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1. CIW 1D0-184 Certification
Study Guide with
Questions
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2. Exam Code 1D0-184
Full Exam Name CIW AI Data Science Specialist
Number of Questions 54
Practice Exams CIW 1D0-184 Certification Practice Exam
Passing Score 74.07%
Time Limit 75 mins
Schedule Exam PSI Store
CIW Shop
1D0-184 Exam Detail
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3. • Perform enough practice with CIW system with related CIW 1D0-184
certification subjects
• Identify the key configuration, workflow and data flow
• Understand the all Syllabus Topics of Exam which are Given in
Description.
• Identify your weak areas from practice test and do more practice with
system
• Repeat practice exams and try to score 100% on www.edusum.com
How to Prepare for 1D0-184
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4. 1D0-184
Exam Questions
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5. Option.
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
Q 1) Why is data normalization important in data preparation?
(Choose two)
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6. a) To ensure that different scales of data do not impact the
analysis
d) To adjust values to a common scale without distorting
differences in ranges
ANSWER
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7. Q 2) What are common types of databases used in data management?
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Option.
a) Spreadsheets and Word documents
b) Relational databases and NoSQL databases
c) Physical filing systems
d) Personal diaries

8. ANSWER
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b) Relational databases and NoSQL databases

9. Q 3) What is the primary goal of applying statistical and mathematical
solutions in data analysis?
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Option.
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

10. ANSWER
d) To identify and interpret patterns and
relationships in data
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11. Q 4) How do classification and regression differ in data analysis?
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Option.
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

12. ANSWER
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a) Classification predicts categorical outcomes;
regression predicts numerical outcomes

13. Q 5) Which of these are ethical guidelines to be applied in data science?
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Option.
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

14. ANSWER
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b) Transparency in how data models work

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• A CIW certification is increasingly becoming important for the
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• The fees information are for the informative purposes and do not
serve as an official offering and are subject to change
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find it out
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