Об этом курсе: 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
Для кого этот курс: • 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
Автор: Google Cloud
| Основные сведения | Course 4 of 4 in the From Data to Insights with Google Cloud Platform Specialization |
| Уровень | Intermediate |
| Выполнение | 1 week of study, 5-7 hours/week |
| Язык | English |
| Требования к аппаратным средствам | You'll need a desktop web browser to run this course's interactive labs via Qwiklabs. |
| Как пройти курс | Чтобы пройти курс, выполните все оцениваемые задания. |
| Оценки пользователей |
Просмотреть
Программа курса
НЕДЕЛЯ 1
Module 16: Notebooks in the Cloud
In this module we’re going to dive into one of the most important tools for data scientists: the collaborative notebook on the cloud. As you’ll soon see, notebooks are a great way of breaking down a big data or ML problem into distinct and repeatable steps.
9 видео, 1 материал для самостоятельного изучения
- Видео: Collaborative Notebooks in the Cloud
- Видео: Demo: Cloud Datalab with BigQuery and Google Analytics
- Видео: Accessing BigQuery datasets from Cloud Datalab
- Видео: Visualizing Datasets in Charts
- Видео: Practice Reading ML Models - Intro
- Leyendo: ML Notebook Example
- Видео: Demo: Using ML to Map Manhattan
- Видео: Module Summary
- Видео: Lab Intro
- Elemento LTI: Qwiklabs – Connecting BigQuery to Cloud Datalab
- Видео: Lab Walkthrough
Оцениваемый: Notebooks in the Cloud
Module 17: Intro to Machine Learning
In this module we’ll explore an overview of what Machine Learning is from a high-level theoretical perspective and then tour how ML has become part of the culture here at Google. After that we will dive into pre-built and pre-trained ML models that we can access (like image recognition and sentiment analysis) within Cloud Datalab.
7 видео
- Видео: What is ML?
- Видео: Pre-Trained ML Models
- Видео: Demo: Cloud Translate and Vision APIs
- Cuadro de aviso de la discusión: Explore the Cloud Vision API
- Видео: Demo: Natural Language Processing API
- Cuadro de aviso de la discusión: Explore the Language APIs
- Видео: Lab Overview
- Elemento LTI: Qwiklabs – Practice with ML APIs within Cloud Datalab
- Видео: Lab Walkthrough
- Видео: Advancing from Data Analysis to Data Science
Оцениваемый: Intro to Machine Learning
Module 18: Cloud Datalab ML Toolbox
Now that you have an understanding of what Machine Learning is and what it can do, let’s continue to build your skillset with more hands on practice with ML models in Cloud Datalab. This module is about Cloud Datalab’s ML Toolbox which provides a friendly abstraction layer instead of writing TensorFlow ML code.
11 видео
- Видео: Cloud Datalab ML Toolbox
- Видео: End-to-end ML Phases Overview
- Видео: Model Training
- Видео: Model Evaluation
- Видео: Model Prediction
- Видео: Model Training with the Cloud
- Видео: Model Evaluation with Cloud Dataflow
- Видео: Model Prediction and Deployment with CMLE
- Видео: Model Monitoring with CMLE
- Видео: Lab Overview
- Elemento LTI: Qwiklabs – End-to-End ML Practice with ML Toolbox
- Видео: Lab Walkthrough
Оцениваемый: Cloud ML Toolbox
Часто задаваемые вопросы
Как это работает
Trabajo del curso
Cada curso es como un libro de texto interactivo, con videos pregrabados, cuestionarios y proyectos.
Ayuda de tus compañeros
Conéctate con miles de estudiantes y debate ideas y materiales del curso, y obtén ayuda para dominar los conceptos.
Certificados
Obtén reconocimiento oficial por tu trabajo y comparte tu éxito con amigos, compañeros y empleadores.
Авторы
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.
Стоимость
| Приобрести курс | |
|---|---|
| Получить доступ к материалам курса | Доступен |
| Получить доступ к оцениваемым материалам курса | Доступен |
| Получить итоговую оценку | Доступен |
| Earn a shareable Course Certificate | Доступен |
Рейтинги и отзывы
Good introduction to ml for me given i had no previous knowledge on the basics.
This was a great course on Machine Learning with BigQuery and Cloud Datalab. The exploration was very good for starters.
Thank you.
ok
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This was a great course in going beyond the lecture to applying the concepts of creating, training, testing and deploying a machine learning model