In this 3-day, interactive Bootcamp you will learn how to apply concurrency to your own programs from beginning to end. We’ll start with the fundamentals and discuss how your computer architecture supports concurrency as well as the role of the Operating System. Once those key topics have been discussed, we'll go over multithreading concepts and how to use them on your own programs, including the associated challenges such as race conditions, synchronization techniques, and more. Next, we will dive into the GIL and learn how multiprocessing can overcome the limitations of CPU-bound, multithreaded apps. Last, but not least, we will guide you through learning several popular patterns for concurrency and parallelism, such as deadlocks (and how to prevent them), the producer/consumer model (using queues) and much more!
Python Concurrency In Practice
May 19th - 21st, 11:00 AM - 2:00 PM EST
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ABOUT THE INSTRUCTOR
Santiago is an expert Data Scientist and Python programmer with more than 10 years of experience in the field. He began his career as a Java developer working as a consultant on high performance and critical systems before moving to Python. In 2012, he was hired as the CTO of Athlete.com, a startup analyzing data from runners. He then fell in love with Data processing with Python and in 2015 founded RMOTR, to provide expert-level Data Science training. In 2020, RMOTR joined the INE family and Santiago has been an INE Data Science instructor ever since.
DAY 1 11 AM - 2 PM EST
- Computer Architecture Basics
- The role of the Operating System
- The OS Process
DAY 2 11 AM - 2 PM EST
- Synchronization mechanisms
- The producer/consumer model
DAY 3 11 AM - 2 PM EST
- The Python GIL
- Concurrent futures
- Closing Remarks & Recommendations