Innovating with Google Cloud Artificial Intelligence

Innovating with Google Cloud Artificial Intelligence

Introduce

Artificial intelligence (AI) and machine learning (ML) represent an important evolution in information technologies that are quickly transforming a wide range of industries. “Innovating with Google Cloud Artificial Intelligence” explores how organizations can use AI and ML to transform their business processes.

Part of the Cloud Digital Leader learning path, this course aims to help individuals grow in their role and build the future of their business.

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AI and ML Fundamentals

  1. How do data analytics and business intelligence differ from AI and ML?

    • Data analytics and business intelligence are used only in small businesses, whereas AI and ML are used exclusively by large corporations.

    • Data analytics and business intelligence identify trends from historical data, whereas AI and ML use data to make decisions for future business.

    • Data analytics and business intelligence use automated decision-making processes, whereas AI and ML require human intervention and interpretation of data.

    • Data analytics and business intelligence involve advanced algorithms for predicting future trends, whereas AI and ML focus on processing historical data.

  2. Google applies generative AI to products like Google Workspace, but what is generative AI?

    • A type of artificial intelligence that can produce new content, including text, images, audio, and synthetic data.

    • A type of artificial intelligence that can understand and respond to human emotions.

    • A type of artificial intelligence that can create and sustain its own consciousness.

    • A type of artificial intelligence that can make decisions and take actions.

  3. Which dimension for measuring data quality means that the data conforms to a set of predefined standards and definitions such as type and format?

    • Validity

    • Uniqueness

    • Accuracy

    • Consistency

  4. Which option refers to the use of technologies to build machines and computers that can mimic cognitive functions associated with human intelligence?

    • Artificial intelligence

    • Machine learning

    • Natural language processing

    • Deep learning

  5. What does the consistency dimension refer to when data quality is being measured?

    • Whether a dataset is free from duplicate values that could prevent an ML model from learning accurately.

    • Whether the data is uniform and doesn’t contain any contradictory information.

    • Whether all the required information is present.

    • Whether the data is up-to-date and reflects the current state of the phenomenon that is being modeled.

  6. Google's AI principles are a set of guiding values that help develop and use artificial intelligence responsibly. Which of these is one of Google’s AI principles?

    • AI should be accountable to other machines.

    • AI should be socially beneficial.

    • AI should be made available for any use.

    • AI should create or reinforce unfair bias.

  7. Which use case demonstrates ML’s ability to process natural language?

    • Identifying the topic and sentiment of customer email messages so that they can be routed to the relevant department.

    • Detecting people and objects in surveillance footage to use as evidence in criminal cases.

    • Segmenting images into different parts or regions to extract information, such as the text on a sign.

    • Identifying the artist, title, or genre of a song to create playlists based on the user's listening habits.

  8. Artificial intelligence is best suited for replacing or simplifying rule-based systems. Which is an example of this in action?

    • Using a reinforcement learning algorithm to train autonomous drones for package delivery.

    • Training a machine learning model to predict a search result ranking.

    • Implementing AI to develop a new product or service that has never been seen before.

    • Using AI to replace a human decision-maker in complex situations, such as those involving life-or-death choices.

  9. Which technology relies on models to analyze large amounts of data, learn from the insights, and then make predictions and informed decisions?

    • Expert systems

    • Natural language processing

    • Machine learning

    • Robotics

  10. You’re watching a video on YouTube and are shown a list of videos that YouTube thinks you are interested in. What ML solution powers this feature?

    • Content moderation

    • Personalized recommendations

    • Video transcription

    • Clickbait detection

Google Cloud’s AI and ML Solutions

  1. Which Google Cloud AI solution is designed to help businesses automate document processing?

    • Document AI

    • Contact Center AI

    • Cloud Talent Solution

    • Discovery AI for Retail

  2. Which feature of Vertex AI lets users build and train end-to-end machine learning models by using a GUI (graphical user interface), without writing a line of code.

    • AutoML

    • Managed ML environment

    • Custom training

    • MLOps

  3. Which Google Cloud AI solution is designed to help businesses improve their customer service?

    • Discovery AI for Retail

    • Cloud Talent Solution

    • Contact Center AI

    • Document AI

  4. An online retailer wants to help users find specific products faster on their website. One idea is to allow shoppers to upload an image of the product they’re looking to purchase. Which of Google’s pre-trained APIs could the retailer use to expand this functionality?

    • Speech-to-Text API

    • Vision API

    • Video Intelligence API

    • Natural Language API

  5. What’s the name of Google’s application-specific integrated circuit (ASIC) that is used to accelerate machine learning workloads?

    • Vertex Processing Unit (VPU)

    • Tensor Processing Unit (TPU)

    • Central Processing Unit (CPU)

    • Graphic Processing Unit (GPU)

  6. Google Cloud offers four options for building machine learning models. Which is best when a business wants to code their own machine learning environment, the training, and the deployment?

    • Custom training

    • AutoML

    • BigQuery ML

    • Pre-trained APIs

  7. BigQuery ML is a machine learning service that lets users:

    • Seamlessly connect with a data science team to create an ML model.

    • Build and evaluate machine learning models in BigQuery by using SQL.

    • Export small amounts of data to spreadsheets or other applications.

    • Build and evaluate machine learning models in BigQuery by using Python and Java.

  8. A large media company wants to improve how they moderate online content. Currently, they have a team of human moderators that review content for appropriateness, but are looking to leverage artificial intelligence to improve efficiency. Which of Google’s pre-trained APIs could they use to identify and remove inappropriate content from the media company's website and social media platforms.

    • Video Intelligence API

    • Vision API

    • Natural Language API

    • Speech-to-Text API