Smart Analytics, Machine Learning, and AI on GCP em Português Brasileiro

Google Cloud via Coursera

Go to Course: https://www.coursera.org/learn/smart-analytics-machine-learning-ai-gcp-br

Introduction

### Course Review: Smart Analytics, Machine Learning, and AI on GCP (em Português Brasileiro) In an era where data-driven decisions are paramount to business success, the course **Smart Analytics, Machine Learning, and AI on GCP (em Português Brasileiro)** stands out as a comprehensive learning experience tailored for Portuguese-speaking professionals seeking to deepen their understanding of machine learning components that can be integrated into data pipelines. Offered on Coursera, this course is expertly designed for individuals looking to harness the power of Google Cloud Platform (GCP) for analytics and AI applications. #### Course Overview The course provides a comprehensive introduction to incorporating machine learning into data pipelines, demonstrating how organizations can extract valuable insights from their data. Covering a range of tools and methodologies, the curriculum balances theoretical knowledge with practical applications, making it suitable for both beginners and data professionals aiming to enhance their skillset. #### Detailed Syllabus Breakdown 1. **Introdução** - This initial module sets the tone for the course by introducing participants to the course structure and key topics. 2. **Introdução ao Analytics e à IA** - Here, learners are introduced to the various machine learning options available within Google Cloud, providing foundational knowledge necessary for subsequent modules. 3. **APIs de modelos de ML pré-criadas para dados não estruturados** - This module focuses on leveraging pre-built ML APIs for structured data, illustrating how companies can quickly integrate powerful models without extensive custom development. 4. **Análise de Big Data com notebooks** - Participants will explore the utilization of notebooks to conduct Big Data analytics, fostering hands-on experience with the tools used in real-world applications. 5. **Pipelines de ML de produção com o Kubeflow** - Understanding production ML pipelines is crucial; this segment introduces Kubeflow and AI Hub, key components for creating custom ML models at scale. 6. **Criar modelos personalizados com o SQL no BigQuery ML** - This module provides an insightful overview of how to build custom models using SQL in BigQuery ML, making advanced analytics accessible to professionals familiar with SQL. 7. **Criar modelos personalizados com o AutoML** - Focusing on AutoML, this section walks participants through creating customized models without the need for extensive machine learning expertise. 8. **Resumo** - The course concludes with a recap of the key themes covered, reinforcing the learning experience and ensuring that participants leave with a strong grasp of the material. #### Review and Recommendation This course is remarkably structured, providing a blend of theoretical foundations and practical applications that help learners implement machine learning in their workflows effectively. The Portuguese-language instruction is an advantage for native speakers, as it ensures that participants can engage with the content without language barriers. The course also excels in its practical components, offering real-world examples and exercises that enhance understanding. For anyone working in analytics, data science, or a related field within varying levels of expertise, this course presents an invaluable opportunity to grow your skillset and leverage machine learning using GCP tools. I highly recommend **Smart Analytics, Machine Learning, and AI on GCP (em Português Brasileiro)** to anyone looking to advance their career in data science and analytics. If you're interested in the transformative power of AI and machine learning, this course will equip you with the essential tools and knowledge needed to thrive in today’s data-centric landscape. Whether you are a beginner or looking to upgrade your skills, enrolling in this course will be a wise investment in your professional development.

Syllabus

Introdução

Neste módulo, apresentamos o curso e a programação.

Introdução ao Analytics e à IA

Neste módulo, falamos sobre as opções de ML no Google Cloud

APIs de modelos de ML pré-criadas para dados não estruturados

O foco deste módulo é o uso de APIs de ML pré-criadas em dados estruturados

Análise de Big Data com notebooks

Neste módulo, falamos sobre como usar o notebooks

Pipelines de ML de produção com o Kubeflow

Neste módulo, falamos da criação de modelos de ML personalizados e apresentamos o Kubeflow e o AI Hub

Criar modelos personalizados com o SQL no BigQuery ML

Este é um módulo sobre o BigQuery ML

Criar modelos personalizados com o AutoML

Criar modelos personalizados com o AutoML

Resumo

Neste módulo, recapitulamos os temas abordados no curso