All Weeks The AI Ladder: A Framework for Deploying AI in your Enterprise Coursera Quiz Answers
Table of Contents
The AI Ladder: A Framework for Deploying AI in your Enterprise Coursera Quiz Answers
Quiz 01 : Introduction to the AI Ladder and Fundamentals of AI
Q1. Which of the following is the best definition for the business function(s) of AI?
- AI provides businesses with enhanced means for predictions, automations, and optimizations.
- AI is a set of tools aimed at understanding and bringing value to an organization’s data.
- AI improves business decisions by leveraging data.
- AI improves customer service, business operations and IT functions.
Q2. What is the main purpose of the metaphorical “ladder” in the AI Ladder?
- To represent that achieving AI competency is a process of several evolutionary steps
- To represent the fact that most AI models are offered in a “ladder” format for businesses
- To represent that achieving AI competency is like climbing to technological supremacy
- To emphasize the fact that adopting AI is a dangerous endeavor
Q3. Which of the following is/are true about neural networks? (Select all that apply)
- Among machine learning algorithms, they are known to perform especially well with very large amounts of data.
- They aim to emulate how neurons function and communicate in the human brain.
- They are most closely associated with the subfield of machine learning known as deep learning.
- They can only be used with visual data, such as images or videos.
Quiz 02: No AI Without IA
Q1. Which of the following are advantages of holding data in a hybrid, multicloud environment? (Select all that apply)
- Data stored in hybrid, multicloud environments can be stored and used across any cloud type (public, private, on-premises, etc.) using containers.
- Data stored in hybrid, multicloud environments can be accessed across an organization without the need for specific hardware or on-premises connective architecture.
- Data stored in hybrid, multicloud environments is always automatically structured such that it is ready for training in AI models with no additional processing.
- Data stored in hybrid, multicloud environments is protected from failures, damages, or infiltration in on-premises hardware.
Q2. True or False: Only data stored with IBM platforms and software can be used to train AI models with IBM Watson.
- True
- False
Quiz 03: Collect Data
Q1. True or False: The Collect Data stage of the AI ladder involves only the collection of historical data (and not real-time or live-streaming data.
- True
- False
Q2. Which of the following are examples of data that can be collected for use in AI model building? (Select all that apply)
- Raw text written in customers’ reviews
- Images taken by maintenance employees
- Website metadata pertaining to how users behave on the site
- Audio files of recorded conversations between representatives and customers
Q3. An effective data management strategy ensures all of the following EXCEPT ___________
- Access to a wide variety of data in AI model-building, regardless of their sources or types
- Flexibility to support changing workloads and consumption cases
- Access to insights across business areas and user types to drive better decision-making
- Certainty that all of the managed data will be useful for AI model-building
Quiz 04: Organize Data
Q1. All of the following are objectives of the Organize stage of the AI Ladder EXCEPT ____________
- To profile, cleanse, and catalog all types of data
- To enable policy-driven visibility, detection, and reporting
- To deploy AI models in production environments
- To manage data with built-in protection and compliance
Q2. Which of the following statements about the Organize stage of the AI Ladder are true? (Select all that apply)
- Data is said to be “business-ready” when it provides valuable business insights.
- Organizing and cataloging data ensures that only permissioned users have access.
- Data is said to be “business-ready” when it has been cleansed, processed, and meets relevant standards of compliance.
Q3. Correctly used, governance can become an enabler for businesses.
- True
- False
Quiz 05: Analyze Data
Q1. Which of the following capabilities is NOT part of the AI life cycle described in the Analyze phase?
- To build models that can be used for prediction
- To put AI models into production within an application or a business process
- To manage the production environment to track who changed the mode, when the model was deployed, and the lineage on the model
- To profile and cleanse all the available data
Q2. An AI model is generally referred to as “transparent” if _______. (Select all that apply)
- The time it takes to train the model is known before it is built.
- The decision that the AI model makes or recommends is a binary “Yes” or “No.”
- The steps taken by an AI model in arriving at a decision or recommendation can be explained by human analysts.
- All the data the model uses in making a decision or recommendation is identifiable and retrievable.
Quiz 06: Infuse AI
Q1. Which of the following would fall under the Infuse stage of the AI Ladder? (Hint: read the answer selections closely)
- How organizations operationalize AI throughout their businesses
- How organizations deploy their AI models across their different business lines
- How organizations develop their employees’ skills in Data Science
- How organizations promote the importance of AI throughout their different business areas
- All the above
Q2. True or False: The Infuse step of the AI Ladder focuses on operationalizing AI across a company’s departments and areas, as opposed to the actual building of AI models
- True
- False
Q3. The Infuse step of the AI Ladder includes all of the following EXCEPT _________
- Training workers to use AI models in conjunction with their existing workflows
- Continuously seeking new areas where existing AI models—or new ones that could be built–can bring value to a companies
- Replacing humans altogether in strategic decision-making
- Operationalizing AI across multiple departments and business areas
Quiz 07: Introduction to AI and the AI Ladder
Q1. Which of these statements is True about AI?
- The primary application for AI is replacing low skilled employees and improving overall productivity.
- AI only focuses on improving leaders’ decisions making.
- AI mainly focuses on improving human decisions by predicting the future evolution of the business.
- AI is a tool for improving human decision making, at speed and scale.
Q2. What are the four rungs of the AI Ladder?
- Collect > Organize > Visualize > Infuse
- Collect > Analyze > Scale > Infuse
- Collect > Organize > Analyze > Infuse
- Organize > Visualize > Analyze > Deploy
Q3. What are some ways AI can improve business outcomes?
- Forecast what is going to happen in the business, at both the macro and micro level
- Automating critical, yet time-consuming, business processes that are often done manually, so employees are free to focus on higher-value, more creative work
- Optimizing routing and logistics, marketing spends, or the configuration of the cloud installation
- All of the above
Q4. Which of the following is/are example(s) of challenges that companies face while adopting AI?
- Getting handle on their data.
- Lack of relevant skills.
- Culture and business model change.
- All of the above.
Q5. In the phrase “No AI without IA,” IA stands for _
- IBM Analytics
- Information Architecture
- Intelligent Applications
- Information Amplification
Q6. How is the term “Modernize” defined in the context of AI adoption?
- Investing in a state-of-the-art data center that provides flexibility and efficiency to data management
- Modernizing IT by updating their technology to recent open source technologies
- Building an information architecture for AI that provides choice and flexibility across the organization
- Automating the generation of data insights
Q7. What is the main purpose of the Collect phase of the AI ladder?
- Accessing all the available data regardless of their sources or types and giving access to insight across the entire organization
- Reorganizing the data of the organization to prevent future information loss
- Identifying new data sources that could be useful and incorporating them in the data lake
- Easing the access to data for the data scientists
Q8. Which of the following represents the correct order of the data organization process described in the AI Ladder?
- Address Data Quality > Organize and Catalog Data > Govern Data
- Govern Data > Address Data Quality > Organize and Catalog Data
- Govern Data > Organize and Catalog Data > Address Data Quality
- Organize and Catalog Data > Address Data Quality > Govern Data
Q9. Which of the following are ways companies can organize their data into trusted, business-ready analytics foundations?
- By focusing on data preparation and quality
- By storing and governing information within a data lake
- By ensuring data privacy and regulatory compliance
- All of the above
Q10. True or False. The Analyze rung of the AI Ladder involves using data for analytics and insights to drive decision-making, but not AI model-building
- True
- False
Q11. What is the main objective of model management in the Analyze stage of the AI Ladder?
- To ensure that a model is transparent and free of bias while monitoring its performance
- To identify other business applications where the model could be deployed
- To ensure that the model is being used
- To ensure the model brings value to the business
Q12. True or False. The ultimate goal of the Infuse step in the AI Ladder is to replace a company’s existing decision-making processes with automated systems
- True
- False
Q13. Which of the following are ways that AI is transforming core business domains?
- Increasing customer satisfaction and reducing agent attrition, while cutting costs and allowing agents to focus on higher value transactions
- Keeping pace with regulatory requirements and managing risk.
- Changing the way clients think about supply chain management and logistics.
- All of the above.
Q14. Which of the following statements about model management are true? (Select all that apply)
- Organizations need to manage their AI across the entire AI life cycle in order to explain either to a consumer or another business how their systems came to a decision and why.
- Businesses need to trust their AI before they fully scale and automate across their organization.
- Model transparency is mostly important for insurance companies and financial institutions.
Q15. Which of the following statements is/are TRUE about hybrid, multicloud platforms? (Select all that apply)
- Hybrid, multicloud platforms will imply more “assembly required” in expanding the impact of AI across the organization.
- Hybrid, multicloud platforms facilitate the automation of AI life cycles across an array of contributors through collaborative workflows.
- Hybrid, multicloud platforms allow organizations to take advantage of their data and applications across any cloud (public, private, on-premises) via containers.
Get All Course Quiz Answers of IBM AI Foundations for Business Specialization
Introduction to Artificial Intelligence (AI) Coursera Quiz Answers
What is Data Science? Coursera Quiz Answers
The AI Ladder: A Framework for Deploying AI in your Enterprise Quiz Answers