Overview
This Serverless Data Processing with Dataflow course is offered by Coursera in partnership with Google Cloud.
What you'll learn
Demonstrate how Apache Beam and Cloud Dataflow work together to fulfill your organization’s data processing needs
Write pipelines and advanced components such as utility functions, schemas, and watermarks.
Perform monitoring, troubleshooting, testing and CI/CD on Dataflow pipelines.
Deploy Dataflow pipelines with reliability in mind to maximize stability for your data processing platform
Skills you'll gain
- Google Cloud Platform
- Big Data
- Cloud Computing
- Computer Architecture
- Data Management
- DevOps
- Distributed Computing Architecture
Programme Structure
Courses included:
- Serverless Data Processing with Dataflow: Foundations
- Serverless Data Processing with Dataflow: Develop Pipelines
- Serverless Data Processing with Dataflow: Operations
Key information
Duration
- Part-time
- 1 months
- 10 hrs/week
Start dates & application deadlines
Language
Delivered
Campus Location
- Mountain View, United States
Disciplines
Data Science & Big Data Data Analytics View 176 other Short Courses in Data Analytics in United StatesWhat students do after studying
Academic requirements
We are not aware of any specific GRE, GMAT or GPA grading score requirements for this programme.
English requirements
We are not aware of any English requirements for this programme.
Other requirements
General requirements
- Intermediate level
- Recommended experience: Basic understanding of Java or Python programming language
Tuition Fees
Additional Details
Course is free for the first 7 days. After 7 days, the course can be accessed with the Coursera Plus Subscription
Funding
Coursera provides financial aid to learners who cannot afford the fee. Apply for it by clicking on the Financial Aid link beneath the "Enroll" button on the left. You'll be prompted to complete an application and will be notified if you are approved. You'll need to complete this step for each course in the Specialization, including the Capstone Project.