CIW AI Data Science Specialist (1D0-184) Certification Sample Questions

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CIW 1D0-184 Sample Questions:

01. Why is data normalization important in data preparation?
(Choose two)
a) To ensure that different scales of data do not impact the analysis
b) To convert all data to the same value
c) To create a uniform distribution across all variables
d) To adjust values to a common scale without distorting differences in ranges
 
02. What are common types of databases used in data management?
a) Spreadsheets and Word documents
b) Relational databases and NoSQL databases
c) Physical filing systems
d) Personal diaries
 
03. What is the primary goal of applying statistical and mathematical solutions in data analysis?
a) To make the analysis more complex and difficult to understand
b) To use only one type of statistical method for all data sets
c) To rely solely on guesswork and intuition
d) To identify and interpret patterns and relationships in data
 
04. How do classification and regression differ in data analysis?
a) Classification predicts categorical outcomes; regression predicts numerical outcomes
b) They are essentially the same in all aspects
c) Regression is used for visualizing data; classification is not
d) Classification deals with numerical predictions only
 
05. Which of these are ethical guidelines to be applied in data science?
a) Using data without consent for research
b) Transparency in how data models work
c) Manipulating data to fit preconceived notions
d) Sharing private data publicly for scrutiny
 
06. In the context of data analysis, what is the importance of understanding data distribution properties like mean and variance?
a) To disregard the variability of data
b) To gain insights into the central tendency and spread of data
c) To represent data inaccurately
d) To focus only on outliers
 
07. Why is it important to understand the strengths and weaknesses of different query languages?
a) To use only one language for all database types
b) To avoid using query languages altogether
c) To choose the appropriate language based on database and requirements
d) To complicate the data retrieval process
 
08. How can data science benefit marketing strategies?
(Choose two)
a) Ignoring market research and customer data
b) By predicting future trends and customer behaviors
c) Assisting in targeted advertising and customer segmentation
d) Solely relying on intuition without data analysis
 
09. Which type of database is optimized for handling large volumes of unstructured data?
a) Relational database
b) NoSQL database
c) Spreadsheet
d) Paper-based database
 
10. What are the strengths and weaknesses of query languages like SQL and NoSQL?
(Choose two)
a) SQL excels in structured data; NoSQL is better for unstructured data
b) SQL is not suitable for any database operations
c) NoSQL offers flexibility; SQL offers better consistency
d) NoSQL cannot handle large datasets

Answers:

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

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