[ad_1]
Google Cloud Fundamentals for AWS Professionals complete course is currently being offered by Google Cloud through Coursera platform.
About this Course
Google Cloud Fundamentals for AWS Professionals introduces important concepts and terminology for working with Google Cloud. Through videos and hands-on labs, this course presents and compares many of Google Cloud’s computing and storage services, along with important resource and policy management tools.
Also Check: How to Apply for Coursera Financial Aid
Big Data and Machine Learning
Question 1. Name two use cases for Google Cloud Dataproc (Select 2 answers).
- Migrate on-premises Hadoop jobs to the cloud
- Manage data that arrives in realtime
- Data mining and analysis in datasets of known size
- Manage datasets of unpredictable size
Question 2. Name two use cases for Google Cloud Dataflow (Select 2 answers).
- Manual resource management
- Extract, Transform, and Load (ETL)
- Orchestration
- Reserved compute instances
Question 3. Name three use cases for the Google Cloud Machine Learning Platform (Select 3 answers).
- Fraud detection
- Data preparation
- Content personalization
- Sentiment analysis
- Query architecture
Question 4. Which statements are true about BigQuery? Choose all that are true (2 statements).
- BigQuery is a good choice for data analytics warehousing.
- BigQuery lets you run fast SQL queries against large databases.
- Once in BigQuery, data is not accessible from other GCP services.
- BigQuery is a good choice for online transaction processing.
- BigQuery requires that you provision database instances ahead of use.
Question 5. Name three use cases for Cloud Pub/Sub (Select 3 answers).
- Analyzing streaming data
- Decoupling systems
- Storage of binary web content
- Internet of Things applications
- Executing ad-hoc SQL queries
Question 6. What is TensorFlow?
- A managed service for building data pipelines
- An open-source software library that’s useful for building machine learning applications
- A hardware device designed to accelerate machine learning workloads
- A managed service for building machine learning models
Question 7. What does the Cloud Natural Language API do?
- It analyzes text to reveal its structure and meaning.
- It extracts text in various languages from images.
- It translates arbitrary strings into any supported language.
- It performs sentiment analysis on audio and video content.
[ad_2]
Source link