About this Course
In this practical course, you'll gain essential skills for modern data engineering: Build interactive Jupyter notebooks for data analysis and machine learning Deploy notebooks on cloud platforms like Google Colab and AWS SageMaker Construct scalable Python microservices using FastAPI Containerize and deploy machine learning microservices Create robust command-line tools in Python and Rust Automate testing and publishing of your data engineering projects Whether you're a data engineer, scientist, or analyst, this course will level up your abilities to build powerful data solutions. Get hands-on experience with cutting-edge tools and techniques you can apply on the job.
What You'll Learn
- Jupyter for data engineering workflows
- Cloud notebook deployment
- FastAPI microservices development
- Containerization of ML microservices
- Python command-line tools
- Rust CLI app development
- Automated testing and publishing
Instructors
Noah Gift
Executive in Residence and Founder of Pragmatic AI Labs
Alfredo Deza
Adjunct Assistant Professor in the Pratt School of Engineering
Kennedy Behrman
Senior Data Engineer