Introduction to Artificial Intelligence (AI) Coursera Quiz Answers

All Weeks Introduction to Artificial Intelligence (AI) Coursera Quiz Answers

In this course, you will learn what Artificial Intelligence (AI) is, explore use cases and applications of AI, understand AI concepts and terms like machine learning, deep learning, and neural networks. You will be exposed to various issues and concerns surrounding AI such as ethics and bias, & jobs, and get advice from experts about learning and starting a career in AI. You will also demonstrate AI in action with a mini-project.

This course does not require any programming or computer science expertise and is designed to introduce the basics of AI to anyone whether you have a technical background or not.

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Introduction to Artificial Intelligence (AI) Week 01 Quiz Answers

Graded: What is AI? Applications and Examples of AI

Q1. Which of the following is NOT a good way to define AI?

  • AI is all about machines replacing human intelligence.
  • AI is the application of computing to solve problems in an intelligent way using algorithms.
  • AI is Augmented Intelligence and is not intended to replace human intelligence rather extend human capabilities
  • AI is the use of algorithms that enable computers to find patterns without humans having to hard code them manually

Q2. Which of the following is an attribute of Strong or Generalized AI?

  • Cannot teach itself new strategies
  • Operate with human-level consciousness
  • Perform independent tasks
  • Can perform specific tasks, but cannot learn new ones

Q3. AI is the fusion of many fields of study. Which of these fields, along with Computer Science, plays a role in the application of AI?

  • Mathematics
  • Philosophy
  • Statistics
  • All responses are correct

Q4. Which of these is NOT a current application of AI?

  • Making precise patient diagnosis and prescribing independent treatment
  • Collaborative Robots helping humans lift heavy containers
  • Classifying rock samples to identify best places to drill for oil
  • Self-Driving vehicles utilizing Computer Vision to navigate around objects

Q5. Natural Language AI algorithms that learn by example are the reason we can talk to machines and they can talk back to us.

  • True
  • False

Q6. Advances in the field of Computer Vision make which of the following possible?

  • Detecting cancerous moles in skin images
  • Real-time transcription
  • On-demand online tutors
  • Detecting fraudulent transactions

Q7. Which of these is currently NOT an application of Collaborative Robots or Cobots?

  • Robots helping move items on shelves for stocking purposes
  • Robots assisting or replacing humans in jobs that may be dull, dangerous, ineffective or inefficient when done by humans
  • Robots helping humans lift heavy containers
  • Personal use in the home such as doing the laundry and cooking for example

Q8. Which of the following aspects involved in converting the stethoscope into a digital device to support patient diagnoses involves the use of AI?

  • Graphing heart beat data on the mobile device allowing a physician to spot trends
  • Sending digital signals to a mobile device with a machine learning app via bluetooth
  • Inserting a digitizer into the stethoscope tube to convert the analog sound of the heart beat into a digital signal
  • An app on the mobile device that applies learnings from previous diagnosis data to assist the physicians in their current diagnoses

Q9. Which of the following are applications of Artificial Intelligence in action?

A. IBM Watson utilizing its information retrieval capabilities to provide technical information to oil and gas company workers.

B. Watson analyzing Grammy nominated song lyrics over a 60-year period and categorizing them based on their emotions.

C. Assisting patients with neurological damage by detecting patterns in massive movement related datasets and using robots to trigger specific movements in the human body to create new neural pathways in the brain.

D. Law enforcement authorities using facial recognition algorithms to identify suspects in multiple streams of video footage

  • Only options A, B, and C are correct
  • None of the options are correct
  • Only option A is correct
  • All of the options are correct

Introduction to Artificial Intelligence (AI) Week 02 Quiz Answers

Graded: AI Concepts, Terminology, and Application Areas

Q1. Which of these statements is true?

  • Cognitive systems can only process neatly organized structured data
  • Cognitive systems can learn from their successes and failures
  • Cognitive systems can derive mathematically precise answers following a rigid decision tree approach
  • Cognitive systems can only translate small volumes of audio data into their literal text translations at massive speeds

Q2. Which of these statements is true?

  • AI is the subset of Data Science that uses Deep Learning algorithms on structured big data
  • Data Science is a subset of AI that uses machine learning algorithms to extract meaning and draw inferences from data
  • Artificial Intelligence and Machine Learning refer to the same thing since both the terms are often used interchangeably
  • Deep Learning is a specialized subset of Machine Learning that uses layered neural networks to simulate human decision-making

Q3. Which of the following is NOT an attribute of Machine Learning?

  • Takes data and rules as input and uses these inputs to develop an algorithm that will give us an answer
  • Machine Learning models can be continuously trained
  • Takes data and answers as input and uses these inputs to create a set of rules that determine what the Machine Learning model will be
  • Machine Learning defines behavioral rules by comparing large data sets to find common patterns

Q4. Which of the following is NOT an attribute of Unsupervised Learning?

  • It is useful for clustering data, where data is grouped according to how similar it is to its neighbors and dissimilar to everything else
  • Takes data and rules as input and uses these inputs to develop an algorithm that will give us an answer
  • The algorithm ingests unlabeled data, draws inferences, and finds patterns from unstructured data
  • It is useful for finding hidden patterns and or groupings in data and can be used to differentiate normal behavior with outliers such as fraudulent activity

Q5. Which of the following is an attribute of Supervised Learning?

  • Relies on providing the machine learning algorithm unlabeled data and letting the machine infer qualities
  • Relies on providing the machine learning algorithm with a set of rules and constraints and letting it learn how to achieve its goals
  • Relies on providing the machine learning algorithm human-labeled data – the more samples you provide, the more precise the algorithm becomes in classifying new data
  • Tries its best to maximize its rewards by trying different combinations of allowed actions within the provided constraints

Q6. Which of the following statements about datasets used in Machine Learning is NOT true?

  • Testing data is data the model has never seen before and is used to evaluate how good the model is
  • Training data is used to fine-tune algorithm’s parameters and evaluate how good the model is
  • Validation data subset is used to validate results and fine-tune the algorithm’s parameters
  • Training subset is the data used to train the algorithm

Q7. When creating deep learning algorithms, developers configure the number of layers and the type of functions that connect the outputs of each layer to the inputs of the next.

  • True
  • False

Q8. Which of the following fields of application for AI can be used at the airport to flag weapons within luggage passing through the X-ray scanner?

  • Natural Language
  • Chatbots
  • Speech
  • Computer Vision

Q9. Which of these activities is not required in order for a neural network to synthesize human voice?

  • Ingest numerous samples of a person’s voice until it can tell whether a new voice sample belongs to the same person
  • Generate audio data and run it through the network to see if it validates it as belonging to the subject
  • Deconstruct sentences to decipher the context of use
  • Continue to correct the sample and run it through the classifier, repetitively, till an accurate voice sample is created

Q10. Which one of these ways is NOT how AI learns?

  • Supervised Learning
  • Unsupervised Learning
  • Reinforcement Learning
  • Proactive Learning

Introduction to Artificial Intelligence (AI) Week 03 Quiz Answers

Graded: AI Issues, Ethics and Bias

Q1. Ethics in artificial intelligence is:

  • Something that is not an issue.
  • Something that somebody else is going to do in the future.
  • Something that we need to apply today.
  • Something that is entirely solved in current AI systems.

Q2. One approach that helps developers avoid unintentionally creating bias in AI systems is:

  • Using a wide variety of appropriately diverse data for training.
  • Using highly specific training data from a narrow range.
  • Not using any training data.
  • None of the above.

Q3. Which of the following statements about IBM’s views on AI are correct?

  • Data and insights belong to the people and businesses who created them. Organizations that collect, store, manage, or process data have an obligation to handle it responsibly.
  • Knowing how an AI system arrives at an outcome is key to trust. To improve transparency, we should define how we build, deploy, and manage AI systems through scientific research.
  • Unbiased models and a spirit of diversity and inclusion are necessary to create fair AI systems, which can mitigate, rather than magnify, our existing prejudices.
  • AI can be applied to solve some of humanity’s most pervasive problems and create opportunity for all.
  • All of the above.

Q4. Which of the following are examples of bias in an AI system?

  • Customers not being aware that they are interacting with a chatbot on a company website.
  • Facial recognition systems performing well for individuals of all skin tones.
  • AI systems in call centers providing context sensitive assistance to staff.
  • Image recognition systems associating images of kitchens, shops, and laundry with women rather than men.

Q5. There is concern that some jobs will be replaced by AI systems. Which of the following characteristics make a job a good candidate for replacement?

  • Requires innovative problem solving.
  • Rules-based decision-making.
  • Has very varied, unpredictable tasks.
  • Features highly creative tasks.

Q6. Ethical concerns with AI systems are:

  • Not genuinely troubling, and the concern of very few AI experts.
  • Short term and easily addressed when developing new AI systems.
  • Something that should be the concern of every AI developer, so they can be mitigated for as AI systems are developed.
  • Something that can’t be mitigated for.

Q7. What are some of the ethical concerns around artificial intelligence?

A. Racial, gender or other types of bias.

B. Loss of jobs due to AI replacing workers performing repetitive tasks.

C. Concern about the trustworthiness of decision-making supported by AI systems.

D. Privacy, for example, as human faces are photographed and recognized in public spaces.

  • None of the options are correct
  • All of the options are correct
  • Only options A and B are correct
  • Only options A, B, and D are correct

Q8. Which of the following NOT a way AI is being used to benefit humanity?

  • In healthcare, AI is being used to interpret scans for early detection of cancer, eye disease, and other problems.
  • Crime: to identify criminals before they commit a crime.
  • In healthcare, AI is being used to predict where the next outbreak of a disease will occur.
  • In agriculture, AI is being used to identify and recommend treatment for plant diseases.

Q9. How many new opportunities and job roles does the World Economic Forum expect that AI will create in the next few years?

  • 7 million
  • 165 million
  • 48 million
  • 133 million

Q10. What is a significant way in which developers of AI systems can guard against introducing bias?

  • Using only examples from their own environment as training data.
  • Providing effective training data and performing regular tests and audits.
  • Using less varied AI systems and datasets.
  • Using government approved algorithms.
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2 Comments

  1. Week 2 question 3 answer given by your website is wrong the right answer is “Takes data and rules as input and uses it to develop algo……”

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