Об этом курсе: This 1-week accelerated on-demand course introduces participants to the Big Data and Machine Learning capabilities of Google Cloud Platform (GCP). It provides a quick overview of the Google Cloud Platform and a deeper dive of the data processing capabilities. At the end of this course, participants will be able to: • Identify the purpose and value of the key Big Data and Machine Learning products in the Google Cloud Platform • Use CloudSQL and Cloud Dataproc to migrate existing MySQL and Hadoop/Pig/Spark/Hive workloads to Google Cloud Platform • Employ BigQuery and Cloud Datalab to carry out interactive data analysis • Choose between Cloud SQL, BigTable and Datastore • Train and use a neural network using TensorFlow • Choose between different data processing products on the Google Cloud Platform Before enrolling in this course, participants should have roughly one (1) year of experience with one or more of the following: • A common query language such as SQL • Extract, transform, load activities • Data modeling • Machine learning and/or statistics • Programming in Python Google Account Notes: • You'll need a Google/Gmail account and a credit card or bank account to sign up for the Google Cloud Platform free trial (Google services are currently unavailable in China). • If you are a Google Cloud Platform customer with European Union (EU) and Russian billing addresses, read the VAT Overview documentation at: https://cloud.google.com/billing/docs/resources/vat-overview • More Google Cloud Platform free trial FAQs are available at: https://cloud.google.com/free-trial/
Для кого этот курс: This class is intended for Data analysts, Data scientists and Business analysts. It is also suitable for IT decision makers evaluating Google Cloud Platform for use by data scientists. This class is for people who do the following with big data: • Extracting, Loading, Transforming, cleaning, and validating data for use in analytics • Designing pipelines and architectures for data processing • Creating and maintaining machine learning and statistical models • Querying datasets, visualizing query results and creating reports
| Основные сведения | Course 1 of 5 in the Data Engineering on Google Cloud Platform Specialization |
| Уровень | Intermediate |
| Выполнение | 1 week of study, 6-10 hours/week |
| Язык | English, Субтитры: Japanese, Spanish |
| Требования к аппаратным средствам | You'll need a Google Cloud Platform Free Trial account. Sign up at: https://cloud.google.com/free/ |
| Как пройти курс | Чтобы пройти курс, выполните все оцениваемые задания. |
| Оценки пользователей |
- Видео: Introduction to the Data and Machine Learning Specialization
- Reading: Please read me
- Видео: Intro to Big Data and Machine Learning Fundamentals
- Видео: Course Overview and Agenda
- Видео: Meet Your Instructor
- Видео: Welcome to Introduction to GCP and its Big Data Products
- Видео: What is the Google Cloud Platform?
- Видео: GCP Big Data Products
- Видео: Usage Scenarios
- Видео: How to do the Labs
- Reading: Sign Up for the Free Trial and Create a Project
- Видео: Module 1 Resources
- Видео: Welcome to Foundations of GCP Compute and Storage
- Видео: CPUs On Demand
- Видео: Lab 2a Overview
- Reading: Start Compute Engine Instance (Lab 2a)
- Видео: Lab 2a Review
- Видео: A Global Filesystem
- Видео: Lab 2b Overview
- Reading: Interact with Cloud Storage
- Видео: Lab 2b Review
- Видео: Module 2 Review
- Видео: Module 2 Resources
- Reading: Module 2 Resources
- Видео: Intro to Managed Services for Common Use Cases
- Видео: Stepping Stones to Transformation
- Видео: Your SQL Database in the Cloud
- Видео: Lab 3a Overview
- Reading: Setup rentals data in Cloud SQL
- Видео: Lab 3a Review
- Видео: Managed Hadoop in the Cloud
- Видео: Lab 3b Overview
- Reading: Recommendations ML with Dataproc
- Видео: Lab 3b Review
- Видео: Module 3 Review
- Видео: Module 3 Resources
- Видео: Intro to Scaling Data Analysis: Change How You Compute with GCP
- Видео: Fast Random Access
- Видео: Interactive, Iterative Development & Demo
- Видео: Warehouse and Interactively Query Petabytes
- Видео: Lab 4a Overview
- Reading: Create ML Dataset with BigQuery (Lab 4a)
- Видео: Lab 4a Review
- Видео: Machine Learning with TensorFlow
- Видео: Training and Creating a Neural Network Model
- Видео: Lab 4b Overview
- Reading: Carry out ML with TensorFlow
- Видео: Fully Build Machine Learning Models
- Видео: Lab 4c Overview
- Reading: Machine Learning APIs (Lab 4c)
- Видео: Module 4 Review
- Видео: Module 4 Resources
- Reading: Module 4 Resources
- Видео: Intro to Data Processing Architectures
- Видео: Message-oriented Architectures
- Видео: Serverless Data Pipelines
- Видео: Module 5 Review
- Reading: Module 5 Resources
- Видео: Summary of GCP, Big Data, and ML
- Видео: Next Steps
- Видео: Module 6 Resources
- Reading: Module 6 Resources
Each course is like an interactive textbook, featuring pre-recorded videos, quizzes and projects.
Connect with thousands of other learners and debate ideas, discuss course material, and get help mastering concepts.
Earn official recognition for your work, and share your success with friends, colleagues, and employers.
| 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 |
Very interesting course. The subjects are challenging, but the instructor explains everything in an interesting and clear manner.
Me parece muy bueno el curso, pero por el momento hay algunos cambios en la plataforma practica, son detalles pero al momento de seguir las instrucciones, cambian algunos menús, se entiende que es por la constante actualizaciones de la plataforma web de GCP. (esto hace perder un poco de tiempo)
Grand insights into Big Data & ML. Highly recommended!
TB
Great examples, excellent overview of GCP products and how they relate. Only thing thats missing is a lab with Google Cloud ML