Kennedy Behrman

Throughout this course, you'll explore virtualization, containerization, and Kubernetes, mastering the very tools that power data engineering in the industry. Each week presents a new set of tools and platforms that are indispensable in data engineering. From mastering Docker and Kubernetes to exploring advanced topics such as AI-driven coding [...]

This is primarily aimed at first- and second-year undergraduates interested in engineering or science, along with high school students and professionals with an interest in programming. Gain the skills for building efficient and scalable data pipelines.

In this fourth course of the Python, Bash and SQL Essentials for Data Engineering Specialization, you will build upon the data engineering concepts introduced in the first three courses to apply Python, Bash and SQL techniques in tackling real-world problems.

In this second course of the Python, Bash and SQL Essentials for Data Engineering Specialization, you will learn the fundamentals of Linux necessary to perform data engineering tasks. Additionally, you will explore how to use both Bash and zsh configurations, and develop the syntax needed to interact and control [...]

In this third course of the Python, Bash and SQL Essentials for Data Engineering Specialization, you will explore techniques to work effectively with Python and SQL. We will go through useful data structures in Python scripting and connect to databases like MySQL. Additionally, you will learn how to use [...]

In this first course of the Python, Bash and SQL Essentials for Data Engineering Specialization, you will learn how to set up a version-controlled Python working environment which can utilize third party libraries. You will learn to use Python and the powerful Pandas library for data analysis and manipulation. [...]

Gain the skills for building efficient and scalable data pipelines. Explore essential data engineering platforms (Hadoop, Spark, and Snowflake) and learn how to optimize them using Python, PySpark, and MLflow.

Master virtualization, Docker, and Kubernetes for data engineering. Gain hands-on experience with cloud development environments, container orchestration, and production best practices.

Learn to build web apps, microservices, and command-line tools for efficient data engineering using Python, FastAPI, and Rust.

Master Python essentials and Pandas for data engineering. Learn to set up development environments, manipulate data, and efficiently solve real-world problems.