Udemy – Data Engineering Bootcamp – Series 1 2025-7

Udemy – Data Engineering Bootcamp – Series 1 2025-7 Downloadly IRSpace

Aug 17, 2025 - 02:45 Updated: Aug 19, 2025 - 14:40

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Udemy – Data Engineering Bootcamp – Series 1 2025-7

Data Engineering Bootcamp – Series 1. This is a hands-on, project-based course designed to teach data engineering concepts using modern platforms. As a first step into the data engineering field, this course is taught by a data architect with 11 years of industry experience and offers a mix of theory and practical topics. Participants will include data engineers, software engineers, analysts, and those interested in building real-world data pipelines. Topics include designing scalable data lakes, building dimensional data models, implementing data quality frameworks, and orchestrating pipelines using Apache Airflow. All of these concepts are simulated through a hands-on project based on an online taxi app to give learners hands-on experience working with enterprise systems.

What you will learn

Modern Data Engineering Fundamentals: You will gain a comprehensive understanding of the core concepts of modern data engineering, including data platforms, OLTP systems, and real-world data platform architectures.
Building and Managing Scalable Data Lakes: You will learn how to build and manage scalable data lakes on AWS S3, considering architecture, partitioning, tiers, and schema evolution.
Designing Star Data Models (Star Schema): You will master Star Schema design and implement SCD Type 1 and SCD Type 2 dimensions.
Developing an ETL pipeline with PySpark: You develop an ETL pipeline using PySpark and use production patterns such as WAP (Write-Audit-Publish).
Querying and Exploring Data Lakes with AWS Athena: You will learn how to query and explore massive datasets using AWS Athena and Glue Catalog.
Workflow automation with Apache Airflow: Automate workflows and pipelines using Airflow and custom plugins, and manage task dependencies.
Implement data quality frameworks: Ensure the accuracy, completeness, and consistency of data by implementing data quality checks and using data contracts.
Data Workflow Optimization: You will learn how to optimize data workflows for cost, performance, and reliability.
Prepare for data engineering interviews: By gaining hands-on experience on real use cases, you will confidently prepare for data engineering interviews.

This course is suitable for people who:

Aspiring data engineers: People looking to enter this field.
Software engineers or analysts: People who want to transition into data-related roles.
Professionals: People looking to gain practical, real-world experience in data engineering.
Interested in: Anyone interested in mastering modern data engineering platforms.