Master Python for data engineering with this full course! This video covers the essentials to kickstart your journey, from basic Python programming to deploying ETL pipelines and managing data quality. This course covers everything you need to know for data engineering with Python. Starting with an overview of data engineering roles, we set up the Python environment, explore core Python concepts, collections, and file handling. You'll learn data processing with Pandas, numerical computing with NumPy, and handling dates/times in ETL. We dive into API integration, object-oriented programming, and building ETL pipelines. Finally, we address data quality, testing, and deploying Python packages. Concluding with key takeaways and resources for further growth. Whether you're just starting or aiming to advance as a data engineer, this course provides essential skills and practical examples. ➡️ Full Notebook: ➡️Connect with me on LinkedIn: ➡️ Data Engineer Career Playlist: Timestamps: 0:00 Introduction 2:50 Setting Up the Python Environment 5:20 Python Basics for Data Engineering 13:00 Python Collections 18:05 File Handling in Python 22:40 Data Processing with Pandas 26:10 Numerical Computing with NumPy 26:10 Working with Dates and Times 33:00 Working with APIs and External Connections 37:40 Object Oriented Programming (OOP) 43:25 Building ETL Pipelines 46:50 Data Quality, Testing, and Code Standards 51:50 Building and Deploying Python Packages