AI For Everyone Answers Week 1 | Coursera

DeepLearning.AI: AI For Everyone Week 1 Quiz Answer

About the course:

AI for Everyone is an insightful and comprehensive online course developed by DeepLearning.AI in collaboration with Coursera. This course provides learners with a holistic understanding of artificial intelligence (AI) and its impact on various industries. Designed for individuals with non-technical backgrounds, this course equips learners with the knowledge necessary to navigate the AI landscape effectively.

Throughout the course, learners will engage with engaging video lectures, hands-on exercises, and interactive quizzes to develop a solid foundation in AI concepts. They will gain a practical understanding of AI technologies, including machine learning, deep learning, and neural networks. By exploring real-world case studies and industry applications, participants will discover the transformative potential of AI in domains such as healthcare, finance, marketing, and more.

Key Learning Objectives:

• Understand AI Fundamentals: Gain a clear understanding of AI, its core principles, and its relevance in today's world.
• Explore AI Technologies: Learn about machine learning algorithms, neural networks, and deep learning architectures, and understand how these technologies power AI applications.
• Discover Real-World AI Applications: Explore diverse industries where AI is making a significant impact, including healthcare, finance, customer service, and transportation.
• Ethical and Social Considerations: Explore the ethical challenges and implications of AI, such as bias, fairness, privacy, and accountability, and learn strategies to address them responsibly.
• Foster AI Literacy: Develop the ability to speak and engage in discussions about AI, understand AI-related terminology, and make informed decisions regarding AI implementation.

Course Structure:

AI for Everyone is a self-paced course, allowing learners to progress at their own speed. The course consists of high-quality video lectures delivered by industry experts, practical exercises, and quizzes to reinforce learning. Additionally, learners will have the opportunity to connect and collaborate with a global community of AI enthusiasts, enabling valuable discussions and peer-to-peer learning.

Completion of the course provides learners with a certificate, highlighting their newfound AI knowledge and skills. Whether you are a business professional, manager, policymaker, or simply curious about AI, AI for Everyone is the perfect starting point to unlock the potential of artificial intelligence in today's rapidly evolving world.

Question 1)

Which of these terms best describes the type of AI used in today’s email spam filters, speech recognition, and other specific applications?

•  Artificial General Intelligence (AGI)
•  Artificial Narrow Intelligence (ANI)

Question 2)

What do you call the commonly used AI technology for learning input (A) to output (B) mappings?

• Unsupervised learning
• Supervised learning
• Reinforcement learning
• Artificial General Intelligence

Question 3)

You want to use supervised learning to build a speech recognition system. The figure above suggests that in order for a neural network (deep learning) to achieve the best performance, you would ideally use: (Select all that apply)

You want to use supervised learning to build a speech recognition system. The figure above suggests that in order for a neural network (deep learning) to achieve the best performance, you would ideally use: (Select all that apply)

•  A large neural network
• A small neural network
•  A large dataset (of audio files and the corresponding text transcript)
•  A small dataset (of audio files and the corresponding text transcript)

Question 4)

The only way to acquire data for a supervised learning algorithm is to manually label it. I.e., given the input A, to ask a human to provide B.

• True
• False

Question 5)

Which of these statements regarding data acquisition do you agree with?

• It doesn’t matter how data is acquired. The more data, the better.
• Only structured data is valuable; AI cannot process unstructured data.
• Some types of data are more valuable than others; working with an AI team can help you figure out what data to acquire.
• It doesn’t help to give data to an AI team, because they can always produce whatever they need by themselves.

Question 6)

You run a company that manufactures scooters. Which of the following are examples of unstructured data? (Select all that apply.)

• Pictures of your scooters
• The maximum speed of each of your scooters
• Audio files of the engine sound of your scooter
• The number of scooters sold per week over the past year

Question 7)

Suppose you run a website that sells cat food. Which of these might be a good result from a Data Science project? (Select all that apply.)

• A large dataset of images labeled as “Cat” and “Not Cat”
• A neural network that closely mimics how cats’ brains work.
• Insights into how to market cat food more effectively, depending on the breed of cat.
• A slide deck presenting a plan on how to modify pricing in order to improve sales.

Question 8)

Based on the terminology defined in Video 4, which of the following statements do you agree with? (Select all that apply.)

• The terms “Machine learning” and “data science” are used almost interchangeably.
• AI is a type of deep learning. (I.e., all AI algorithms are deep learning algorithms.)
• The terms “Deep learning” and “neural network” are used almost interchangeably.
• Deep learning is a type of machine learning. (I.e., all deep learning algorithms are machine learning algorithms.)

Question 9)

Which of these do AI companies do well?

• Strategic data acquisition
• Spot automation opportunities
• Invest in unified data warehouses
• All of the above

Question 10)

Say you want to input a picture of a person’s face (A), and output whether or not they are smiling (B). Because this is a task that most humans can do in less than 1 second, supervised learning can probably learn this A-to-B mapping.

• True
• False

Conclusion

 

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