Google AI certification with Complete Solutions
1. A spreadsheet that calculates No (not AI) [The outcome is determined by
sums and other pre-defined the user-specified formula, no AI needed.]
functions on given data
2. Predicting the stock market Kind of/no/yes [Fitting a simple curve is not
by fitting a curve to past data really AI, but there are so many different
about stock prices curves to choose from, even if there's a lot
of data to constrain them, that one needs
machine learning/AI to get useful results.]
3. A GPS navigation system for Kind of/no/yes [the signal processing and
finding the fastest route geometry used to determine the coordinates
isn't AI, but providing good suggestions for
navigation (shortest/fastest routes) is AI, es-
pecially if variables such as traffic conditions
are taken into account.]
4. A music recommendation Yes [The system learns from the users' (not
system such as Spotify that only your) listening behavior.]
suggests music based on the
users' listening behavior
5. Big data storage solutions No [Storing and retrieving specific items from
that can store huge amounts a data collection is neither adaptive or au-
of data (such as images or tonomous.]
video) and stream them to
many users at the same time
6. Photo editing features such kind of & no [Adjustments such as color bal-
as brightness and contrast in ance, contrast, and so on, are neither adap-
applications such as Photo- tive nor autonomous, but the developers of
shop the application may use some AI to automat-
ically tune the filters.]
7. Style transfer filters in appli- Yes [Such methods typically learn image sta-
cations such as Prisma that tistics (read: what small patches of the image
take a photo and transform it in a certain style look like up close) and
into different art styles (im- transform the input photo so that its statistics
pressionist, cubist, ...) match the style, so the system is adaptive.]
, Google AI certification with Complete Solutions
8. Where would you put AI? (AI Section B
is a part of computer sci-
ence.)
9. Where would you put ma- Section C
chine learning? (Machine
learning is usually consid-
ered to be a part of AI)
10. Where would you put comput- Section A
er science? (Computer sci-
ence is a relatively broad field
that includes AI but also other
subfields such as distributed
computing, human-computer
interaction, and software en-
gineering.)
11. Where would you put data Section E
science? (Data science needs
computer science and AI.
However, it also involves a
lot of statistics, business,
law, and other application do-
mains, so it is usually not con-
sidered to be a part of com-
puter science.)
12. Where would you put deep Section D
learning? (Deep learning is a
part of machine learning.)
13. Autonomous car Autonomous cars apply a wide range of tech-
niques to function. These include statistics,
robotics, and machine learning.
14. Steering a rocket into orbit Robotics. (In order to steer a rocket into orbit
robotics are needed to fire the engines at the
right times and with the right power.)
1. A spreadsheet that calculates No (not AI) [The outcome is determined by
sums and other pre-defined the user-specified formula, no AI needed.]
functions on given data
2. Predicting the stock market Kind of/no/yes [Fitting a simple curve is not
by fitting a curve to past data really AI, but there are so many different
about stock prices curves to choose from, even if there's a lot
of data to constrain them, that one needs
machine learning/AI to get useful results.]
3. A GPS navigation system for Kind of/no/yes [the signal processing and
finding the fastest route geometry used to determine the coordinates
isn't AI, but providing good suggestions for
navigation (shortest/fastest routes) is AI, es-
pecially if variables such as traffic conditions
are taken into account.]
4. A music recommendation Yes [The system learns from the users' (not
system such as Spotify that only your) listening behavior.]
suggests music based on the
users' listening behavior
5. Big data storage solutions No [Storing and retrieving specific items from
that can store huge amounts a data collection is neither adaptive or au-
of data (such as images or tonomous.]
video) and stream them to
many users at the same time
6. Photo editing features such kind of & no [Adjustments such as color bal-
as brightness and contrast in ance, contrast, and so on, are neither adap-
applications such as Photo- tive nor autonomous, but the developers of
shop the application may use some AI to automat-
ically tune the filters.]
7. Style transfer filters in appli- Yes [Such methods typically learn image sta-
cations such as Prisma that tistics (read: what small patches of the image
take a photo and transform it in a certain style look like up close) and
into different art styles (im- transform the input photo so that its statistics
pressionist, cubist, ...) match the style, so the system is adaptive.]
, Google AI certification with Complete Solutions
8. Where would you put AI? (AI Section B
is a part of computer sci-
ence.)
9. Where would you put ma- Section C
chine learning? (Machine
learning is usually consid-
ered to be a part of AI)
10. Where would you put comput- Section A
er science? (Computer sci-
ence is a relatively broad field
that includes AI but also other
subfields such as distributed
computing, human-computer
interaction, and software en-
gineering.)
11. Where would you put data Section E
science? (Data science needs
computer science and AI.
However, it also involves a
lot of statistics, business,
law, and other application do-
mains, so it is usually not con-
sidered to be a part of com-
puter science.)
12. Where would you put deep Section D
learning? (Deep learning is a
part of machine learning.)
13. Autonomous car Autonomous cars apply a wide range of tech-
niques to function. These include statistics,
robotics, and machine learning.
14. Steering a rocket into orbit Robotics. (In order to steer a rocket into orbit
robotics are needed to fire the engines at the
right times and with the right power.)
