. An AI vendor draws a line between a model's "training" phase and its "inference" phase.
Which description best matches the inference phase?
a) Collecting and cleaning the raw data that will eventually be used to build a model in the first place
b) Permanently deleting a model from a system once it is no longer needed for any further use
c) Repeatedly adjusting a model's internal values so its predictions better match already-known outcomes
d) Using an already-trained model to produce an output for a brand-new piece of input data
 
08. Within the commonly used nesting of AI-related terms, one subset specifically refers to models built from multi-layer neural networks trained on large amounts of data.
Which term does this describe?
a) Reinforcement learning, an approach where an agent learns via reward signals from its environment
b) Natural language processing, the broad field concerned with machines working with human language
c) Deep learning, a subset of machine learning built on multi-layer neural networks
d) Retrieval augmented generation, a pattern for grounding generated answers in retrieved content
 
09. Large language models are typically described as being trained on an extensive collection of text examples gathered for that purpose.
What is the common term for this collection of text?
a) A ledger, a running record of financial transactions maintained by an accounting system
b) A corpus, a large body of text assembled for training or evaluating a language model
c) A charter, a formal document that defines the scope and objectives of a business project
d) A manifest, a list of files that are included in a single software release package
 
10. Before writing a single prompt, a team at Ashgrove Consulting spends a week interviewing stakeholders to agree on exactly which business problem a planned generative AI assistant must solve and how success will be measured.
Which stage of the LLM Application Project Lifecycle does this activity represent?
a) Scoping the use case and defining what success looks like
b) Selecting and adapting a base model through prompt engineering, retrieval, or fine-tuning
c) Monitoring the deployed application and retraining it as usage patterns drift
d) Evaluating the built application for quality, groundedness, and safety before release

Answers:

Question: 1 Answer: c Question: 2 Answer: a
Question: 3 Answer: b Question: 4 Answer: d
Question: 5 Answer: a Question: 6 Answer: b
Question: 7 Answer: d Question: 8 Answer: c
Question: 9 Answer: b Question: 10 Answer: a

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