Project Description

Planning to improve knowledge and learning using Okta-Lithmos and Linkedin-Learning platforms on topics useful in testing jobs and start / continue / complete some training.

Topics will be to :

  • Training on SUSE SLE Micro 5.x [Lithmos]
  • Learn more about Terraform, Helm, Rancher
  • Learn more about Containers, Kubernetes

Goal for this Hackweek

Possibly complete one of the above mentioned topics.

Resources

Possible links are:

  • SLE Micro 5x: https://suselearningcenter.litmoseu.com/home/LearningPath/10166
  • Terraform: https://www.linkedin.com/learning/learning-terraform-15575129
  • Kubernetes: https://www.linkedin.com/learning/imparare-kubernetes

Looking for hackers with the skills:

learning training

This project is part of:

Hack Week 23

Activity

  • about 2 years ago: mdati left this project.
  • about 2 years ago: mdati liked this project.
  • about 2 years ago: mdati started this project.
  • about 2 years ago: mdati added keyword "learning" to this project.
  • about 2 years ago: mdati added keyword "training" to this project.
  • about 2 years ago: mdati originated this project.

  • Comments

    Be the first to comment!

    Similar Projects

    Advent of Code: The Diaries by amanzini

    Description

    It was the Night Before Compile Time ...

    Hackweek 25 (December 1-5) perfectly coincides with the first five days of Advent of Code 2025. This project will leverage this overlap to participate in the event in real-time.

    To add a layer of challenge and exploration (in the true spirit of Hackweek), the puzzles will be solved using a non-mainstream, modern language like Ruby, D, Crystal, Gleam or Zig.

    The primary project intent is not just simply to solve the puzzles, but to exercise result sharing and documentation. I'd create a public-facing repository documenting the process. This involves treating each day's puzzle as a mini-project: solving it, then documenting the solution with detailed write-ups, analysis of the language's performance and ergonomics, and visualizations.

                                   |
                                 \ ' /
                               -- (*) --
                                  >*<
                                 >0<@<
                                >>>@<<*
                               >@>*<0<<<
                              >*>>@<<<@<<
                             >@>>0<<<*<<@<
                            >*>>0<<@<<<@<<<
                           >@>>*<<@<>*<<0<*<
             \*/          >0>>*<<@<>0><<*<@<<
         ___\\U//___     >*>>@><0<<*>>@><*<0<<
         |\\ | | \\|    >@>>0<*<0>>@<<0<<<*<@<<
         | \\| | _(UU)_ >((*))_>0><*<0><@<<<0<*<
         |\ \| || / //||.*.*.*.|>>@<<*<<@>><0<<<
         |\\_|_|&&_// ||*.*.*.*|_\\db//_
         """"|'.'.'.|~~|.*.*.*|     ____|_
             |'.'.'.|   ^^^^^^|____|>>>>>>|
             ~~~~~~~~         '""""`------'
    ------------------------------------------------
    This ASCII pic can be found at
    https://asciiart.website/art/1831
    
    

    Goals

    Code, Docs, and Memes: An AoC Story

    • Have fun!

    • Involve more people, play together

    • Solve Days 1-5: Successfully solve both parts of the Advent of Code 2025 puzzles for Days 1-5 using the chosen non-mainstream language.

    • Daily Documentation & Language Review: Publish a detailed write-up for each day. This documentation will include the solution analysis, the chosen algorithm, and specific commentary on the language's ergonomics, performance, and standard library for the given task.


    Try AI training with ROCm and LoRA by bmwiedemann

    Description

    I want to setup a Radeon RX 9600 XT 16 GB at home with ROCm on Slowroll.

    Goals

    I want to test how fast AI inference can get with the GPU and if I can use LoRA to re-train an existing free model for some task.

    Resources

    https://rocm.docs.amd.com/en/latest/compatibility/compatibility-matrix.html https://build.opensuse.org/project/show/science:GPU:ROCm https://src.opensuse.org/ROCm/