GCP Data Engineering (45-Day Plan)

1. Module 1: Introduction to Cloud Computing (2 Days)

2. Module 2: Introduction to Google Cloud Platform (GCP) (3 Days)

3. Module 3: SQL and Relational Database Systems with MySQL (3 Da)

4. Module 4: Python for Data Engineering (5 Days)

5. Module 5: Storage and Core GCP Services (6 Days)

6. Module 6: Data Warehouse Concepts and BigQuery (6 Days)

7. Module 7: Batch and Streaming Data (4 Days)

8. Module 8: Data Pipeline Orchestration (5 Days)

9. Module 9: Data Security and Privacy (2 Days)

10. Module 10: Data Visualization (2 Days)

11. Module 11: Advanced Data Engineering Concepts (4 Days)

12. Module 12: Final Wrap-Up (3 Days)

Syllabus in Detail for 45 Days

Module 1: Introduction to Cloud Computing (2 Days)

• Overview:

  • Who can learn this course

  • Introduction to Cloud Computing

  • Benefits of Cloud Computing

  • Roles and Responsibilities of Cloud Data Engineer

  • Overview of Cloud Platforms (GCP/AWS/Azure)

  • Comparison among the popular Cloud Platforms

  • Understanding cloud service providers

• Core Concepts:

  • IaaS, PaaS, SaaS

  • Google Compute Engine:

    • Virtual machine instances

    • Creating and managing VM instances

    • Networking and security

Module 2: Introduction to Google Cloud Platform (GCP) (3 Days)

• GCP Overview and Architecture

• Advantages of Google Cloud Platform

• Google Network Infrastructure: Points of Presence/Data Centers/Regions/Zones

• Setting up Individual Accounts on GCP

• Navigating the GCP Console

• GCP Project Management, Credits, and Billing

• Basic Linux Commands

• Accessing GCP Services:

  • Google Cloud Shell (Shell Scripting)

  • Google Cloud SDK

• Introduction to Key GCP Services:

  • BigQuery, DataProc, DataFlow, DataFusion, Cloud Composer, Cloud SQL, Cloud Functions

Module 3: SQL and Relational Database Systems with MySQL (3 Days)

• SQL Fundamentals

• DML and DDL Statements

• Queries and Sub-Queries

• Joins and Keys (Primary, Foreign, Unique)

• Aggregate Functions

• Windows Functions

• Introduction to Common Table Expressions (CTE)

Module 4: Python for Data Engineering (5 Days)

• Python Basics:

  • Syntax, Code Structure, Data Types, Collections (List, Tuple, Dictionary)

  • Operators, Conditional Statements, Loops, Functions, Exception Handling

  • File Operations

• Introduction to Pandas:

  • Data structures in Pandas (Series, DataFrames)

  • Operations on DataFrames

• Overview of Python Modules for Data Engineering

Module 5: Storage and Core GCP Services (6 Days)

• Introduction to Google Cloud Storage (GCS):

  • Create/Delete/Upload Buckets and Files using Web UI, gsutil, and Python

  • Handling multiple files in GCS using Python

  • Data Processing in GCS using Pandas

  • Data Conversions and Validation

• Overview of Cloud SQL, Bigtable, Datastore, and Data Lakehouse

Module 6: Data Warehouse Concepts and BigQuery (6 Days)

• Data Warehouse Basics:

  • Introduction to DWH (Data Warehouse)

  • OLTP vs. OLAP

  • Dimension and Fact Tables

• BigQuery Fundamentals:

  • CRUD Operations

  • Loading Data into BigQuery Tables

  • Partitioned and Clustered Tables

  • External Tables and Queries

  • Integration with Python

  • Advanced SQL in BigQuery

  • BigQuery Views and Materialized Views

Module 7: Batch and Streaming Data (4 Days)

• Introduction to Batch and Streaming:

  • Cloud Dataflow

  • Cloud Datafusion

  • Pub/Sub

  • Apache Kafka

Module 8: Data Pipeline Orchestration (5 Days)

• Introduction to Google Cloud Composer:

  • Airflow Basics and Architecture

  • Deploying and Running Airflow DAGs

  • Integration with Dataproc and BigQuery

  • Managing Variables and Job Dependencies

Module 9: Data Security and Privacy (2 Days)

• IAM Roles and Permissions

• Data Encryption and Key Management

• Data Privacy Regulations (GDPR, CCPA)

Module 10: Data Visualization (2 Days)

• Introduction to Google Data Studio and Looker Studio

• Data Visualization Techniques

Module 11: Advanced Data Engineering Concepts (4 Days)

• Big Data Fundamentals

• Hadoop Basics and Architecture

• ETL and ELT Concepts

Module 12: Final Wrap-Up (3 Days)

• Mock Interviews

• Resume Preparation

• Job Application Assistance

This curriculum provides a comprehensive foundation for aspiring Cloud Data Engineers, combining in-depth theoretical understanding with hands-on experience in leveraging GCP tools and technologies for data engineering excellence.