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Introduction to AI and Data Analytics QUESTIONS AND CORRECT ANSWERS,

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Introduction to AI and Data Analytics QUESTIONS AND CORRECT ANSWERS .pdf Introduction to AI and Data Analytics QUESTIONS AND CORRECT ANSWERS .pdf

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Data Analysis
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Uploaded on
December 23, 2025
Number of pages
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Written in
2025/2026
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Introduction to AI and Data Analytics
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Order the terms below according to the chronology of 1. Decision Support Systems
their development and prominence in the marketplace, 2. Enterprise Resource Planning (ERP) and Relational Databases
beginning with Decision Support Systems in the 1970s. 3. Business Intelligence and Software-as-a-Service (SaaS)
4. Cloud Computing and Big Data
5. AI, Deep Learning, Internet of Things (IoT)


The process of computer-assisted decision-making Implement the solution in case of success or failure.
includes all the following steps EXCEPT:


The case about people complaining about long elevator installing mirrors on elevator doors to divert attention and help people pass the
wait time was resolved by ... time.


The architecture of business intelligence (BI) software self-optimizing automation algorithms.
includes all the following elements EXCEPT:


The difference between OLAP and OLTP is analytical vs. True
transactional data processing.


Descriptive analytics seek to answer which questions? What happened? What is happening?


What are the questions that predictive analytics seek to What will happen? Why will it happen?
answer?


Analytics applications in the retail value chain can only be False
implemented at the beginning of the process (with the
vendors) and at the end (with the customers).


All the following statements are AI myths EXCEPT: AI is not the same as a robot.


All the following are good rules for AI usage EXCEPT: Using AI puts you above the law.

, For the purposes of this class, machine learning, deep True
learning, and neural networks refer to the same set of
algorithms that enable AI systems to self-optimize.


Drivers of AI include all the following EXCEPT: The rising cost of AI applications and system training.


Limitations of AI machines include all the following They can think for themselves and better than their designers.
EXCEPT:


Open AI and the EU's Human Brain Project are on the False
cusp of designing and building an artificial human brain
that will have "general artificial intelligence."


Augmented intelligence refers best to AI systems that... Combine with human workers and extend their abilities.


The Turing Test measures... a machine's ability to exhibit intelligent behavior to or indistinguishable from a
human's.


Cognitive computing is a discipline and technology False
related to AI but operates at a higher level of accuracy,
speed, and responsibility compared to AI.


Select the 5 main functions of AI: 1. Content generation
2. Data transfer
3. Image/object/item "recognition"/tagging
4. Predictive analytics
5. Natural language processing (NLP)


In which one of the following areas has AI proved to be Market, advertising, and CRM
most profitable?


There are no really effective applications for AI tech in False
agriculture at this time.


What is the best definition of data? Digitized raw material, structured or unstructured, for analytical systems.


Match the examples of data below with their - Entries for race, sex/gender, etc: structured, categorical, nominal
classifications. - Entries for temperature: structured, numerical, interval
- Entries for household income description, 1) low, 2) med, 3) high: structured,
categorical, ordinal
- Image, audio, video files: unstructured, multimedia


Put the steps of data preprocessing in correct order: 1. Data consolidation (collect, select, integrate)
2. Data cleaning (impute missing values, reduce noise, remove duplicates)
3. Data transformation (reduce dimension and volume, balance data)
4. Data reduction


Skewness and kurtosis measure the distribution of data as True
depicted in a graphical curve, skewness the asymmetry of
the curve, and kurtosis its height/shape/skinny-ness.

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