Data Engineering Bootcamp (Udemy.com)
Learn Data Engineering basics: data architecture, ETL vs ELT, cloud pipelines, and workflow orchestration
Created by: Navid Shirzadi
Last updated July 2026
What you will 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
How it compares
Against the other 1,182 rated Udemy courses in IT & Software on CourseDuck:
- Rating4.4 out of 5higher than 30% of them
- Reviews362#659 of 1,183 by number of reviews
- Length9.3 hourslonger than 68% of them
- Last updatedJuly 2026more recently than 82% of them
Course 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.
Instructor Details
- 4.4 Rating
362 Reviews
Navid Shirzadi
Welcome! I'm Navid Shirzadi, and I'm thrilled you're here.
I’m an Applied Scientist with a Ph.D. in Engineering and over a decade of experience working with integrated energy systems, optimization, and intelligent control strategies. My background spans mathematical optimization, advanced control, and hybrid modeling techniques that blend physics‑based simulations with modern AI.
I’m deeply experienced in Python, and I build cutting‑edge machine learning, deep learning, and agentic AI models for real‑world applications. My recent work focuses on leveraging agentic AI workflows and LLM‑powered tools to automate and enhance building energy modeling, EnergyPlus pipelines, and large‑scale simulation tasks.
Throughout my career, I’ve published research on intelligent control strategies for energy systems and developed AI‑driven methods that improve efficiency, reliability, and decision‑making. My passion lies in teaching these concepts in a clear, practical, and intuitive way, helping learners build skills they can immediately apply in engineering, data science, and AI‑driven modeling.
I’m excited to share my knowledge and help you grow your expertise in AI, optimization, and energy systems.
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Reviews
By Tsholofelo Sebigi on 9/7/2026
Liked the explanations and the steps shown to us throughout the session. It really takes you from the ground up. Towards the end felt like it was rather fast but I guess Containerisation does not need as much attention compared to the other parts.
By Manuel Perez on 8/6/2026
Great content with clear progression and excellent delivery
By Sudhansu Sekhar Rout on 6/26/2026
Half a way through the course! So far enjoying it.
By R G on 4/24/2026
Pretty good course. Good examples through out. I liked that the instructor made mistakes while typing which forced a debug session. Seeing how he resolved the issues is always helpful. 4/5 because I would like to see more detail regarding containerization and a full on cloud example. But this may not have been his intent for the course. Overall very good.
By Wise Mawusinu Jnr. Ofori on 2/2/2026
Very hands on and practical with real world experiences. It was a great course
By Prasad Tare on 1/8/2026
Need improvement in terms of perspective
By Gabriele K on 1/4/2026
It was a great project, a bit too many typos, but overall I'm happy taking this course.
By Maria Kuziela on 12/1/2025
Interesting, like the way the course is conducted. Leading in programming is really helpful.
By Khaja Aleemuddin on 11/15/2025
Great course for beginners who want to start data engineering journey and start working on hands-on projects. All steps are explained in a simple manner.
By Leo S on 10/27/2025
The course gave me a simple and clear introduction to data engineering, and I feel more confident now about how data pipelines work!
Quality Score
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Overall Score : 88 / 100












