Artificial Intelligence Foundation and Intermediate B2

Welcome to your Artificial Intelligence Foundation and Intermediate B2

Instructions

All 30 questions should be
All answers are to be marked on the question paper
You have 1 hour to complete this exam.

Name

DOB(dd/mm/yyyy)

What are the common steps when preparing for Machine Learning implementation?

Gather Data, Exploratory Data Analysis, Split-Train & Test, Select Best Model, Validate, Evaluate

Split-Train & Test, Exploratory Data Analysis, Select Best Model, Gather Data, Evaluate, Validate

Gather Data, Exploratory Data Analysis, Split-Train & Test, Select Best Model, Evaluate, Validate

Split-Train & Test, Gather Data, Select Best Model, Evaluate, Validate, Exploratory Data Analysis

None

Which of the following is a formalization of relationships between variables in the form of mathematical equations?

Deep Learning

Machine Learning

Statistical Analysis

Statistical Model

None

What is the difference between traditional programming and machine learning?

Traditional programming is based on permutations and combinations, whereas machine learning uses traditional analytics.

Traditional programming considers output of the program to generate code, whereas machine learning uses data and program to generate output.

Traditional programming uses software programs, whereas machine learning uses hardware solutions.

Traditional programming uses hard-coded rules to make decisions, whereas machine learning learns from data.

None

The below code will produce?

----------------------------
print(dataset.head(20))
----------------------------

Produce first 20 records

Produce last 20 records

Produce first 20 column

Produce last 20 column

None

Which of the following will be used to determine Accuracy?

TP & FP

TP & TN

TN & FP

FP & FN

None

To predict continuous values like the price of a house, which model is suitable to be used in machine learning?

Linear Regression

Decision tree

kNN

Classification

None

If you would like to start on a Machine Learning project what would be the most important aspect to think of?

The accuracy of the machine learning model

The Algorithm to be used for the model

Identification of the business goal

Data to be extracted for the machine learning model

The team to be involved in the development

None

What is ANI?

Artificial Narrow Intelligence

Artificial Neuro Intelligence

Artificial Naive Intelligence

Artificial Native Intelligence

None

What are some of the Machine Learning algorithms?

Decision trees, XGboost, Google Vision API

Random forests, regression (linear and logistic) but not kNN

Regression, decision trees, Naive Bayes, K-Means clustering

XGboost, Adaboost, regression except Naive Bayes

None

10.

A pizza chain wants to open its delivery centers across a city. Which of the model suited to perform the task?

Linear Regression

Decision tree

kNN

Statistical Classification

None

11.

Which of the below is used in Machine Learning?

A. Supervised

B. Unsupervised

Both A & B

None of the Above

None

12.

Which statement is not true when we use Anaconda Enterprise?

It is an end-to-end platform for data science.

It is FREE!

It allows us to document our investigations

It allows collaboration between parties.

We can deploy it for production

None

13.

The below code produce?

--------------------
pyplot.show()
--------------------

Show all the records

Show graph

Show logs

Show Python logs

None

14.

Train the Model is the first step of this type of machine learning. Identify the type.

Supervised Learning

Semi-supervised Learning

Unsupervised Learning

Reinforcement Learning

None

15.

What are the common tools that we would use for developing a Machine Learning algorithm?

Python

Matplotlib

Anaconda

Hadoop

Tensorflow

Javascript

None

16.

What is a library in Python?

Sets of available functions.

Sets of available AI solution.

Sets of available AI and ML solution.

Sets of available methods, functions.

None

17.

Robots are example that uses this type of machine learning. Identify the type.

Supervised Learning

Semi-supervised Learning

Reinforcement Learning

Unsupervised Learning

None

18.

How can AI enhance throughput and efficiency?

AI systems will be designed to monitor specific areas and situations.

Self-driving cars will have a combination of sensors, cameras, radar, and artificial intelligence technology.

AI platforms will provide real-time insights, combined with the explosion of computing power, to diagnose and treat patients.

Infusing telemedicine platforms with machine learning algorithms will mean better diagnoses with less human effort.

None

19.

Which of the following is more balanced than the arithmetic mean?

Precision

Sensitivity

Harmonic Mean

F1 Score

None

20.

What is the output of the below program?

def greeting(name):
print("Hello, + name)
greeting("Donser'z Abica Wizer")

Hello Donser'z Abica Wizer

Hello Donserz Abica Wizer

HelloDonser'z Abica Wizer

Error EOL

None

21.

How do Google, Amazon, and LinkedIn use artificial intelligence in their ecosystems?

Google, Amazon, and LinkedIn do not use artificial intelligence.

Google and LinkedIn use AI through their offerings, but Amazon does not use AI.

Google and Amazon use AI, and LinkedIn is in the process of incorporating AI.

Amazon uses AI in Alexa and AI Everywhere; Google uses AI in Vision API and Google Translate, whereas LinkedIn uses AI in the entire job application process.

None

22.

Which of the following is used in classification problems where the output can be of two or more types of classes?

Confusion Matrix

Accuracy

Precision

None

23.

Basic workflow in Machine Learning consist of

2 Layers

7 Layers

8 Layers

4 Layers

None

24.

Which Python modules are NOT used for Machine Learning?

Numpy

Pandas

Tensorflow

Scapy

Theano

Keras

None

25.

Which of the following is NOT an example of Artificial Narrow Intelligence?

Super-intelligent AI Agents

Spam Filter

AlphaGo

Google Translate

None

26.

Which of the following is domain-specific feature engineering?

Econometric, technological, agricultural, and sociological data engineering

Term Frequency-Inverse Document Frequency (TF-IDF): Text

Scale Invariant Feature Transform (SIFT): Images

Images, text, and audio data engineering

None

27.

Which of the following have computers traditionally done better than people?

A. Storing Information

B. Responding Flexibly

C. Computing Numerically

Both (A) and (C)

None

28.

Which of the following is not a performance measure, but acts as a base for almost all of the performance metrics?

Confusion Matrix

F1 Score

Specificity

Recall

None

29.

Which of the following is an example of a sharp question?

How can revenue be maximized?

What should you do?

Which career path should you take?

Which data can tell you about your business?

None

30.

Which of the following is a goal of the machine learning workflow?

Investigate a business challenge

Systematic arrangement of data for detailed analysis

Derive answers to business challenges

Determine if the data is acceptable for further investigation

None

1 out of 6

Time is Up!

Artificial Intelligence Foundation and Intermediate B2

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