This 2-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.
Google Cloud Platform Big Data and Machine Learning Fundamentals
ofrecido por
Google Cloud
Acerca de este Curso
313,571 vistas recientes
Resultados profesionales del estudiante
45%
comenzó una nueva carrera después de completar estos cursos
43%
consiguió un beneficio tangible en su carrera profesional gracias a este curso
Qué aprenderás
Processing big data at scale for analytics and machine learning
Fundamentals of building new machine learning models
Creating streaming data pipelines and dashboards
Habilidades que obtendrás
TensorflowBigqueryGoogle Cloud PlatformCloud Computing
Resultados profesionales del estudiante
45%
comenzó una nueva carrera después de completar estos cursos
43%
consiguió un beneficio tangible en su carrera profesional gracias a este curso
100 % en línea
Comienza de inmediato y aprende a tu propio ritmo.
Fechas límite flexibles
Restablece las fechas límite en función de tus horarios.
Nivel intermedio
Aprox. 14 horas para completar
Sugerido: 2 weeks of study, 6-10 hours/week
Inglés (English)
Subtítulos: Inglés (English)
ofrecido por
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.
Programa - Qué aprenderás en este curso
3 horas para completar
Introduction to the Data and Machine Learning on Google Cloud Platform Specialization .
Welcome to the Big Data and Machine Learning fundamentals on GCP course. Here you will learn the basics of how the course is structured and the four main big data challenges you will solve for.
3 horas para completar
13 videos (Total 78 minutos), 2 lecturas, 2 cuestionarios
13 videos
Introduction to Google Cloud Platform3m
Compute Power for Analytic and ML Workloads9m
Demo: Creating a VM on Compute Engine13m
Elastic Storage with Google Cloud Storage5m
Build on Google's Global Network3m
Security: On-premise vs Cloud-native2m
Evolution of Google Cloud Big Data Tools5m
Getting Started with Google Cloud Platform and Qwiklabs3m
Choosing the right approach5m
What you can do with Google Cloud Platform3m
Activity: Explore real customer solution architectures7m
Key roles in a data-driven organization6m
2 lecturas
Google Cloud Public Datasets program10m
Module Resources10m
1 ejercicio de práctica
Module Review5m
2 horas para completar
Recommending Products using Cloud SQL and Spark
In this module you will have an existing Apache SparkML recommendation model that is running on-premise. You will learn about recommendation models and how you can run them in the cloud with Cloud Dataproc and Cloud SQL.
2 horas para completar
8 videos (Total 50 minutos), 1 lectura, 2 cuestionarios
8 videos
Introduction to machine learning5m
Challenge: ML for recommending housing rentals8m
Approach: Move from on-premise to Google Cloud Platform9m
Demo: From zero to an Apache Spark job in 10 minutes or less6m
Challenge: Utilizing and tuning on-premise clusters6m
Move storage off-cluster with Google Cloud Storage4m
Lab Intro2m
1 lectura
Module Resources5m
1 ejercicio de práctica
Module Review15m
3 horas para completar
Predict Visitor Purchases with BigQuery ML
In this module, you will learn the foundations of BigQuery and big data analysis at scale. You will then learn how to build your own custom machine learning model to predict visitor purchases using just SQL with BigQuery ML.
3 horas para completar
13 videos (Total 74 minutos), 2 lecturas, 2 cuestionarios
13 videos
Demo: Query 2 billion lines of Github code in less than 30 seconds11m
BigQuery: Fast SQL Engine4m
Demo: Exploring bike share data with SQL11m
Data quality4m
BigQuery managed storage5m
Insights from geographic data2m
Demo: Analyzing lightning strikes with BigQuery GIS7m
Choosing a ML model type for structured data4m
Predicting customer lifetime value5m
BigQueryML: Create models with SQL3m
Phases in ML model lifecycle2m
BigQuery ML: key features walkthrough5m
2 lecturas
Lab Intro10m
Module Resources10m
1 ejercicio de práctica
Module Review4m
2 horas para completar
Create Streaming Data Pipelines with Cloud Pub/sub and Cloud Dataflow
In this module you will engineer and build an auto-scaling streaming data pipeline to ingest, process, and visualize data on a dashboard. Before you build your pipeline you'll learn the foundations of message-oriented architecture and pitfalls to avoid when designing and implementing modern data pipelines.
2 horas para completar
8 videos (Total 31 minutos), 1 lectura, 2 cuestionarios
8 videos
Message-oriented architectures with Cloud Pub/Sub6m
Designing streaming pipelines with Apache Beam3m
Implementing streaming pipelines on Cloud Dataflow3m
Visualizing insights with Data Studio3m
Creating charts with Data Studio2m
Demo: Data Studio walkthrough7m
Lab Intro1m
1 lectura
Module Resources10m
1 ejercicio de práctica
Module Review4m
2 horas para completar
Classify Images with Pre-Built Models using Vision API and Cloud AutoML
Don't want to create a custom ML model from scratch? Learn how to leverage and extend pre-built ML models like the Vision API and Cloud AutoML for image classification.
2 horas para completar
10 videos (Total 55 minutos), 2 lecturas, 2 cuestionarios
10 videos
How does ML on unstructured data work?3m
Demo: ML built into Google Photos1m
Comparing approaches to ML2m
Demo: Using ML building blocks7m
Using pre-built AI to create a chatbot4m
Customizing Pre-built models with AutoML7m
Lab Intro22s
Building a Custom Model1m
Demo: Text classification done three ways21m
2 lecturas
Additional resources to build custom models10m
Module Resources10m
1 ejercicio de práctica
Module Review
5 minutos para completar
Summary
In this final module, we will review the key challenges, solutions, and topics covered as part of this fundamentals course. We will also review additional resources and the steps you can take to get certified as a Google Cloud Data Engineer.
5 minutos para completar
1 video (Total 5 minutos)
1 video
Revisiones
Principales revisiones sobre GOOGLE CLOUD PLATFORM BIG DATA AND MACHINE LEARNING FUNDAMENTALS
por VSMar 2, 2019
Overall a good curated course to help understand the GCP offerings and high level architecture of how their offerings fit in the current landscape. Easy to follow along as this was fundamental course.
por MMNov 13, 2019
In general - great course with a good introduction to GCP tools and platform. Some of the materials might need to get updated though as it seems they are a bit behind the new version of the platform.
por ADSep 23, 2019
This course really helped me in understanding exactly 'How the Big data and Machine learning can be used in Cloud' and 'The ease to use it'. Thank you for summing all the fundamentals in this course.
por DKApr 7, 2019
This course provides the basics of Google Cloud Platform and makes us understand Google Products and services on Cloud. I would love to explore GCP more and will opt for the remaining GCP courses.
por ARMay 26, 2019
This course gives you a pretty good fundamental idea on what you are diving into. Google cloud platform has bucket of data engineering features. This course sets you on the starting line for them.
por BVDec 23, 2019
It was very good training with some of the real-time use cases enjoyed a lot. As a new person to google cloud and big data, I think this the best basic fundamental which I have come across so far.
por CRDec 26, 2017
This was a great course to understand at a high level how to design and create my data ecosystem and how to do it sustainably. Hopefully, next courses provide more in-depth the technical features.
por GOOct 5, 2018
This is an awesome course to understand GCP and fundamentals of Big Data. Very well designed and delivered by Google and Coursera. I love the teacher and his techniques as well. A BIG Thank you.
por PCJun 23, 2017
Course is very engaging and attentive. As we have hands-on lab, we get some practical experience with guidance. I have learnt a lot from this course. Cant wait to attend Data Engineering Course.
por JIMar 26, 2018
Very good and well thought out.\n\nI just laughed out loud when the translation for "wow this is cool" to Spanish was "wow esto es fresco" (wow, this is a fresco/fresh) Classic google translate.
por BBJun 3, 2019
It was great learning about Google Cloud and hands on with the various services on the platform. There are immense possibilities of Cloud technologies in the future and happy to be a part of it
por MPJun 6, 2017
I highly recommend this course for an overview of what tools and services are provided by Google Cloud Platform that can be used for your web app hosting needs, big data, and machine learning.
Preguntas Frecuentes
¿Cuándo podré acceder a las lecciones y tareas?
Una vez que te inscribes para obtener un Certificado, tendrás acceso a todos los videos, cuestionarios y tareas de programación (si corresponde). Las tareas calificadas por compañeros solo pueden enviarse y revisarse una vez que haya comenzado tu sesión. Si eliges explorar el curso sin comprarlo, es posible que no puedas acceder a determinadas tareas.
¿Qué recibiré si me suscribo a este Certificado?
Cuando te inscribes en un curso, obtienes acceso a todos los cursos del Certificado y te darán un certificado cuando completes el trabajo. Se añadirá tu Certificado electrónico a la página Logros. Desde allí, puedes imprimir tu Certificado o añadirlo a tu perfil de LinkedIn. Si solo quieres leer y visualizar el contenido del curso, puedes auditar el curso sin costo.
¿Cuál es la política de reembolsos?
Are there prerequisites for this course?
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
Am I eligible for the Google Cloud Platform free trial?
To be eligible for the free trial, you will need:
- Google account (Google is currently blocked in China)
- Credit card or bank account
- Terms of service
Note: There is a known issue with certain EU countries where individuals are not able to sign up, but you may sign up as "business" status and intend to see a potential economic benefit from the trial. More details at: https://support.google.com/cloud/answer/6090602
More Google Cloud Platform free trial FAQs are available at: https://cloud.google.com/free-trial/
For more details on how the free trial works, visit our documentation page: https://cloud.google.com/free-trial/docs/
What if I have already used up my Google Cloud Platform free trial?
If your current Google account is no longer eligible for the Google Cloud Platform free trial, you can create another Google account. Your new Google account should be used to sign up for the free trial.
How does the free trial work?
View this page for more details: https://cloud.google.com/free-trial/docs/
Is this course similar to CPB100?
Yes, this online course is based on the instructor-led training formerly known as CPB100.
Does this course relate to the Google Certified Professional Data Engineer certification?
The course covers the topics presented on the certification exam, however we recommend additional preparation including hands-on product experience. The best preparation for certification is real-world, hands-on experience. Review the Google Certified Professional Data Engineer certification preparation guide for further information and resources at https://cloud.google.com/certification/guides/data-engineer/
What is a Google certification?
Google’s Certification Program gives customers and partners a way to demonstrate their technical skills in a particular job-role and technology. Individuals are assessed using a variety of rigorously developed industry-standard methods to determine whether they meet Google’s proficiency standards. Read more at https://cloud.google.com/certification/
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