Data Engineering for Beginner using Google Cloud & Python

🌟 Course Title: Basic Data Engineering: Python, Pandas, Google Cloud Platform (GCP) BigQuery, Spark on Dataproc, GCS, Data Warehouse 🌟

🚀 Course Headline: "Unlock the Power of Data with Python and Google Cloud!"

**"Data is the new oil". 🏭✨_

You've undoubtedly come across this mantra in the digital age. Just as oil fuels our world, data powers our economy. But raw data, much like crude oil, is seldom immediately useful. Its true value unfolds when it's meticulously and accurately gathered, intelligently connected with other pertinent datasets, and all of this done swiftly to inform decision-making processes.

As a budding data engineer, you'll design and construct the pipelines that refine raw data into a valuable, usable format. Subsequently, professionals like data scientists or machine learning engineers can leverage these clean, processed datasets to extract meaningful business insights.

Embarking on a career in data engineering requires a solid foundation in data literacy and hands-on experience. This course serves as your gateway into the world of data engineering, offering both theoretical knowledge and practical exercises to kickstart your journey.

🎓 Course Structure Overview:

In this course, we will dive into the fundamental aspects of data engineering, exploring:

• Introduction to Data Engineering: Gain a comprehensive understanding of what data engineering entails.
• Databases Explored: Delve into both relational and non-relational databases, comprehending their structures and uses.
• Data Modeling: Learn about the different data models, including how to normalize and denormalize data effectively for data warehousing.
• ETL Processes: Understand the Extract, Transform, Load (ETL) process and learn how to use Python and Pandas to manage data staging.
• Data Warehousing Basics: Explore the concepts of data warehousing, including fact and dimension tables, and their importance in data analysis.
• Elasticsearch & Numbers Every Engineer Should Know: Discover the basics of Elasticsearch and key numbers that every engineer should be familiar with to understand big data contexts.
• Big Data Technologies: Introduce yourself to Hadoop and learn how to set up a Spark cluster on Google Cloud Dataproc for handling big data tasks.
• Data Lakes & GCP Services: Grasp the concept of data lakes and learn how to utilize GCP services like BigQuery, GCS (Google Cloud Storage), and more for efficient data management.

📚 Important Notes:

• The world of data is vast! This course will evolve over time, with continuous updates to ensure you stay ahead of the curve in this fast-paced field.
• For Beginners: This course is tailored for those who are new to data engineering and eager to build a strong foundation.
• Programming Background Recommended: If you already have some programming experience, you'll find this course an excellent stepping stone into data engineering.
• Data Engineering Veterans: While this course is introductory, it's open to anyone with a passion for learning, even if you're an experienced data engineer.
• SQL & Python Prerequisites: This course assumes you have some knowledge of SQL and Python to fully grasp the concepts and exercises provided.

Embark on your journey into the fascinating field of data engineering today. With Google Cloud and Python as your tools, unlock the potential of big data and become a key player in transforming raw information into strategic insights. 🚀📊

Sign up now to start shaping the future of data!