This course introduces the Google Cloud big data and machine learning products and services that support the data-to-AI lifecycle. It explores the processes, challenges, and benefits of building a big data pipeline and machine learning models with Vertex AI on Google Cloud.
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À propos de ce cours
Ce que vous allez apprendre
Recognize the data-to-AI lifecycle on Google Cloud and the major big data and machine learning products.
Analyze big data at scale with BigQuery.
Identify different options to build machine learning solutions on Google Cloud.
Describe a machine learning workflow and the key steps with Vertex AI.
Compétences que vous acquerrez
- Tensorflow
- Bigquery
- Google Cloud Platform
- Cloud Computing
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Google Cloud
We help millions of organizations empower their employees, serve their customers, and build what’s next for their businesses with innovative technology created in—and for—the cloud. Our products are engineered for security, reliability, and scalability, running the full stack from infrastructure to applications to devices and hardware. Our teams are dedicated to helping customers apply our technologies to create success.
Programme de cours : ce que vous apprendrez dans ce cours
Course Introduction
This section welcomes learners to the Big Data and Machine Learning Fundamentals course, and provides an overview of the course structure and goals.
Big Data and Machine Learning on Google Cloud
This section explores the key components of Google Cloud's infrastructure. It's here that we introduce many of the big data and machine learning products and services that support the data-to AI lifecycle on Google Cloud.
Data Engineering for Streaming Data
This section introduces Google Cloud's solution to managing streaming data. It examines an end-to-end pipeline, including data ingestion with Pub/Sub, data processing with Dataflow, and data visualization with Looker and Data Studio.
Big Data with BigQuery
This section introduces learners to BigQuery, Google's fully-managed, serverless data warehouse. It also explores BigQuery ML, and the processes and key commands that are used to build custom machine learning models.
Machine Learning Options on Google Cloud
This section explores four different options to build machine learning models on Google Cloud. It also introduces Vertex AI, Google's unified platform for building and managing the lifecycle of ML projects.
The Machine Learning Workflow with Vertex AI
This section focuses on the three key phases--data preparation, model training, and model preparation--of the machine learning workflow in Vertex AI. Learners get the opportunity to practice building a machine learning model with AutoML.
Course Summary
This section reviews the topics covered in the course, and provides additional resources for further learning.
Avis
- 5 stars71,69 %
- 4 stars23,67 %
- 3 stars3,51 %
- 2 stars0,53 %
- 1 star0,58 %
Meilleurs avis pour GOOGLE CLOUD BIG DATA AND MACHINE LEARNING FUNDAMENTALS
Course is very engaging and attentive. As we have hands-on lab, we get some practical experience with guidance. I have learnt a lot from this course. Cant wait to attend Data Engineering Course.
This course gives you a pretty good fundamental idea on what you are diving into. Google cloud platform has bucket of data engineering features. This course sets you on the starting line for them.
This course really helped me in understanding exactly 'How the Big data and Machine learning can be used in Cloud' and 'The ease to use it'. Thank you for summing all the fundamentals in this course.
It is a fun journey to explore the Big Data and ML resource in GCP. And even cooler is you don't need work for a big company or own lots of resource to get your hands dirty to support your learning!
Foire Aux Questions
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