100% OFF- Testing Python Full Stack & Backend for MC/ ML Engines 101
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Testing Python Full Stack & Backend for MC/ ML Engines 101 , Running Maintaining Testing and Debugging Python Full Stack and Backend for Monte Carlo Engines 102.
Course 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
Who this course is for:
- Intermediate Python for Computational Full Stack engines is for anyone who want to learn more beyong python basics
Free