Google Cloud Fundamentals: Big Data and Machine Learning (GCF-BDM)
Virtual Learning: 550€ + IVA
REF: GCF-BDM Catálogo: Google Cloud Área: Fundamentals
Duração:
1 dia
Próxima Data:
26 Jun 2025
Local:
Online
Descrição
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.
*PVP por participante. A realização do curso nas datas apresentadas está sujeita a um quórum mínimo de inscrições.
Destinatários
- Data analysts, Data scientists, 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.
-
Área: Google Cloud
-
Certificação Associada: This course is part of the following Certifications: Google Cloud Certified Professional Machine Learning Engineer (PMLE), Google Cloud Certified Professional Data Engineer (PDE)
Programa:
Module 1: 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.
Lessons:
- Google Cloud infrastructure
- Compute
- Storage
- The history of big data and ML products
- Big data and ML product categories
- Customer example: Gojek
- Lab: Exploring a BigQuery Public Dataset
Module 2: 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 Looker Studio.
Lessons:
- Big data challenges
- Message-oriented architecture
- Designing streaming pipelines with Apache Beam
- Implementing streaming pipelines on Cloud Dataflow
- Visualization with Looker
- Visualization with Looker Studio
- Lab: Creating a streaming data pipeline for a Real-Time dashboard with Dataflow
Module 3: 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.
Lessons:
- Storage and analytics
- Demo: Querying TB of data in seconds
- Introduction to BigQuery ML
- Using BigQuery ML to predict customer lifetime value
- BigQuery ML project phases
- BigQuery ML key commands
- Lab: Predict Visitor Purchases with BigQuery ML
Module 4: 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.
Lessons:
- Options to build ML models
- Pre-built APIs
- AutoML
- Custom training
- Vertex AI
- AI Solutions
Module 5: 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.
Lessons:
- Data preparation
- Model training
- Model evaluation
- Model deployment and monitoring
- Lab: Vertex AI: Predicting Loan Risk with AutoML
Pré-requisitos:
- 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.
Partilha:
Precisas de ajuda a encontrar o teu futuro?
