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Data Engineering for Beginners with Hands-On Projects
Highest Rated
Rating: 4.8 out of 5(31 ratings)
104 students

Data Engineering for Beginners with Hands-On Projects

Master SQL, Python, ETL Pipelines, Big Data, Cloud Platforms, Apache Spark, Apache Airflow, and Snowflake with Projects!
Highest Rated
Created byHema Sundar Thulugu
Last updated 5/2026
English

What you'll learn

  • Master the fundamentals of Data Engineering including databases, SQL, ETL pipelines, data warehouses, and modern data architecture concepts
  • Build real-world data pipelines using Python, Apache Spark, Apache Airflow, and cloud platforms for processing and managing large-scale data efficiently.
  • Learn modern cloud data engineering tools and technologies such as Amazon Web Services, Snowflake, data lakes, and big data ecosystems used in the industry.
  • Develop practical industry-ready skills through hands-on projects, real-time data workflows, optimization techniques, and best practices

Course content

5 sections • 71 lectures • 29h 5m total length

  • Python Introduction10:41
  • What is Python in Data Engineering20:00
  • Project Structuring25:47

    Apply a basic extract, transform, and load flow within Airflow by iterating data items, transforming to uppercase, and printing loaded items, while wiring task dependencies.

  • Project Structuring Part - 222:20
  • Data Structures25:28

    Learn how the web server reads from the metadata database to display metadata, logs, tags, runs, and retries, without executing tasks, while workers distribute load for the salary executor.

  • Data Structures Part - 222:38

    Compare the local executor, a single-machine learning-friendly setup, with the production-grade salary executor using a scheduler, DAG plan, metadatabase, and a message broker to distribute tasks across workers.

  • Raw API Response in Python26:14
  • CSV Read and Write in Python27:12
  • Json in Python27:42

    Explore a data pipeline with extract, transform, and load tasks that execute in order only after success, with graph and tree views, UI triggers, and failure handling.

  • Function Flow in Data Engineering25:19
  • Non-idempotent in Python26:28
  • Pandas vs Spark vs SQL in Data Engineering27:32
  • Pandas Generate27:32
  • Pandas Clean22:47
  • Exception Flow in Python24:01
  • Exception Files in Python25:58
  • Log Levels in Python26:46
  • Python - Snowflake Flow26:28
  • Snowflake Demo25:19
  • REST Basics in Python26:46
  • Class Structure26:14
  • Data Pipeline in Data Engineering25:12
  • Load Data in Data Engineering23:38
  • Pipeline Config in Python29:37
  • Multithreading vs Multiprocessing34:33

Requirements

  • You do not need any experience

Description

Data Engineering for Beginners with Hands-On Projects is a practical and beginner-friendly course designed to introduce students to the exciting world of modern data engineering. This course is perfect for anyone who wants to learn how data is collected, processed, transformed, and managed in real-world organizations. Whether you are a student, aspiring Data Engineer, software developer, data analyst, or IT professional, this course will help you build a strong foundation in data engineering using simple explanations and practical projects.

The course starts with the fundamentals of databases, SQL, and data processing concepts. You will learn how modern companies store and manage massive amounts of data using relational databases and cloud-based systems. Step-by-step, you will understand important concepts such as ETL pipelines, data warehouses, data lakes, and big data processing. Even if you have no prior experience in data engineering, the course is structured to help you learn comfortably from scratch.

You will also learn Python programming for data engineering tasks, including data manipulation, automation, and file processing. The course introduces industry-standard tools and technologies such as Apache Spark for big data processing, Apache Airflow for workflow management, and Snowflake for cloud-based data warehousing. In addition, you will gain exposure to cloud platforms like Amazon Web Services and understand how modern cloud data systems work.

By the end of this course, you will have a clear understanding of data engineering fundamentals, practical project experience, and the confidence to work with modern data tools and technologies. You will be ready to continue learning advanced concepts, build your own projects, and begin preparing for entry-level Data Engineering roles in the technology industry.

Who this course is for:

  • Everyone who wants to master Data Engineering concepts and become a data engineer

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