Free Download Data Engineering 101 The Beginner’s Guide
Published 4/2024
Created by Seungchan Lee
MP4 | Video: h264, 1280×720 | Audio: AAC, 44.1 KHz, 2 Ch
Genre: eLearning | Language: English | Duration: 48 Lectures ( 3h 47m ) | Size: 1.42 GB
Master Modern Data Engineering Fundamentals
What you’ll learn:
Get an intuitive understanding of data engineering
Understand the most critical concepts in data engineering
Learn what the end-to-end data pipeline is comprised of and what each part of the pipeline does
Solidify your understanding with example end-to-end data pipeline architectures for the most popular use cases
Requirements:
No prior knowledge of data engineering required. You’ll learn everything you need to know.
No programming experience required.
Description:
Master Modern Data Engineering FundamentalsAre you curious about data engineering but unsure where to start?Are you a software engineer, data scientist, or data analyst who wants to learn more about modern data engineering?Dive into our intro course where we demystify the complexities of the field and give you a solid foundation in modern data engineering.This course is tailored specifically for those who are new to the field, providing a clear and concise introduction to the essential concepts and tools used in modern data engineering today.What You’ll Learn:What Exactly Is Data Engineering? Understand the core concept of data pipelines and the role of data engineering in a wider data team.End-to-end data pipeline: Explore each part of the end-to-end data pipeline from data generation, storage, ingestion, transformation, and serving. Learn how data flows from creation to consumption.Critical Data Engineering Concepts: Learn the most important concepts in data engineering, such as data warehouse vs data lakehouse, row-based vs column-based data stores, ELT vs ETL and more.Introduction to Modern Data Engineering Tools: See how modern data tools like Dagster, Trino, DBT, and Apache Iceberg are used to build out the end-to-end data pipelines.Modern Data Stack Architecture Examples: Get a solid introduction to the tools and technologies that data engineers use to architect end-to-end modern data pipelines for the four most common use cases: 1) Business analytics, 2) Streaming, 3) ML, and 4) Deep Learning.Who Should Take This Course:Beginners curious about building a career in data engineering.Data professionals like Data Scientists or Data Analysts seeking to understand the fundamentals of modern data engineering.Anyone who wants to learn about what role Data Engineering plays in data-driven businesses.Why Take This Course?This course is designed as a gentle introduction to the field of data engineering. It breaks down data engineering into clear sections within a data pipeline so you can see what data engineering is all about.You will leave with a clear understanding of what data engineering is and a solid foundation to further explore more advanced topics or actually build out the modern data stack.What This Course Is NOT:Before you take this course, you should know what this course is NOT. This course is NOT a tutorial. So if you’re expecting to learn about how to set up and use tools like Spark or Airflow, or write SQL statements, this is not the course for you.There’s no docker setup, there’s no tool installations, and there’s no coding.If you’re looking for that kind of tutorial course, take a look at our more advanced data engineering courses where we walk you through how to actually build end-to-end data pipelines using cutting-edge open-source tools.Join us on this exciting journey to discover the fundamentals of data engineering. Whether you’re planning a career shift or just looking to broaden your technological horizons, this course will provide you with the knowledge and tools you need to succeed.Ready to transform the way you see data? Join the course and let’s get started!
Who this course is for:
Beginners curious about building a career in data engineering.
Data professionals like Data Scientists or Data Analysts seeking to understand the fundamentals of modern data engineering.
Anyone who wants to learn about what role Data Engineering plays in data-driven businesses.
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