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ITE303C (MOOC 1, 2, 3 AND MORE ANSWERS AND EXPLAINS ITE 2024

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ITE303C (MOOC 1, 2, 3 AND MORE ANSWERS AND EXPLAINS ITE 2024 ITE303C (MOOC 1, 2, 3 AND MORE ANSWERS AND EXPLAINS ITE 2024 ITE303C (MOOC 1, 2, 3 AND MORE ANSWERS AND EXPLAINS ITE 2024

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ITE303C (MOOC 1, 2, 3 AND
MORE ANSWERS AND
EXPLAINS ITE 2024
1. A process or set of rules to be followed in calculations or other problem-solving
operations, especially by a computer describes an

A. set of inputs
B. troubleshooting problem
C. algorithm
D. computer program: C. algorithm

An algorithm is defined as a process or set of rules to be followed in calculations or other
problem-solving operations, especially by a computer


2. To make this algorithm functional, which step would you add to step 4?
1. Scan to find the smallest number
2. Set to 0 in the index in the output array
3. Remove that number from the input array
4. __________________________________________

A. Divide the array by the index, print the array output
B. Repeat steps 1-3, but subtract the total from the numbers summated
C. Print output in the correct order
D. Repeat steps 1-3, but add 1 to the index number for each loop: D. Repeat steps 1-3, but
add 1 to the index number for each loop

Repeating the steps, but adding 1 to the index number will ensure that the new array will sort
the numbers in the correct order






,3. Take input, get output, use output on next input is an example of a learning algorithm
A. true
B. false: A. true

This is true, because a learning algorithm is able to use the output's "learnings" on the next input
to improve function performance
4. Learning algorithms require large datasets, which means storing identifying information
about users
A. true
B. false: A. true

This is true. One side effect of learning algorithms is that they require large amounts of data to
get better at what they do. This is usually a negative for users, which end up being victims of
having their data tracked


5. A _________ _________ in machine learning is the idea that the algorithm itself influences
the next set of inputs that go into the model. The main takeaway is that algorithms
sometimes have more influence than a user's initial input.

A. false dichotomy
B. feedback loop
C. learning algorithm
D. large dataset: B. feedback loop

A feedback loop in machine learning is the idea that the algorithm itself influences the next set
of inputs that go into the model. The main takeaway is that algorithms sometimes have more
influence than a user's initial input.


6. Are anonymous datasets truly anonymous?

A. No, due to lacking regulations
B. Yes, thanks to machine learning randomness algorithms
C. Yes, thanks to privacy regulations
D. No, due to combining data and re-identification: D. No, due to combining data and re-
identification




,Anonymized datasets assume that the dataset exists in a vacuum, and researchers don't
anticipate what the individual row characteristics will look like when combined with other
datasets
7. Which of the following best describes what an algorithm is?

A. a list of ingredients a computer uses to generate problems to solve
B. a type of computer that calculates problem-solving methods
C. a type of process a human uses to write down what steps need to happen to get a
problem solved
D. a recipe that a computer uses to solve problems: D. a recipe that a computer uses to solve
problems

An algorithm is a process or set of rules to be followed in calculations or other problem-solving
operations, especially by a computer.
8. An algorithm that takes an input, tries 10 different sorting techniques, and uses the best
fit on the next 100 inputs is best described as a

A. implicit algorithm
B. learning algorithm
C. data algorithm
D. explicit algorithm: B. learning algorithm

A learning algorithm is one that takes the initial calculation to get better at solving the
problem at hand, applying the data from the learned output to the next set of inputs
9. Which of these steps follows the most logical order for a low-to-high sorting algorithm?
A.
1. Scan to find the largest number
2. Set to 0 in the index in the output array
3. Remove that number from the input array
4. Repeat steps 1-3, but add 1 to the index number for each loopB.
1. Scan to find the smallest number
2. Set the length of the array in the index in the output array
3. Remove that number from the input
4. Repeat steps 1-3, but add 1 to the index number for each loopC.
1. Scan to find the smallest number
2. Set to 0 in the index in the output array



, 3. Remove that number from the input array
4. Repeat steps 1-3, but add 1 to the index number for each loopD.
1. Scan to find the smallest number
2. Set to 0 in the index in the output array
3. Remove that number from the input array: C.
1. Scan to find the smallest number
2. Set to 0 in the index in the output array
3. Remove that number from the input array
4. Repeat steps 1-3, but add 1 to the index number for each loop

The goal of a sorting algorithm is to find the smallest number each time, identifying it's place
in the output array (0, 1, 2, etc) and removing it from the input array 10. What's the difference
between a basic and learning algorithm?

A. A basic algorithm takes an input, while a learning algorithm takes an input and gets
an output
B. A basic algorithm takes an input, gets an output, while a learning algorithm takes
multiple inputs and gets multiple outputs
C. A basic algorithm takes an input and gets an output, while a learning algorithm takes
multiple inputs and gets multiple outputs
D. An basic algorithm takes an input and gets an output, while a learning algorithm
uses the output on the next input: D. An basic algorithm takes an input and gets an output,
while a learning algorithm uses the output on the next input

A basic algorithm takes an input, makes a calculation, and provides an output. A learning
algorithm uses the calculation to get better at solving the problem at hand, applying the data
from the learned output to the next set of inputs
11. Pseudocode can best be defined as

A. a middle ground between code and plain writing that can be fed into a computer
B. a type of Javascript that is both human and machine-readable
C. a Python library for machine learning
D. an explainable description of code that is meant for humans, not comput-ers: D. an
explainable description of code that is meant for humans, not computers

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