About this Specialization
100% online courses

100% online courses

Start instantly and learn at your own schedule.
Flexible Schedule

Flexible Schedule

Set and maintain flexible deadlines.
Intermediate Level

Intermediate Level

Hours to complete

Approx. 1 month to complete

Suggested 14 hours/week
Available languages

English

Subtitles: English...

Skills you will gain

TensorflowBigqueryBigtableDataflow
100% online courses

100% online courses

Start instantly and learn at your own schedule.
Flexible Schedule

Flexible Schedule

Set and maintain flexible deadlines.
Intermediate Level

Intermediate Level

Hours to complete

Approx. 1 month to complete

Suggested 14 hours/week
Available languages

English

Subtitles: English...

How the Specialization Works

Take Courses

A Coursera Specialization is a series of courses that helps you master a skill. To begin, enroll in the Specialization directly, or review its courses and choose the one you'd like to start with. When you subscribe to a course that is part of a Specialization, you’re automatically subscribed to the full Specialization. It’s okay to complete just one course — you can pause your learning or end your subscription at any time. Visit your learner dashboard to track your course enrollments and your progress.

Hands-on Project

Every Specialization includes a hands-on project. You'll need to successfully finish the project(s) to complete the Specialization and earn your certificate. If the Specialization includes a separate course for the hands-on project, you'll need to finish each of the other courses before you can start it.

Earn a Certificate

When you finish every course and complete the hands-on project, you'll earn a Certificate that you can share with prospective employers and your professional network.

how it works

There are 5 Courses in this Specialization

Course1

Google Cloud Platform Big Data and Machine Learning Fundamentals

4.6
3,851 ratings
731 reviews
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: • Google services are currently unavailable in China. Looking for the English version of this course? Check out https://www.coursera.org/learn/gcp-big-data-ml-fundamentals/ このコースの日本語版をお探しですか?https://www.coursera.org/learn/gcp-big-data-ml-fundamentals-jp/...
Course2

Leveraging Unstructured Data with Cloud Dataproc on Google Cloud Platform

4.5
1,918 ratings
238 reviews
This 1-week, accelerated course builds upon previous courses in the Data Engineering on Google Cloud Platform specialization. Through a combination of video lectures, demonstrations, and hands-on labs, you'll learn how to create and manage computing clusters to run Hadoop, Spark, Pig and/or Hive jobs on Google Cloud Platform. You will also learn how to access various cloud storage options from their compute clusters and integrate Google’s machine learning capabilities into their analytics programs. In the hands-on labs, you will create and manage Dataproc Clusters using the Web Console and the CLI, and use cluster to run Spark and Pig jobs. You will then create iPython notebooks that integrate with BigQuery and storage and utilize Spark. Finally, you integrate the machine learning APIs into your data analysis. Pre-requisites • Google Cloud Platform Big Data & Machine Learning Fundamentals (or equivalent experience) • Some knowledge of Python...
Course3

Serverless Data Analysis with Google BigQuery and Cloud Dataflow

4.5
1,445 ratings
156 reviews
This 1-week, accelerated on-demand course builds upon Google Cloud Platform Big Data and Machine Learning Fundamentals. Through a combination of instructor-led presentations, demonstrations, and hands-on labs, students learn how to carry out no-ops data warehousing, analysis and pipeline processing. Prerequisites: • Google Cloud Platform Big Data and Machine Learning Fundamentals • Experience using a SQL-like query language to analyze data • Knowledge of either Python or Java Google Account Notes: • Google services are currently unavailable in China....
Course4

Serverless Machine Learning with Tensorflow on Google Cloud Platform

4.4
1,192 ratings
170 reviews
This one-week accelerated on-demand course provides participants a a hands-on introduction to designing and building machine learning models on Google Cloud Platform. Through a combination of presentations, demos, and hand-on labs, participants will learn machine learning (ML) and TensorFlow concepts, and develop hands-on skills in developing, evaluating, and productionizing ML models. OBJECTIVES This course teaches participants the following skills: ● Identify use cases for machine learning ● Build an ML model using TensorFlow ● Build scalable, deployable ML models using Cloud ML ● Know the importance of preprocessing and combining features ● Incorporate advanced ML concepts into their models ● Productionize trained ML models PREREQUISITES To get the most of out of this course, participants should have: ● Completed Google Cloud Fundamentals- Big Data and Machine Learning course OR have equivalent experience ● Basic proficiency with common query language such as SQL ● Experience with data modeling, extract, transform, load activities ● Developing applications using a common programming language such Python ● Familiarity with Machine Learning and/or statistics Google Account Notes: • Google services are currently unavailable in China....

About 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....

Frequently Asked Questions

  • Yes! To get started, click the course card that interests you and enroll. You can enroll and complete the course to earn a shareable certificate, or you can audit it to view the course materials for free. When you subscribe to a course that is part of a Specialization, you’re automatically subscribed to the full Specialization. Visit your learner dashboard to track your progress.

  • This course is completely online, so there’s no need to show up to a classroom in person. You can access your lectures, readings and assignments anytime and anywhere via the web or your mobile device.

  • This Specialization doesn't carry university credit, but some universities may choose to accept Specialization Certificates for credit. Check with your institution to learn more.

  • This accelerated specialization is designed to be completed in only four weeks. Additionally, our Google Cloud Platform free trial ends after 60 days or when your $300 in credits are used up.

  • 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

  • We strongly recommend you take these courses in order, beginning with Big Data and Machine Learning Fundamentals. This is especially important when completing the Google Codelabs projects, as these hands-on labs build upon the work you complete in preceding courses.

  • Google Cloud Platform is used in a wide variety of environments, all the way from startups to global enterprises. This specialization is designed to help prepare you to implement solutions using Google Cloud Platform in any of these types of environments.

  • 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\n\nMore 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/

  • 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.

  • View this page for more details: https://cloud.google.com/free-trial/docs/

  • No, the certificate received is a Coursera coursework completion certificate and not an official Google Cloud certification. To receive a Google Cloud certification you need to pass a Google Cloud certification exam which must be taken in-person at an official testing center. More information available here: https://cloud.google.com/certification/

  • Taking courses is a great way to familiarize yourself with the various components of Google Cloud Platform; however, actual real-world, hands-on experience is the best preparation for certification. Combine these courses and work experience and you are on your way to certification.

More questions? Visit the Learner Help Center.