ITM - Final Exam Review UPDATED ACTUAL Questions and
CORRECT Answers
Weak AI Analyzes large amounts of data
Can be trained to solve specific problems
Strong AI Used to describe a certain mindset of AI development
Self-aware consciousness with ability to solve problems, learn, and plan for the
future
Expert Systems Attempt to mimic human experts by applying expertise in a specific domain
AI Hierarchy 1. AI
2. Machine Learning
3. Neural Networks
4. Deep Learning
Machine Learning Operate by building a model from example inputs in order to make data-driven
predictions or decisions
Ability to perform new, unseen tasks, built on known properties learned from
training or historical data that are labelled
Neural Networks Virtual neurons that work in parallel to simulate the way the human brain works
Assigns numerical values, or weights, to connections between the neurons
Neural Networks: Image Processing Each layer of the neural network manages a different level of abstraction
Deep Learning System discovers new patterns without being exposed to labelled data on input
inter-relations (eg. image recognition, CHATGPT)
Information Systems Set of interrelated components that collect, process, store, and distribute
information to support decision making and control in an organization
Organizational Roles: Direct User The users that interact directly with the existing IS
Organizational Roles: Indirect User Users who depend on the results of direct users' interactions with existing IS
Organizational Roles: Designer Individuals who design, implement, test, and maintain IS
Low-Code Collection of tools that provides visual, drag-and-drop interfaces so one can
build apps by connecting pre-built components
Citizen Developers Individuals with little to no coding experience - to build and deploy custom
business applications
, 4 Strategies to Organize Spreadsheets 1. Clearly state inputs and assumptions
2. Separate model inputs from analysis/outputs
- use referencing - do not hard-code
3. Perform analysis in easy-to-debug steps
4. Design model layout to enable understanding
- Name cells (start with letter, ___ , or \ (no spaces)
4 Elements of a Pivot Table Values, Row, Columns, Filters (optional)
Goal Seek Used when we know what the output of a calculation is and we want to know how
to arrive at that output by changing particular inputs
Data Tables Used when we want to change one or two inputs to see what the outputs would
be
=UNIQUE( ___ ) =UNIQUE(array)
*Returns a list of unique entries from a range or array
=SUM( ___ , [___] , [____] ) =SUM(number 1, [number 2], [number 3])
*Adds numbers in a range of cells
=PRODUCT( ____ , [____] , [____] ) =PRODUCT(number 1, [number 2], [number 3])
*Multiplies all the numbers provided as arguments and returns the product
=SQRT( ______________ ) =SQRT(number)
*Calculates the square root of a positive number
=EXP( ______________ ) =EXP(number)
*Calculates the value of e raised to a specified power
=LN( ______________ ) =LN(number)
*Calculates the natural logarithm of a number
=SUMPRODUCT( ______ , ______ ) =SUMPRODUCT(array 1, array 2)
*Multiplies corresponding components in given arrays and returns the sum of
those products
=ROUND( ______ , ______ ) =ROUND(number, num_digits)
*Rounds a number to a specified number of digits using standard rounding rules
CORRECT Answers
Weak AI Analyzes large amounts of data
Can be trained to solve specific problems
Strong AI Used to describe a certain mindset of AI development
Self-aware consciousness with ability to solve problems, learn, and plan for the
future
Expert Systems Attempt to mimic human experts by applying expertise in a specific domain
AI Hierarchy 1. AI
2. Machine Learning
3. Neural Networks
4. Deep Learning
Machine Learning Operate by building a model from example inputs in order to make data-driven
predictions or decisions
Ability to perform new, unseen tasks, built on known properties learned from
training or historical data that are labelled
Neural Networks Virtual neurons that work in parallel to simulate the way the human brain works
Assigns numerical values, or weights, to connections between the neurons
Neural Networks: Image Processing Each layer of the neural network manages a different level of abstraction
Deep Learning System discovers new patterns without being exposed to labelled data on input
inter-relations (eg. image recognition, CHATGPT)
Information Systems Set of interrelated components that collect, process, store, and distribute
information to support decision making and control in an organization
Organizational Roles: Direct User The users that interact directly with the existing IS
Organizational Roles: Indirect User Users who depend on the results of direct users' interactions with existing IS
Organizational Roles: Designer Individuals who design, implement, test, and maintain IS
Low-Code Collection of tools that provides visual, drag-and-drop interfaces so one can
build apps by connecting pre-built components
Citizen Developers Individuals with little to no coding experience - to build and deploy custom
business applications
, 4 Strategies to Organize Spreadsheets 1. Clearly state inputs and assumptions
2. Separate model inputs from analysis/outputs
- use referencing - do not hard-code
3. Perform analysis in easy-to-debug steps
4. Design model layout to enable understanding
- Name cells (start with letter, ___ , or \ (no spaces)
4 Elements of a Pivot Table Values, Row, Columns, Filters (optional)
Goal Seek Used when we know what the output of a calculation is and we want to know how
to arrive at that output by changing particular inputs
Data Tables Used when we want to change one or two inputs to see what the outputs would
be
=UNIQUE( ___ ) =UNIQUE(array)
*Returns a list of unique entries from a range or array
=SUM( ___ , [___] , [____] ) =SUM(number 1, [number 2], [number 3])
*Adds numbers in a range of cells
=PRODUCT( ____ , [____] , [____] ) =PRODUCT(number 1, [number 2], [number 3])
*Multiplies all the numbers provided as arguments and returns the product
=SQRT( ______________ ) =SQRT(number)
*Calculates the square root of a positive number
=EXP( ______________ ) =EXP(number)
*Calculates the value of e raised to a specified power
=LN( ______________ ) =LN(number)
*Calculates the natural logarithm of a number
=SUMPRODUCT( ______ , ______ ) =SUMPRODUCT(array 1, array 2)
*Multiplies corresponding components in given arrays and returns the sum of
those products
=ROUND( ______ , ______ ) =ROUND(number, num_digits)
*Rounds a number to a specified number of digits using standard rounding rules
