Transform Your Career with Data Engineering Mastery

Enroll now in this Free Udemy Course to become a Data Engineering expert!

The Certified Data Engineering & Pipelines course is designed for those who want to dive deep into the world of data engineering. This comprehensive program guides you through foundational concepts to advanced data engineering practices. With a focus on modern cloud-native solutions, you’ll gain hands-on experience in deploying and managing complex data pipelines capable of handling petabytes of data efficiently and reliably.

What sets this course apart is its unique approach to the data project lifecycle. You’ll explore and integrate essential tools such as Python, SQL, Apache Spark, and various cloud services (AWS/GCP), all within a structured pipeline orchestration framework using Apache Airflow. Rather than simply understanding what these tools do, you will learn how to weave them into scalable, industry-standard ETL/ELT solutions, ensuring you are well-prepared for certification and real-world data challenges.

Throughout the course, we focus on three core areas: pipeline orchestration with Airflow, data processing and transformation with Spark and cloud services, and cloud data infrastructure development. By the end, you’ll have effectively created a portfolio-ready project that showcases your ability to design, deploy, and maintain robust data pipelines—unlocking doors to top roles in data engineering.

What you will learn:

  • Design and manage complex data pipelines using Apache Airflow.
  • Utilize PySpark for processing and transforming large datasets.
  • Build scalable cloud data infrastructure using AWS and GCP.

Course Content:

  • Sections: 15
  • Lectures: 75
  • Duration: 30 hours

Requirements:

  • Basic understanding of programming and databases
  • Familiarity with data handling concepts

Who is it for?

  • Aspiring Data Engineers seeking structured, practical training and a comprehensive certification path.
  • Existing Data Analysts or BI Developers looking to transition into a Data Engineering role.
  • Software Developers who want to specialize in building backend data systems and ETL processes.

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