
[Free] Testing Python Full Stack &Amp; Backend For Mc/ Ml Engines 101
Running Maintaining Testing and Debugging Python Full Stack and Backend for Monte Carlo Engines 102 – Free Course
What you’ll learn
- Running Maintaining Testing and Debugging Python Engines
- Monte Carlo and Machine Engines Simulation Engines
- An introductory but 102 Level course with advanced Topics
- Use for training remote managerless Python Computational Science Developers
Requirements
- No programming experience needed
Description
Python Full Stack and Backend Engines for MC/ ML Engines 102
Running Maintaining Testing and Debugging Python Full Stack and Backend for Monte Carlo Engines 102
Intro
How to work and success in remote managerless environment
What technical skill are needed: Python shell coding spark df git commands and sshing
Running Maintaining Testing and Debugging Computational engines
Inputs given through yaml
How get old runs information so that you can pull data. What do in case you are stuck
How to handle authentication errors
Execution is through .sh file
Full stack vs Back end engine
How to get the the root of mismatch
What are clone proxy runners how to use their runs
How to make proper notes
How tos:
How to search for an old run
How to see the latest run
How to see the runs that is still in progress
How to start a run
Assignments:
Write step for Getting Outputs of Monte Carlo Backend Run
Backend runs
How to compare two dfs
What are diff type of authentication
What to do if you cannot find the runs
Common causes of mismatch of runs
Give 3 common type of grid run errors / issues
Write sample wiki notes about your findings of attempting to search the runs
Author(s): Shivgan Joshi








