ZeroToMastery – The Data Engineering Bootcamp: Zero to Mastery 2025-7

ZeroToMastery – The Data Engineering Bootcamp: Zero to Mastery 2025-7 Downloadly IRSpace

Aug 17, 2025 - 02:19 Updated: Aug 19, 2025 - 14:15

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ZeroToMastery – The Data Engineering Bootcamp: Zero to Mastery 2025-7

The Data Engineering Bootcamp: Zero to Mastery will introduce you to data engineering from the ground up. It will enable you to build real-time systems using Apache Kafka and Flink, implement data lakes on AWS, develop machine learning workflows with Spark, and integrate large language models (LLMs) into production-ready systems. The course is designed to kick-start your career as a forward-thinking data engineer. Data engineering has quickly become one of the most in-demand and fastest-growing careers in IT. The field is experiencing significant growth (25% to 50% year-over-year) as businesses across industries strengthen their data infrastructure to support AI, data analytics, and real-time applications. Last year alone, more than 20,000 new data engineering jobs were created, bringing the total job openings in North America to nearly 150,000; This is a clear sign of serious growth in this industry.

The earning potential for data engineers is equally impressive. Professionals in the U.S. earn an average base salary of $80,000 to $110,000 for entry-level roles, which can rise to $190,000 to $200,000 or more for senior positions. Data engineering plays a strategic role in modern technology; data engineers are the backbone of AI systems, machine learning models, and data analytics platforms, making them critical to modern product development and continuous innovation. This means that as the AI industry explodes, data engineering will grow in tandem. This has led to a significant talent shortage in the field, which in turn has led to higher salaries and greater flexibility in remote work. Compared to data science, data engineering is a less saturated yet faster-growing field, offering the potential for long-term career growth and job security.

What you will learn

Learn the real skills and tools used by data engineers and you will be in the top 10% in this field.
You build data stream processing systems with Apache Kafka and Apache Flink.
You create scalable, cloud-based data lakes on AWS using S3, EMR, and Athena.
You develop distributed processing jobs with Apache Spark and coordinate workflows with Apache Airflow.
You’ll prepare your skills for the future by learning how to integrate AI and machine learning, including using Spark ML and Large Language Models (LLM).
You build real, production-ready projects and pipelines using popular open source software.

This course is suitable for people who:

They are looking for comprehensive and efficient learning of data engineering from zero to one hundred.
They intend to work with real tools used in the industry.
They want to build real-time and scalable data systems.
Interested in integrating artificial intelligence and machine learning into data workflows.
Want to start or advance in a high-demand, high-income potential career in the technology field.
They are looking for a supportive environment to learn and exchange ideas with other students and professionals.
They want to learn from an industry expert who has hands-on experience at large companies like Amazon and Stripe.