Google Cloud-Professional Data Engineer
With the Google Cloud Professional Data Engineer Training by Techpratham, you can learn how to process, store, and use machine learning solutions on GCP. This course will help you pass the Professional Data Engineer certification exam and make cloud apps that can grow and are based on data.
Level
Advanced
Duration
8 Weeks
Placement Client
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About Google Cloud-Professional Data Engineer
The Google Cloud Professional Data Engineer Training by Techpratham will help you become an expert at designing, building, and running data processing systems on GCP. You will learn how to use BigQuery, Dataflow, Pub/Sub, Cloud Storage, and machine learning to solve real-world data problems. This training focuses on making sure that data is reliable, scalable, secure, and follows the rules in business settings. It fully prepares you for the Google Cloud Professional Data Engineer certification exam and high-demand cloud data engineering jobs with hands-on labs and projects.
Training Plan
About trainer
Working professional who is carrying more then 10 years of industry experience.
Decks & Updated Content
Access to updated presentation decks shared during live training sessions.
e-Book
E-book provided by TechPratham. All rights reserved.
Assignments & MCQs
Module-wise assignments and MCQs provided for practice.
Video Recording
Daily Session would be recorded and shared to the candidate.
Projects
Live projects will be provided for hands-on practice.
Resume Building
Expert-guided resume building with industry-focused content support.
Interview Preparation
Comprehensive interview preparation with real-time scenario practice.
Google Cloud-Professional Data Engineer
Course Curriculum
Introduction to Data Engineering & GCP
Introduction to Data Engineering & GCP covers building, processing, and managing data pipelines using Google Cloud Platform services for scalable analytics.
Data Engineering Concepts
Data Engineering Concepts cover data ingestion, transformation, storage, and pipeline orchestration to enable reliable and scalable analytics systems.
Cloud Storage & Data Lake Design
Cloud Storage & Data Lake Design focus on organizing, storing, and managing large volumes of structured and unstructured data for scalable analytics.
BigQuery – Data Warehouse
BigQuery is Google Cloud’s fully managed data warehouse that enables fast SQL-based analytics on large-scale datasets.
Data Ingestion Methods
Data Ingestion Methods involve collecting data from multiple sources using batch, streaming, or real-time pipelines for processing and analytics.
Data Integration & ETL
Data Integration & ETL involve extracting data from sources, transforming it into usable formats, and loading it into target systems for analysis.
Google Cloud Courses
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Who Should Take Google Cloud-Professional Data Engineer
IT Professionals
Non-IT Career Switchers
Fresh Graduates
Working Professionals
Ops/Administrators/HR
Developers
BA/QA Engineers
Cloud / Infra
IT Professionals
Non-IT Career Switchers
Fresh Graduates
Key Projects
<h1><strong>Google Cloud-Professional Data Engineer</strong></h1>
Real-Time Data Pipeline with Pub/Sub and Dataflow
You will use Cloud Pub/Sub and Dataflow to build a pipeline that takes in and processes data in real time for this project. BigQuery will collect, change, and store streaming data so that it can be analyzed. This project focuses on scalability, fault tolerance, and an architecture based on events.
Big Data Analytics with BigQuery and Looker Studio
This project is all about using BigQuery to look at big datasets and Looker Studio to make interactive dashboards. You will use advanced SQL, optimize queries, and work with partitioned and clustered tables. The final dashboard will give you business intelligence insights and let you report on them in real time.
Machine Learning Integration with Vertex AI & BigQuery ML
You will use BigQuery ML and Vertex AI to train and deploy a machine learning model in this project. This will help you make predictions. You will put the model into a data pipeline so that it can make predictions automatically. This will show how AI can be used to make decisions in the cloud.
Placement Process
Live Class with Industry Use Cases
- Interactive learning
- Real-world examples
- Expert guidance
- Doubt resolution
Daily Assignment & Weekly Assessments
- Hands-on practice
- Concept reinforcement
- Weekly evaluation
- Timely feedback
Project Testing & Deployment
- Project development
- Testing practice
- Deployment exposure
- Portfolio creation
Interview Preparation (Mock, PD, Alumni Session)
- Mock interviews
- Personal development
- Alumni guidance
- Confidence building
Resume Building
- Resume crafting
- Industry-focused format
- Skills highlighting
- Professional presentation
Placement
- Job assistance
- Interview support
- Career guidance
- Opportunity access
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Industry-Recognized Certification
India
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Hyderabad Office
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