Informações sobre o curso: >>> By enrolling in this specialization you agree to the Qwiklabs Terms of Service as set out in the FAQ and located at: https://qwiklabs.com/terms_of_service <<< Want to know how to query and process petabytes of data in seconds? Curious about data analysis that scales automatically as your data grows? Welcome to the Data Insights course! This 1-week, accelerated online course teaches participants how to derive insights through data analysis and visualization using the Google Cloud Platform. The course features interactive scenarios and hands-on labs where participants explore, mine, load, visualize, and extract insights from diverse Google BigQuery datasets. The course covers data loading, querying, schema modeling, optimizing performance, query pricing, and data visualization. PREREQUISITES To get the most out of this course, participants must complete the prior courses in this specialization: • Exploring and Preparing your Data • Storing and Visualizing your Data • Architecture and Performance
Para quem é direcionado este curso: • Data Analysts, Business Analysts, Business Intelligence professionals • Cloud Data Engineers who will be partnering with Data Analysts to build scalable data solutions on Google Cloud Platform
Desenvolvido por: Google Cloud
| Informações básicas | Curso 4 de 4 no From Data to Insights with Google Cloud Platform Specialization |
| Nível | Intermediário |
| Compromisso | 1 week of study, 5-7 hours/week |
| Idioma | English |
| Requisitos de hardware | You'll need a desktop web browser to run this course's interactive labs via Qwiklabs. |
| Como ser aprovado | Seja aprovado em todas as tarefas para concluir o curso. |
| Classificação do usuário |
Visualizar
Programa
SEMANA 1
Introduction
Welcome to the last course in the Data Insights specialization. In this module we will overview the course topics and the labs platform you will be using.
2 videos
- Vídeo: Qwiklabs Overview
Introduction to Machine Learning
In this module, we define what Machine Learning is and how it can benefit your business. You'll see a few demos of ML in action and learn key ML terms like instances, features, and labels.
6 videos
- Vídeo: Demo: Google Photos
- Vídeo: What is deep learning?
- Vídeo: ML Applications for Business
- Vídeo: ML Terms: Instances, Features, Labels
- Vídeo: The Spectrum of ML Tools
Nota atribuída: Introduction to Machine Learning
Pre-trained ML APIs
In this module we will dive into pre-built and pre-trained ML models that we can access (like image recognition and sentiment analysis) within Cloud Datalab.
11 videos
- Vídeo: Demo: Cloud Translate and Vision APIs
- Discussion Prompt: Explore the Cloud Vision API
- Vídeo: Demo: Natural Language Processing API
- Discussion Prompt: Explore the Language APIs
- Vídeo: Collaborative Notebooks in the Cloud
- Vídeo: Demo: Cloud Datalab with BigQuery and Google Analytics
- Vídeo: Accessing BigQuery datasets from Cloud Datalab
- Vídeo: Visualizing Datasets in Charts
- Vídeo: Lab Overview
- Vídeo: Lab Walkthrough
- Vídeo: Lab Intro
- LTI Item: Qwiklabs – Connecting BigQuery to Cloud Datalab
- Vídeo: Lab Walkthrough
Nota atribuída: Qwiklabs – Practice with ML APIs within Cloud Datalab
Nota atribuída: Notebooks in the Cloud
SEMANA 2
Creating ML Datasets in BigQuery
8 videos
- Vídeo: Choosing good features
- Vídeo: Exploring and Preprocessing Data
- Vídeo: Demo: Exploring and Preprocessing Data
- Vídeo: Other Tools for Creating Data Pipelines
- Vídeo: Knowing the Unknowable
- Vídeo: Creating Repeatable Dataset Splits
- Vídeo: Lab Solution: Creating Repeatable Dataset Splits
Nota atribuída: Creating Repeatable Dataset Splits with BigQuery
Nota atribuída: Intro to Machine Learning
Creating ML Models in BigQuery
In this module, you will learn how to create machine learning models directly inside of BigQuery. You will learn the new syntax and work through the phases of building, evaluating, and testing an ML model.
6 videos, 1 leituras
- Vídeo: Phases of Model Building
- Vídeo: Demo: Predicting Taxi Cab Fare
- Reading: BigQuery ML Resources
- Vídeo: Demo: Creating a Classification Model
- Vídeo: Lab Intro: Predicting Visitor Return Purchases with BigQuery
- Vídeo: Lab Solution: Predicting Visitor Return Purchases in BigQuery
Nota atribuída: Predicting Visitor Return Purchases with BigQuery
Nota atribuída: Building a Forecasting model in BigQuery ML
Nota atribuída: BigQuery ML
End of Course Recap
You've made it to the end! Let's review the lessons learned in the course and what resources are available for continued learning.
1 vídeos
Perguntas frequentes
Como funciona
Coursework
Each course is like an interactive textbook, featuring pre-recorded videos, quizzes and projects.
Help from Your Peers
Connect with thousands of other learners and debate ideas, discuss course material, and get help mastering concepts.
Certificates
Earn official recognition for your work, and share your success with friends, colleagues, and employers.
Desenvolvedores
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.
Custo
| Comprar curso | |
|---|---|
| Acesso aos materiais do curso | Disponível |
| Acesso a materiais valendo nota | Disponível |
| Receba uma nota final | Disponível |
| Obtenha um Certificado de Curso compartilhável | Disponível |
Classificações e avaliações
Very professional Google course.
good
The instructor Evan is super great to rolling out machine learning in an easy /understandable way. hope he can tech more in-depth of machine learning.
O Coursera proporciona acesso universal à melhor educação do mundo fazendo parcerias com as melhores universidades e organizações para oferecer cursos on-line.
© 2018 Coursera Inc. Todos os direitos reservados.
CC
It would be nice if the labs had additional/different code then the one explained over the videos.