Data Engineering on GCP
Course Overview
This course will show participants how to design data processing systems, build end-to-end data pipelines, analyze data, and implement machine learning on Google Cloud. It covers structured, unstructured, and streaming data. At the end of this course, participants will be able to:
• Design and build data processing systems on Google Cloud
• Leverage unstructured data using Spark and ML APIs on Cloud Dataproc
• Process batch and streaming data by implementing autoscaling data pipelines on Cloud Dataflow
• Derive business insights from extremely large datasets using Google BigQuery
• Train, evaluate and predict using machine learning models using TensorFlow and Cloud ML
• Enable instant insights from streaming data
Audience Profile
This course is intended for experienced developers responsible for managing big data transformations including:
• Extracting, loading, transforming, cleaning, and validating data
• Designing pipelines and architectures for data processing
• Creating and maintaining machine learning and statistical models
• Querying datasets, visualizing query results and creating reports
Prerequisites
Participants should have:
• Completed Google Cloud Big Data and Machine Learning Fundamentals 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 as Python
• Familiarity with basic statistics
Course Outline
Course Outline
- Introduction to Data Engineering
- Building a Data Lake & Data Warehouse
- Introduction to Building Batch Data Pipelines
- Executing Spark on Cloud Dataproc
- Serverless Data Processing with Cloud Dataflow
- Manage Data Pipelines with Cloud Data Fusion and Cloud Composer
- Introduction to Processing Streaming Data
- Serverless Messaging with Cloud Pub/Sub
- Cloud Dataflow Streaming Features
- High-Throughput BigQuery and Bigtable Streaming Features
- Advanced BigQuery Functionality and Performance
- Introduction to Analytics and AI
- Prebuilt ML model APIs for Unstructured Data
- Big Data Analytics with Cloud AI Platform Notebooks
- Production ML Pipelines with Kubeflow
- Custom Model building with SQL in BigQuery ML & Cloud AutoML
COURSE INFORMATION
| Code | GDE2 |
| Duration | 4 Days |
| Full Price | RM 7,200 |
| Early Bird Price | RM 6,400 |