IT & SoftwareAdded Oct 3, 2026

Azure Data Engineering Masters: Build Scalable Solutions

Master Data Engineering with Azure: From Fundamentals to Real-World Projects in Spark, SQL, and Databricks

4.4 / 5.0
415 ratings
51h 27m 53s
On-demand
English
Audio
Satyajit Pattnaik, Praveen Kumar
Instructor
Azure Data Engineering Masters: Build Scalable Solutions100% OFF
  • 51h 27m 53s on-demand video
  • Certificate of Completion
  • Mobile, TV & Desktop Access
  • Full Lifetime Access

What you'll learn

Fundamentals of Data Engineering: Understand the core concepts, roles, and responsibilities within data engineering, including data lifecycle management.
SQL Proficiency: Master both basic and advanced SQL techniques for querying, data modeling, and optimizing database performance.
Python Programming: Gain hands-on experience in Python, focusing on essential programming concepts, data manipulation, and file handling.
Databricks & PySpark Skills: Learn to use Databricks for data processing and transformations with PySpark, including building efficient ETL pipelines.
Azure Services Expertise: Explore various Azure services, including Azure Data Factory, Azure Synapse, and Azure Storage, for data integration and analytics.
Data Visualization with Power BI: Create interactive dashboards and reports using Power BI, integrating data from multiple sources and leveraging AI tools.
Real-World Project Experience: Apply learned skills in practical projects that simulate industry scenarios, enhancing problem-solving and project management abi

Course Description

Embark on a transformative journey in data engineering with our comprehensive Azure Data Engineering Masters 2025 course. This program equips you with the essential skills to design, implement, and manage scalable data solutions using Microsoft Azure technologies.

Curriculum Highlights:

  1. Introduction to Data Engineering: Understand core concepts, the data lifecycle, and the differences between databases, pipelines, and cloud platforms. Explore the fundamental roles of data engineering and the significance of ETL processes.

  2. Spark Core: Gain in-depth knowledge of Apache Spark, its architecture, and core functionalities. Learn about RDDs, transformations, actions, and the execution of Spark applications.

  3. Spark SQL: Dive into the capabilities of Spark SQL, its features, and use cases. Master data manipulation using DataFrames and explore integration with Hive and other data sources.

  4. Spark Streaming: Discover real-time data processing with Spark Streaming. Learn about micro-batching, structured streaming, and how to build applications that handle live data streams.

  5. Python for Data Engineering: Build a solid foundation in Python with a focus on data structures, functions, and libraries like NumPy and Pandas. Understand how to visualize data using Matplotlib and Seaborn.

  6. SQL Basic and Advanced: Master SQL from installation to advanced querying techniques, including joins, window functions, and stored procedures. Learn to connect SQL with Python for enhanced data manipulation.

  7. Azure Cloud Fundamentals: Explore Azure's cloud services, including storage solutions, data integration with Azure Data Factory, and data processing using Databricks. Understand security and monitoring in the cloud environment.

  8. Complete Databricks with PySpark: Get hands-on experience with Databricks, learning about data ingestion, orchestration, and performance optimization. Engage in practical labs and projects to solidify your understanding.

  9. Capstone Projects: Apply your learning in real-world scenarios through comprehensive projects, including ADF pipelines, Databricks implementations, and CI/CD processes.

Join us to build a robust skill set in data engineering, preparing you for exciting opportunities in the rapidly evolving field of data analytics and cloud computing. Whether you're a beginner or looking to deepen your expertise, this course will empower you with the tools and knowledge to excel.

Who this course is for:

  • Aspiring Data Engineers: Individuals looking to start a career in data engineering and analytics.
  • IT Professionals: Current IT professionals seeking to upskill and transition into data engineering roles.
  • Data Analysts: Data analysts who want to deepen their technical skills and expand their knowledge of data engineering.
  • Students in Related Fields: University students studying computer science, information technology, or data science.
  • Business Analysts: Professionals interested in leveraging data engineering to enhance business insights and decision-making.
  • Career Changers: Individuals from non-technical backgrounds who are motivated to enter the data engineering field.
  • Anyone Interested in Azure Solutions: Those looking to understand and utilize Azure as a cloud service provider for data solutions.

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