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Data Engineering Bootcamp
Rating: 4.5 out of 5(289 ratings)
2,473 students

Data Engineering Bootcamp

Learn Data Engineering basics: data architecture, ETL vs ELT, cloud pipelines, and workflow orchestration
Last updated 5/2026
English

What you'll learn

  • Understand core data engineering concepts
  • Apply data architecture principles
  • Build cloud-based data pipelines
  • Process and transform data for analytics
  • Orchestrate and automate workflows
  • Complete an end-to-end data engineering project

Course content

8 sections50 lectures9h 20m total length
  • Course Content6:14

    Master end-to-end data engineering with a hands-on ETL project, learning ETL vs ELT, data ingestion with AWS S3, data lake vs data warehouse, and orchestration with Prefect and Docker.

  • Course Information3:34

    Explore data engineering fundamentals in a structured bootcamp, coding along in Python from requirements and installation to basic concepts and a final exercise, with practical debugging steps.

  • Source Files1:03

Requirements

  • No prior data engineering experience required
  • Basic programming knowledge
  • Fundamental understanding of data

Description

Data is the new oil—but without the right systems to collect, store, and process it, data quickly becomes unusable. That’s where data engineering comes in. This Data Engineering Bootcamp is designed to take you from foundational concepts to a complete, hands-on project where you’ll build and deploy an end-to-end data pipeline.

We’ll start with the basics of data engineering, exploring what it is, how it differs from roles like analysts and scientists, and why it’s such a critical skill in today’s data-driven world. You’ll learn about the data engineering workflow, data roles, and real-world scenarios through interactive quizzes and activities.

Next, we’ll dive into data architecture—comparing traditional vs. modern approaches, understanding data storage paradigms, and exploring ETL vs. ELT and batch vs. streaming pipelines. You’ll put your knowledge into practice with worksheets and design exercises that reinforce key concepts.

The highlight of the course is the hands-on project, where you’ll:

  • Ingest raw data into an AWS S3 data lake

  • Process and transform datasets for analytics

  • Organize and store results in multiple formats

  • Orchestrate workflows with Prefect for automation, scheduling, and monitoring

By the end of this course, you’ll not only understand the theory but also gain practical, job-ready experience in building cloud-based data pipelines. Whether you’re an aspiring data engineer, a data analyst looking to level up, or a career changer entering the data field, this bootcamp will give you the confidence and skills to succeed.

Who this course is for:

  • Aspiring data engineers who want to break into the field and learn modern tools and workflows from scratch.
  • Data analysts or scientists who want to strengthen their knowledge of data pipelines, architecture, and cloud data. workflows.
  • Software engineers or IT professionals looking to transition into data engineering roles.
  • Students and career changers eager to gain hands-on experience with real-world projects in data engineering.