Google Cloud: Big Data And Machine Learning Fundamentals
- Kursuskode GO8325
- Varighed 1 Dag
Leveringsmetoder
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GTC 20 Inkl. Moms
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Leveringsmetoder
Kurset er tilgængeligt i følgende formater:
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Firma kursus
Et lukket firma kursus
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Åbent kursus
Traditionel klasserumsundervisning
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Åbent kursus (Virtuelt)
Live klasserumsundervisning du tilgår virtuelt
Anmod om dette kursus Med en anden leveringsløsning
Beskrivelse
ToppenKursusdato
ToppenMålgruppe
Toppen- Data analysts getting started with Google Cloud Platform
- Data scientists getting started with Google Cloud Platform
- Business analysts getting started with Google Cloud Platform
- Individuals responsible for designing pipelines and architectures for data processing, creating and maintaining machine learning and statistical models, querying datasets, visualizing query results and creating reports
- Executives and IT decision makers evaluating Google Cloud Platform for use by data scientists
Kursets formål
ToppenIn this course you will learn:
- Purpose and value of the key Big Data and Machine Learning products in the GoogleCloud Platform
- Use Cloud SQL and Cloud Dataproc to migrate existing MySQL andHadoop/Pig/Spark/Hive workloads to Google Cloud Platform
- Employ BigQuery and Cloud Datalab to carry out interactive data analysis
- Train and use a neural network using TensorFlow
- Employ ML APIs
- Choose between different data processing products on the Google Cloud Platform
Kursusindhold
Toppen1. Introducing Google Cloud Platform
- Google Platform Fundamentals Overview
- Google Cloud Platform Data Products and Technology
- Usage scenarios
2. Compute and Storage Fundamentals
- CPUs on demand (Compute Engine)
- A global filesystem (Cloud Storage)
- CloudShell
3. Data Analytics on the Cloud
- Stepping-stones to the cloud
- CloudSQL: your SQL database on the cloud
- Lab: Importing data into CloudSQL and running queries
- Spark on Dataproc
4. Scaling Data Analysis
- Fast random access
- Datalab
- BigQuery
- Machine Learning with TensorFlow
- Fully built models for common needs
5. Data Processing Architectures
- Message-oriented architectures with Pub/Sub
- Creating pipelines with Dataflow
- Reference architecture for real-time and batch data processing
6. Summary
- Why GCP?
- Where to go from here
- Additional Resources
Classroom Live Labs
Lab 1: Sign up for Google Cloud Platform
Lab 2: Set up a Ingest-Transform-Publish data processing pipeline
Lab 3: Machine Learning Recommendations with SparkML
Lab 4: Build machine learning dataset
Lab 5: Train and use neural network
Lab 6: Employ ML APIs
Forudsætninger
Toppen- Basic proficiency with common query language such as SQL
- Experience with data modeling, extract, transform, load activities
- Developing applications using a common programming language such Python
- Familiarity with Machine Learning and/or statistics
- #000000
- GO8325
- Google Cloud: Big Data And Machine Learning Fundamentals
- Cloud Computing
- GO8325 | Google Cloud: Big Data And Machine Learning Fundamentals | Training Course | Google.