ISACA Data Science
Fundamentals Certification
Exam Questions and Answers
ISACA Data Science Fundamentals Exam Guide
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Introduction to ISACA Data Science
Fundamentals Exam
The ISACA Data Science Fundamentals Exam is challenging and thorough preparation
is essential for success. This exam study guide is designed to help you prepare for the
Data Science Fundamentals certification exam. It contains a detailed list of the topics
covered on the Professional exam, as well as a detailed list of preparation resources.
This study guide for the ISACA Data Science Fundamentals will help guide you through
the study process for your certification.
Data Science Fundamentals ISACA Data Science
Fundamentals Exam Summary
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Exam Name: ISACA Data Science Fundamentals
Exam Code: Data Science Fundamentals
Exam Price ISACA Member: $120 (USD)
Exam Price ISACA NonMember: $150 (USD)
Duration: 120 mins
Number of Questions: 60
Passing Score: 65%
Books / Training:
ISACA Data Science Fundamentals
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○ Data Science Fundamentals Online Course
○ Data Science Fundamentals Study Guide
● Schedule Exam: Exam Registration
● Sample Questions: ISACA Data Science Fundamentals Sample Questions
● Recommended Practice: ISACA Data Science Fundamentals Certification
Practice Exam
Exam Syllabus: Data Science Fundamentals ISACA Data
Science Fundamentals
Topic
Data Management
Data Science Process
Data Science Concepts
Weights
42%
33%
25%
ISACA Data Science Fundamentals Certification Sample
Questions and Answers
To make you familiar with ISACA Data Science Fundamentals (Data Science
Fundamentals) certification exam structure, we have prepared this sample question set.
We suggest you to try our Sample Questions for Data Science Fundamentals
Certification to test your understanding of ISACA Data Science Fundamentals process
with the real ISACA certification exam environment.
Data Science Fundamentals ISACA Data Science Fundamentals
Sample Questions:01. Which algorithms are typically used for unsupervised learning tasks?
(Choose Two)
a) Decision Trees
b) K-means Clustering
c) Support Vector Machines
d) Principal Component Analysis
02. Which scaling techniques are appropriate for preparing features in data
preprocessing?
(Choose Two)
a) Min-Max Scaling
b) One-Hot Encoding
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c) Standardization
d) Tokenization
03. In the context of data science, what is 'model validation'?
a) Documenting the steps involved in building the model
b) The process of ensuring a model operates within certain parameters
c) Testing a model on new data to check its performance
d) Integrating the model with existing databases
04. CRISP-DM stands for what in the context of a data science project?
a) Cross-Industry Standard Process for Data Management
b) Cross-Industry Standard Practice for Data Mining
c) Cross-Industry Standard Process for Data Mining
d) Cross-Industry Systematic Protocol for Data Management
05. Which of the following is a common method to ensure data security in
management practices?
a) Regular data audits
b) Frequent data duplication
c) Periodic system shutdowns
d) Reduced data access speeds
06. What type of machine learning algorithm would be best suited for creating a
system that suggests products based on customer buying history?
a) Unsupervised learning
b) Supervised learning
c) Reinforcement learning
d) Semi-supervised learning
07. What is the main purpose of data lifecycle management (DLM)?
a) To define processes for resolving data breaches
b) To manage data from creation to deletion
c) To increase data transparency only
d) To ensure data is never archived
08. What are the benefits of using ensemble methods in machine learning?
(Choose Three)
a) Reducing variance
b) Reducing bias
c) Improving prediction confidence
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d) Simplifying models
09. In data visualization, what does a 'heatmap' typically represent?
a) Geographical distributions
b) Trends over time
c) Relationships between two variables
d) Data density through variations in coloring
10. Which SQL statement is used to remove duplicates from a result set?
a) SELECT DISTINCT
b) REMOVE DUPLICATES
c) DELETE
d) DROP DUPLICATES
Answers:Answer 01:- b, d
Answer 02:- a, c
Answer 03:- c
Answer 04:- c
Answer 05:- a
Answer 06:- b
Answer 07:- b
Answer 08:- a, b, c
Answer 09:- d
Answer 10:- a
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