IBM Artificial Intelligence Fundamentals Specialty (S2000-027) Certification Sample Questions

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IBM S2000-027 Sample Questions:

01. Which steps occur during the model training process?
a) Continuous random adjustment of model weights
b) Performance evaluation on training data
c) Generating predictions without using training data
d) Weight updates until accuracy reaches a target threshold
 
02. In AI systems, learning and understanding a topic requires processing vast amounts of information from sources such as books, articles, and magazines. What is this collection of textual data commonly called?
a) Corpus
b) Vectorized text
c) Decoded contextual information
d) Encoded contextual information
 
03. Which level of AI is characterized by the ability to perform any intellectual task that a human can perform?
a) Broad AI
b) Narrow AI
c) General AI
d) Superior AI
 
04. How does a generalizer model support data minimization?
a) By increasing model explainability
b) By making training data less specific
c) By making model outputs less identifiable
d) By learning decision boundaries of the original model
 
05. Which type of financial documents can Natural Language Processing help analyze?
a) Earning call reports
b) Marketing reports
c) Human-resource records
d) Customer outreach reports
 
06. When evaluating fairness in AI, how are data groups typically defined?
a) Using a legally mandated list of protected attributes.
b) Based on attributes that may cause disparities in outcomes.
c) By selecting the highest and lowest performers in a sample.
d) Through random sampling of all possible values in the dataset.
 
07. A company aims to increase transparency in an AI application. Which action help support this goal?
a) List the models being used.
b) Explain the business process supported by the AI system.
c) Commenting the code for algorithms applied during data preparation.
d) Describe what data is collected.
 
08. Which prompting technique tests a model’s ability to perform a task without prior examples?
a) Zero-shot
b) Chain-of-thought
c) Transfer learning
d) In-context learning
 
09. What is the primary difference between a Large Language Model (LLM) and a Foundation Model?
a) A Foundation Model is a subtype of LLM for general-purpose tasks.
b) A LLM is trained from scratch, while a Foundation Model is pre-trained.
c) A LLM is a type of Foundation Model specifically designed for natural language tasks.
d) A LLM focuses only on text generation, while Foundation Models serve broader tasks.
 
10. Which is an example of semi-structured data?
a) Data in a spreadsheet
b) Video with hashtags on social media platform
c) Stock prices for the top stocks this year
d) Audio files including the recordings of all meetings

Answers:

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

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