Azure Data Engineering Training

Learn from industry experts with real-world projects, mentorship, and career-focused programs.

A small group of people are gathered in a modern conference room. One person stands by a whiteboard presenting a diagram labeled 'UGC Types', while the others are seated around a wooden table with laptops and papers. A large screen on the wall displays content related to the presentation.

A small group of people are gathered in a modern conference room. One person stands by a whiteboard presenting a diagram labeled 'UGC Types', while the others are seated around a wooden table with laptops and papers. A large screen on the wall displays content related to the presentation.

This comprehensive training is designed to enhance your skills in Azure Data Engineering, helping you advance your career. Throughout the course, you'll work on real-world projects and gain hands-on experience in Azure Data Engineering. We start from the basics, so no prior knowledge is required.

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Detailed course topics

Module 1: Introduction to Data Engineering

Overview of Data Engineering and its importance.
Key tools and technologies in the data engineering ecosystem.
Understanding the data lifecycle.

Module 2: Python for Data Engineering

Python fundamentals for data manipulation.
Working with libraries like Pandas, NumPy, and CSV.
Writing reusable scripts for data processing.

Module 3: SQL for Data Analysis

Basics of SQL: SELECT, JOIN, GROUP BY, etc.
Advanced SQL: CTEs, window functions, and optimization techniques.
Writing SQL queries for ETL workflows.

Module 4: PySpark for Big Data Processing

Introduction to distributed computing.
Setting up and using Apache Spark with Python (PySpark).
Writing transformations and actions in PySpark.
Optimizing Spark jobs.

Module 5: Hive and Data Warehousing

Fundamentals of Hive and its architecture.
Creating and managing Hive tables.
Querying data with HiveQL.
Integrating Hive with other tools in the ecosystem.

Module 6: ETL Concepts and Frameworks

Understanding ETL (Extract, Transform, Load) processes.
Designing efficient ETL pipelines.
Hands-on with popular ETL tools.
Best practices in ETL development.

Module 7: Capstone Project

Real-world data engineering project.
Building end-to-end pipelines.
Data processing, storage, and reporting

Bonus: Interview Prep and Career Guidance.

This outline ensures participants gain theoretical knowledge and practical skills in data engineering.

Azure Data Engineering Training
Fees: ₹19,999/-

Live Session Timing: 8:00AM, IST

Batch starting soon

Download syllabus