8 hours ago
[center]![[Image: 114e73e8bd6e0b8cb59dd3b0cb041f56.jpg]](https://i127.fastpic.org/big/2026/0515/56/114e73e8bd6e0b8cb59dd3b0cb041f56.jpg)
Azure Data Engineering For Beginners
Published 5/2026
MP4 | Video: h264, 1920x1080 | Audio: AAC, 44.1 KHz, 2 Ch
Language: English | Duration: 5h 31m | Size: 8.35 GB[/center]
Azure Cloud, ADF, Databricks
What you'll learn
Students will learn to build and manage data pipelines, perform data ingestion and transformation, work with cloud platforms, understand ETL processes, and use
Will develop a strong foundation in data engineering concepts, including understanding the role of a data engineer within modern data ecosystems.
Identify risks like data quality issues, pipeline failures, and security gaps. Assess impact, implement monitoring, ensure backups, apply governance
will gain practical experience in processing and transforming datasets using Azure Databricks and PySpark. They will learn how to write eff
Requirements
Basic understanding of databases, SQL, and data concepts is helpful but not mandatory. Familiarity with any programming language (preferably Python) will be an advantage. Learners should have access to a laptop/desktop with internet connectivity and willingness to learn cloud technologies. No prior experience in Azure is required, as all concepts will be taught from scratch.
Description
This comprehensive Data Engineering course is designed to take you from beginner to professional level with real-world, hands-on projects. You will learn how to build scalable data pipelines, perform data ingestion, transformation, and loading using modern tools and cloud technologies.
The course covers Azure Data Factory, Databricks, ADLS, and Azure SQL in a practical, project-based approach. You will also understand ETL processes, data modeling, workflow automation, Delta Lake concepts, data governance, Unity Catalog, and cloud-based data engineering fundamentals used in enterprise environments.
You will work on multiple real-time projects including API ingestion, CSV processing, data lake implementation, batch and streaming pipelines, data transformation using PySpark, and loading curated data into analytical platforms for reporting and business insights. The course also includes hands-on exercises, architecture understanding, pipeline orchestration, monitoring, optimization techniques, security implementation, performance tuning, troubleshooting strategies, deployment approaches, cost optimization methods, disaster recovery concepts, scalable solution design, and best practices followed in modern enterprise-level data engineering projects across cloud environments.
By the end of this course, you will be able to design end-to-end data solutions, handle real-time and batch data, optimize data workflows, and confidently work as a Data Engineer in modern cloud environments with industry-level practical knowledge and implementation experience.
Who this course is for
This course is designed for aspiring data engineers, software developers, and IT professionals who want to transition into data engineering roles. It is also suitable for beginners looking to build a strong foundation in cloud-based data technologies. Data analysts and BI professionals aiming to upskill with modern tools will benefit as well. Anyone interested in learning end-to-end data pipelines using Azure services will find this course valuable.
Azure Data Engineering For Beginners
Published 5/2026
MP4 | Video: h264, 1920x1080 | Audio: AAC, 44.1 KHz, 2 Ch
Language: English | Duration: 5h 31m | Size: 8.35 GB[/center]
Azure Cloud, ADF, Databricks
What you'll learn
Students will learn to build and manage data pipelines, perform data ingestion and transformation, work with cloud platforms, understand ETL processes, and use
Will develop a strong foundation in data engineering concepts, including understanding the role of a data engineer within modern data ecosystems.
Identify risks like data quality issues, pipeline failures, and security gaps. Assess impact, implement monitoring, ensure backups, apply governance
will gain practical experience in processing and transforming datasets using Azure Databricks and PySpark. They will learn how to write eff
Requirements
Basic understanding of databases, SQL, and data concepts is helpful but not mandatory. Familiarity with any programming language (preferably Python) will be an advantage. Learners should have access to a laptop/desktop with internet connectivity and willingness to learn cloud technologies. No prior experience in Azure is required, as all concepts will be taught from scratch.
Description
This comprehensive Data Engineering course is designed to take you from beginner to professional level with real-world, hands-on projects. You will learn how to build scalable data pipelines, perform data ingestion, transformation, and loading using modern tools and cloud technologies.
The course covers Azure Data Factory, Databricks, ADLS, and Azure SQL in a practical, project-based approach. You will also understand ETL processes, data modeling, workflow automation, Delta Lake concepts, data governance, Unity Catalog, and cloud-based data engineering fundamentals used in enterprise environments.
You will work on multiple real-time projects including API ingestion, CSV processing, data lake implementation, batch and streaming pipelines, data transformation using PySpark, and loading curated data into analytical platforms for reporting and business insights. The course also includes hands-on exercises, architecture understanding, pipeline orchestration, monitoring, optimization techniques, security implementation, performance tuning, troubleshooting strategies, deployment approaches, cost optimization methods, disaster recovery concepts, scalable solution design, and best practices followed in modern enterprise-level data engineering projects across cloud environments.
By the end of this course, you will be able to design end-to-end data solutions, handle real-time and batch data, optimize data workflows, and confidently work as a Data Engineer in modern cloud environments with industry-level practical knowledge and implementation experience.
Who this course is for
This course is designed for aspiring data engineers, software developers, and IT professionals who want to transition into data engineering roles. It is also suitable for beginners looking to build a strong foundation in cloud-based data technologies. Data analysts and BI professionals aiming to upskill with modern tools will benefit as well. Anyone interested in learning end-to-end data pipelines using Azure services will find this course valuable.
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