About this course: 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/ Buscando la versión en español de este curso? Visita https://www.coursera.org/learn/gcp-big-data-ml-fundamentals-es/ 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/
Who is this class for: 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
| Basic Info | Course 1 of 5 in the Data Engineering on Google Cloud Platform Specialization |
| Level | Intermediate |
| Commitment | 1 week of study, 6-10 hours/week |
| Language | English, Subtitles: Japanese, Spanish |
| Hardware Req | You'll need a Google Cloud Platform Free Trial account. Sign up at: https://cloud.google.com/free/ |
| How To Pass | Pass all graded assignments to complete the course. |
| User Ratings |
- Reading: Please read me
- Video: Course Overview and Agenda
- Video: Getting Started with Google Cloud Platform and Qwiklabs
- Video: Meet Your Instructor
- Video: What is the Google Cloud Platform?
- Video: GCP Big Data Products
- Video: Usage Scenarios
- Video: Module Resources
- Video: CPUs On Demand
- Video: Lab Overview
- Video: Lab Review
- Video: A Global Filesystem
- Video: Lab Overview
- Video: Lab Review
- Video: Module Review
- Video: Module Resources
- Reading: Module Resources
- Video: Stepping Stones to Transformation
- Video: Your SQL Database in the Cloud
- Video: Lab Overview
- Video: Lab Review
- Video: Managed Hadoop in the Cloud
- Video: Lab Overview
- Video: Lab Review
- Video: Module Review
- Video: Module Resources
- Video: Fast Random Access
- Video: Warehouse and Interactively Query Petabytes with Google BigQuery
- Video: Ingesting data into BigQuery
- Video: Interactive, Iterative Development with Cloud Datalab
- Video: Cloud Datalab : Demo
- Video: Datalab supports BigQuery
- Video: Lab Overview
- Video: Lab Review : Setting up Datalab
- Video: Lab Review : Working in ipython notebook
- Video: Introduction
- Video: Machine Learning with TensorFlow
- Video: Training and creating a Neural Network Model : Part 1
- Video: Training and Creating a Neural Network Model (Part 2)
- Video: Lab Overview
- Video: Pre-built Machine Learning Models
- Video: Pre-built ML APIs : Examples
- Video: Lab Review
- Video: Module Review
- Video: Scaling Data Analysis : Resources
- Reading: Scaling Data Analysis : Resources
- Video: Machine Learning : Resources
- Video: Message-oriented Architectures
- Video: Serverless Data Pipelines
- Video: Module Review
- Reading: Module Resources
- Video: Next Steps
- Video: Additional Resources
- Reading: Additional Resources
Each course is like an interactive textbook, featuring pre-recorded videos, quizzes and projects.
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| Purchase Course | |
|---|---|
| Access to course materials | Available |
| Access to graded materials | Available |
| Receive a final grade | Available |
| Earn a shareable Course Certificate | Available |
Very nice tutorial to learn about GCP and ML fundamental and practical lab session to help us understand each components in GCP.
It was really a great course, I learned a lot and special thanks to instructor for helping in every possible aspects especially in labs part. Overall it was really a great experience.
The course was pretty deep and good learning experience.Some parts of the lab didn't work as expected.
SK
**UPDATE 08/14**
Bumping the score by a point due to great tech/customer support.
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The lab instructions could be clearer and the real time update of scores is not working for few of the labs that needs to be corrected. Content was good.