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Ultimate Data Engineering for Beginners to Advanced
Highest Rated
New
Rating: 4.9 out of 5(34 ratings)
72 students

Ultimate Data Engineering for Beginners to Advanced

Master SQL, Python, ETL Pipelines, Big Data, Cloud Platforms, Apache Spark, Apache Airflow, and Snowflake with Projects!
Highest Rated
New
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 to become a Data Engine

Course content

4 sections • 59 lectures • 24h 12m total length

  • Python Introduction10:41

    Explore the six-phase dbt master class, starting with production setup and runtime. Learn core modeling principles, testing and quality enforcement, yaml documentation, observability, performance engineering, and environment strategy.

  • What is Python in Data Engineering20:00
  • Project Structuring25:47
  • Project Structuring Part - 222:20
  • Data Structures25:28

    Define the dag and its state in the metadata database as the scheduler orchestrates runs and writes task states, and describe executors (local, celery, kubernetes, sequential).

  • Data Structures Part - 222:38
  • Raw API Response in Python26:14
  • CSV Read and Write in Python27:12
  • Json in Python27:42

    Trace dag execution from backfill to failure by viewing audit and task logs, observe an exception causing three attempts with two retries, and learn to trigger, pause, and delete dags.

  • 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

The Ultimate Data Engineering for Beginners to Advanced course is a complete and practical program designed to help students, software professionals, and aspiring data engineers master the most in-demand data engineering skills used in modern industries. This course takes you step-by-step from the fundamentals of data engineering to advanced real-world implementations using industry-standard tools and technologies. Whether you are a complete beginner or an experienced professional looking to upgrade your skills, this course provides a strong foundation and hands-on experience to build modern data solutions with confidence.

In this course, you will start by learning the core concepts of databases, data warehouses, data lakes, and data architecture. You will gain a deep understanding of SQL, relational databases, and data modeling techniques that are essential for designing efficient and scalable data systems. The course also introduces Python programming for data engineering, enabling you to automate workflows, process data efficiently, and build powerful ETL pipelines.

you will explore modern big data technologies and cloud-based data engineering platforms widely used in the industry. You will work with tools such as Apache Spark for distributed data processing, Apache Airflow for workflow orchestration, and Snowflake for cloud data warehousing. You will also learn how to integrate cloud services from Amazon Web Services and other modern cloud ecosystems to create scalable and reliable data pipelines.

The course focuses heavily on practical learning through hands-on projects, real-world datasets, and industry-oriented assignments. You will build complete ETL and ELT pipelines, perform batch and real-time data processing, optimize query performance, and understand best practices for handling large-scale data systems. By working on real projects, you will develop the confidence and experience needed to solve real business problems using modern data engineering techniques.

By the end of this course, you will have the skills required to design and build scalable data pipelines, work with cloud platforms and big data technologies, and confidently apply for Data Engineering roles in top companies. You will also gain valuable experience with modern tools, workflows, and projects that will strengthen your resume and help you stand out in the competitive technology industry.

Who this course is for:

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

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