Data Engineering on Microsoft Azure Cloud Platform (3 Months)

Course Overview: This course provides hands-on training in data engineering using Microsoft Azure. You'll learn key tools and technologies, including SQL, Python, Azure Data Factory, Azure Databricks, Spark, and PySpark. The course is project-driven and prepares you for real-world data engineering roles.

Course Structure:

• Duration: 1.5-hour sessions on Saturdays and Sundays
• Total Sessions: 12 sessions monthly (including 1.5-hour weekly doubt-clearing session on Fridays)
• Project-Based Learning: All sessions include practical, project-driven activities.

Modules:

1. SQL & Python (Basic to Advanced) – 4 Sessions
   Learn SQL queries, advanced concepts, and Python for data engineering.

2. Azure & Big Data Services – 1 Session
   Introduction to Azure and key Big Data services (Azure Data Lake, Synapse).

3. Azure DevOps Setup – 1 Session
   Overview of Azure DevOps tools for CI/CD and project management.

4. Azure Data Factory (ADF) – 2 Sessions
   Set up ADF pipelines, data flows, and triggers for ETL tasks.

5. Azure Databricks – 2 Sessions
   Setup and use Databricks for data processing and analytics.

6. Spark Architecture & APIs – 1 Session
   Understand Spark's architecture and APIs for big data processing.

7. PySpark – 4 Sessions
   Work with RDDs, DataFrames, and optimization techniques in PySpark.

8. Final Project & Interview Readiness – 2 Sessions
   Complete a capstone project and prepare for data engineering interviews.

Additional Details:

• Doubt-Clearing Sessions: Weekly 1.5-hour sessions on Fridays.
• Azure Subscription: Students need their own Azure subscription for hands-on labs (costs borne by the student).
• Project-Driven Learning: From the second session onward, all activities focus on practical, real-world projects.

Certification: Upon completion, students will receive a Certificate of Completion validating their Azure data engineering skills.