Professional Data Engineer Certification Course

Professional Data Engineer Certification Course: Harness the Power of Google Cloud

This course equips you with essential skills to excel as a data engineer using Google Cloud technologies. Dive into data processing systems design, implementation, machine learning model operation, and solution quality assurance. Learn key SQL features for handling, querying, and performing operations on structured data in Google Cloud.

Section 1: Mastering Design of Data Processing Systems

• Storage Technology: Choosing the Right Option
• Data Pipeline: The Backbone of Data Flow
• Data Processing Solution: Designing for Efficiency
• Data Warehousing & Processing Migration: Seamless Transitions

Section 1 Videos

• Introductory Thoughts on Data Engineering
• Welcome to the Course!
• Deep Dive into BigQuery and Prompt Engineering
• Creating Pipelines with BigQuery and Colab
• Exploring Data with Google BigQuery
• Getting Onboard with Google Cloud Platform

Section 2: Building & Operationalizing Data Processing Systems

• Storage System: Implementing for Accessibility
• Pipeline Construction & Operationalization: Keeping the Data Flowing
• Processing Infrastructure: Building the Foundation of Your System

Section 2 Videos

• Course Introduction to Building and Operationalizing Systems
• Deep Dive into Google Cloud Analytics Services
• Understanding Data Engineering Pipelines
• Strategic Planning for Google Cloud Storage
• Overview of Google Cloud Storage Options
• Optimizing Database Solutions in Google Cloud Platform

Section 3: Operationalizing Machine Learning Models

• Pre-built ML Models as a Service: Easy and Effective Machine Learning
• ML Pipeline Deployment: Bringing Your Models to Life
• Training & Serving Infrastructure Selection: Laying the Groundwork for ML Success
• ML Model Measurement, Monitoring & Troubleshooting: Ensuring Peak Performance

Section 3 Videos

• Welcome to Operationalizing ML Models
• The Five Whys of Machine Learning
• Load Testing Demonstrations
• MLOps on Google Cloud Platform
• Using Google Courses for Success
• Harnessing TensorFlow with Google Colab
• Natural Language Processing with Google Cloud
• Deploying Pretrained Models with PyTorch
• Running Pretrained PyTorch Models in Rust
• Understanding TPUs: Your Guide to Google's Tensor Processing Units
• The Technology Transition of TPUs
• Getting Started with VertexAI
• Using the CLI for Google's Vision API

Section 4: Ensuring Solution Quality

• Security & Compliance Design: Protecting Your Data
• Scalability & Efficiency Assurance: Preparing for Growth
• Reliability & Fidelity Assurance: Trust in Your System
• Flexibility & Portability Assurance: Building for the Future

Section 4 Videos

• Introduction to Ensuring Solution Quality
• Energy Efficiency: Comparing Python and Rust
• Integrated Data Security: A Closer Look
• What is Distroless?
• Build & Deploy: Rust Microservice Cloud Run Demo
• App Engine Rust Deployment Demo
• Rust Crate Audits: Ensuring Security
• Rust: Secure by Design
• Enhancing Productivity with Bard
• Using Copilot with Rust
• Continuous Integration: Rust with GitHub Actions
• Unit Test: Rust Demo

• Master the design, build, and operationalization of data processing systems that meet business requirements, system requirements, and industry best practices.
• Develop scalable, efficient, and secure solutions with Google Cloud technologies to manage and analyze data at scale.
• Grasp the key syntax and features of the SQL language for handling, querying, and performing operations on structured data in Google Cloud.

Harness the power of Google Cloud and SQL to propel your career in data engineering. Enroll now to get started.

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