Google Cloud Platform Big Data and Machine Learning Fundamentals em Português Brasileiro

Go to Course: https://www.coursera.org/learn/gcp-big-data-ml-fundamentals-br

Introduction

### Course Review: Google Cloud Platform Big Data and Machine Learning Fundamentals (Portuguese-Brazilian) In today’s data-driven world, understanding big data and machine learning is not just an advantage; it's becoming a necessity. For professionals wanting to dive deep into these concepts within the Google Cloud ecosystem, the course "Google Cloud Platform Big Data and Machine Learning Fundamentals em Português Brasileiro" is an excellent choice. Here’s an in-depth look at what you can expect from this course, including a review of its content and structure, along with a recommendation for prospective learners. #### Course Overview This course provides a comprehensive introduction to the critical products and services associated with big data and machine learning on Google Cloud. It equips participants with the necessary knowledge to manage the entire data lifecycle for artificial intelligence (AI). From understanding the challenges involved in building efficient data pipelines to leveraging Vertex AI for machine learning models, this course covers it all. #### Syllabus Breakdown 1. **Introdução ao curso** The course kicks off with a solid foundation in big data and machine learning concepts. This section does a fantastic job setting the stage, outlining the course objectives, and providing learners with a roadmap of what to expect. 2. **Big Data e machine learning no Google Cloud** Here, learners are introduced to the core components of the Google Cloud infrastructure. This segment highlights essential products and services that facilitate the data lifecycle, ensuring students understand their importance in the context of AI. 3. **Engenharia de dados para dados de streaming** Streaming data is a critical aspect of modern data engineering, and this section covers Google Cloud’s solutions for managing such data. Students will engage with a complete pipeline involving data ingestion with Pub/Sub, data processing via Dataflow, and data visualization using Looker and Data Studio. 4. **Big Data com BigQuery** This section delves into BigQuery, Google’s serverless, fully-managed data warehouse. It offers insights into BigQuery ML and the essential commands for developing custom machine learning models. It’s an excellent resource for those interested in real-time data analysis and decision-making. 5. **Opções de machine learning no Google Cloud** Learners are exposed to different methodologies for developing machine learning models. The introduction of Vertex AI as a unified platform for managing ML project cycles is crucial for anyone looking to implement practical machine learning solutions. 6. **O fluxo de trabalho de machine learning com a Vertex AI** This module focuses on the three primary stages of machine learning workflows within Vertex AI: data preparation, model training, and model evaluation. Participants will appreciate the hands-on experience of building an ML model using AutoML, which reinforces learning through practical application. 7. **Resumo do curso** The course concludes with a summary that revisits key themes and provides additional resources for future reference. This recap is valuable for solidifying knowledge gained and for guiding learner’s next steps in their education. #### Recommendation The "Google Cloud Platform Big Data and Machine Learning Fundamentals em Português Brasileiro" course is highly recommended for anyone looking to enhance their data proficiency, particularly within the Google Cloud environment. It’s suitable for beginners who want to develop a solid understanding of big data principles and machine learning applications, and it’s also beneficial for professionals aiming to upskill. The course's structure encourages a balanced approach to theory and practice, making it engaging and accessible for learners with varied backgrounds. Plus, the fact that it's taught in Portuguese Brazilian ensures that native speakers can grasp complex concepts more readily. In conclusion, if you're eager to embark on a journey into the world of big data and machine learning, this course is an excellent starting point. Enrolling in this course can empower you with the skills to leverage Google Cloud's vast capabilities for data analytics and AI, transforming your professional opportunities in today's tech landscape.

Syllabus

Introdução ao curso

Nesta seção, os participantes encontram o curso de noções básicas de Big Data e machine learning, bem como uma visão geral da estrutura e dos objetivos do curso.

Nesta seção, você encontra os principais componentes da infraestrutura do Google Cloud. Nela, apresentamos muitos dos produtos e serviços de Big Data e machine learning que suportam o ciclo de vida de dados para IA no Google Cloud.

Nesta seção, você conhecerá a solução do Google Cloud para gerenciar dados de streaming. Nela, analisamos um pipeline completo, incluindo a ingestão de dados com o Pub/Sub, o processamento de dados com o Dataflow e a visualização de dados com o Looker e o Data Studio.

Nesta seção, apresentamos aos participantes o BigQuery, o data warehouse sem servidor e totalmente gerenciado do Google. Também mostramos o BigQuery ML, bem como os processos e principais comandos usados para criar modelos de machine learning personalizados.

Nesta seção, você verá quatro opções diferentes para criar modelos de machine learning no Google Cloud. Nela, também apresentaremos a Vertex AI, a plataforma unificada do Google para criação e gerenciamento do ciclo de vida de projetos de ML.

Neste módulo, focaremos nas três etapas principais do fluxo de trabalho de machine learning na Vertex AI: preparação de dados, treinamento de modelos e avaliação de modelos. Os participantes poderão praticar a criação de um modelo de machine learning com o AutoML.

Nesta seção, você verá novamente os temas do curso, bem como outros recursos para consultar no futuro.