Modern Data Engineering Essentials
Modern Data Engineering Essentials
.MP4, AVC, 1280x720, 30 fps | English, AAC, 2 Ch | 1h 21m | 373 MB
Instructor: Christina Taylor
.MP4, AVC, 1280x720, 30 fps | English, AAC, 2 Ch | 1h 21m | 373 MB
Instructor: Christina Taylor
This video equips you with the knowledge and skills needed to engineer data for today’s large systems.
Overview
Modern Data Engineering Essentials presents the concepts and issues surrounding today’s big data and AI systems. You also gain hands-on experience with data tools and workflows. The video finishes with a discussion of education, experience, and credentials needed to develop your skills in the modern data world.
About the Instructor
Christina Taylor is a seasoned data engineer who is passionate about open-source, multi-cloud, scalable, and efficient data pipelines. She makes data informed architectural decisions to build modern systems that support advanced analytics, machine learning, and customer-facing product use cases. She has a keen interest in interdisciplinary areas such as DevOps, MLOps, and Cloud FinOps. She loves to learn, share, and contribute to the open source community.
Learn How To
- Apply data engineering concepts
- Load data into DuckDB
- Set up and use dbt
- Orchestrate data engineering workflows using Airflow, Dagster, and Prefect
- Put it all together integrating Dagster and dbt
- Maximize your education, experience, and skills to work in the modern data engineering world
Who Should Take This Course
Developers, data scientists, and engineers who are interested in the data side of big data systems
Course Requirements
- Previous experience with data and data models
- Some knowledge of SQL and Python
Modern Data Engineering Essentials
