All Weeks The AI Ladder: A Framework for Deploying AI in your Enterprise Coursera Quiz Answers
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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.
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