Advanced Data Engineering
Pragmatic AI Labs
Become an expert in scaling data systems. Master Celery, Airflow, graph databases. Build real-world solutions for massive datasets and complex workflows. Optimize performance at enterprise scale. 10 hands-on labs and exercise to "learn by doing".
About this Course
Master Scalable Data Engineering with Cutting-Edge Tools Learn to handle massive datasets efficiently with this advanced course Gain practical expertise in scaling data systems using modern technologies Ideal for data scientists, engineers & professionals with data handling experience Course Highlights: Leverage Celery & RabbitMQ for scalable data consumption Optimize workflows with Apache Airflow for efficient management Utilize Vector & Graph databases for robust data management at scale Hands-on projects for real-world experience in solving data challenges Create scalable systems & analyze performance for optimum results Upskill to design, build & optimize data engineering pipelines that can handle complex, large-scale datasets. Prepare for demanding data roles by mastering advanced techniques with this comprehensive training.
What You'll Learn
- Create and manage data pipelines and their lifecycle
- Connect and work with message queues to manage data processing
- Use vector, graph, and key/value databases for data storage at scale
Prerequisites
- Familiarity with programming, preferably with Python.
- Experience with version control systems like Git
- Using the terminal and running shell commands.
Instructors
Alfredo Deza
Adjunct Assistant Professor in the Pratt School of Engineering
Noah Gift
Executive in Residence and Founder of Pragmatic AI Labs