Leading Google Cloud Data Engineer Training Institute in Coimbatore
Leading Google Cloud Data Engineer Training – GCP Data Pipeline & Analytics Mastery
Course Overview
The Leading Google Cloud Data Engineer Training is a comprehensive, certification-focused program designed to equip learners with advanced skills in Google Cloud data services, big data processing, machine learning pipelines, and data warehouse solutions. This course is ideal for individuals aiming to become Google Cloud Professional Data Engineers or senior data architects building scalable data solutions on Google Cloud Platform.
Offered by Linux Training Center, Coimbatore, this program covers all Google Cloud Professional Data Engineer certification objectives while providing extensive hands-on experience with BigQuery, Dataflow, Pub/Sub, Cloud Storage, and AI/ML services, ensuring students gain both theoretical knowledge and practical implementation skills required for enterprise-level GCP data engineering roles.
Who Should Enroll?
- Data engineers seeking Google Cloud Platform specialization
- Software developers transitioning to data engineering roles
- Data analysts wanting to advance to data engineering positions
- Cloud engineers looking to specialize in data solutions
- Database professionals pursuing GCP data certifications
- Analytics professionals planning to work with big data on Google Cloud
Why This Course Stands Out
- Complete preparation for Google Cloud Professional Data Engineer certification
- Advanced hands-on labs with real-time data processing and analytics projects
- Enterprise-scale data pipeline design using Dataflow and Apache Beam
- Integration with machine learning services and AI Platform solutions
- Real-world scenarios covering data lake architecture and data governance
- GCP data security, monitoring, and cost optimization best practices
- Industry-standard ETL/ELT processes and streaming data solutions
Career Roles You Can Pursue
- Google Cloud Data Engineer
- Professional Data Engineer (GCP)
- Senior Data Architect
- Big Data Engineer
- Data Pipeline Specialist
- Analytics Engineer
- ML Data Engineer
- Cloud Data Solutions Architect
Why Choose Linux Training Center, Coimbatore?
- Google Cloud certified data engineering instructors with enterprise experience
- Dedicated GCP data lab with BigQuery, Dataflow, and ML platform access
- Flexible training schedules: weekday, weekend, and accelerated data bootcamp options
- Official Google Cloud study materials and Professional Data Engineer exam voucher included
- Real-time projects covering data ingestion, processing, storage, and visualization
- Mock exams, hands-on assessments, and comprehensive certification preparation
- Job placement assistance with data-focused companies and GCP consulting partners
- Post-training support with Google Cloud data engineering community access
Master Google Cloud’s powerful data platform with industry-leading certification training. This comprehensive course is your gateway to high-paying data engineering roles in the rapidly expanding GCP data ecosystem.
Data Engineer Syllabus
Modules
Chapter 1.
Introduction
Chapter 2.
Data Processing Fundamentals, Data Processing Concepts, Data Processing Pipelines
Chapter 3.
Storage and Databases, Introduction to Data Storage in GCP, Working with Data, Cloud Storage, Service Accounts, Cloud SQL, Creating a Cloud SQL Instance and Loading Data,
Cloud Firestore, Cloud Spanner, Working with Cloud Spanner, Cloud Memorystore, Comparing Storage Options
Chapter 4.
Big Data Ecosystem, MapReduce, Hadoop & HDFS, Apache Pig, Apache Spark, Apache Kafka
Chapter 5.
Pipelines with Cloud Dataflow, Dataflow Introduction, Pipeline Lifecycle, Dataflow Pipeline Concepts, Advanced Dataflow Concepts, Dataflow Security and Access, Using Dataflow
Chapter 6
Managed Spark with Cloud Dataproc, Dataproc Overview, Dataproc Basics, Working with Cloud Dataproc, Advanced Dataproc, Cloud Dataproc with the GCS Connector
Chapter 7
NoSQL Data with Cloud Bigtable, Bigtable Concepts, Bigtable Architecture, Bigtable Data Model, LAB: Working with Cloud Bigtable, Bigtable Schema Design, Bigtable Advanced Concepts, Loading and Querying Data with Cloud Bigtable
Chapter 8
Data Analytics with BigQuery, BigQuery Basics, Using BigQuery, Partitioning and Clustering, Best Practices, Securing BigQuery, BigQuery Monitoring and Logging, Machine Learning with BigQuery ML
Chapter 9
Orchestration with Cloud Composer, Cloud Composer Overview, Cloud Composer Architecture, Advanced Cloud Composer
Chapter 10
Introduction to Machine Learning, Machine Learning Introduction, Machine Learning Basics, Machine Learning Types and Models, Overfitting, Hyperparameters, Feature Engineering
Chapter 11
Machine Learning with TensorFlow, Deep Learning with TensorFlow, Introduction to Artificial Neural Networks, Neural Network Architectures, Building a Neural Network
