September 11 2022

Git, GitHub, and GitLab: From Beginner to Expert

Git, GitHub, and GitLab: From Beginner to Expert
Published 09/2022MP4 | Video: h264, 1280x720 | Audio: AAC, 44.1 KHz, 2 ChGenre: eLearning | Language: English | Duration: 6 lectures (1h 53m) | Size: 682 MB

The differences between Git, Github, Gitlab
How to use Git and why we use it in the first place
The star features of Git: branching and meg
How remote Git works like Gitlab and Github
Demonstration of clone, pull and push with a simulated collaboration
The use of CUDA with Python to speed code computation

Basic Knowledge in Software Programing
True Desire to Master the Git and GitHub Tools

In this course, we first explain the basic working principle of the distributed version control software Git.

Then, we explain the star features of Git: branching and meg. We will see how branching allows you to make parallel histories inside one project. This is a key element to easy collaboration, and a good understanding of branching and meg is a prerequisite for effectively using remote services such as Gitlab and GitHub.

After you feel an expert on Git, in the somewhat longer and last video in the series, we finally explain how we can use Gitlab and other remote git services to collaborate on git projects. More specifically, you will get an Introduction to different hosting platforms, then get the following

Basic explanation of how remotes work, then

Demonstration of creating a new remote repository on Gitlab + a short tour of the site

Demonstration of clone, pull, and push with a simulated collaboration

How I propose we work on our GitLab projects

Why do we use the -u modifier with push

You can get Git for your system from git-scm. The lectures in this course are only meant as an introductory presentation, not as an exhaustive course. You will find all relevant details in the Pro-Git book by Chanon and Straub. For specific questions you will 99% of the find answers on StackExchange.

In the bonus section, which is about using the GPU to substantially speed up all kinds of numerical problems. You will Conventional wisdom dictates that for fast numeric you need to be a C/C wizz. It turns out that you can get quite far with only python. In this video, I explain how you can use Cupy together with Numba to perform calculations on NVIDIA GPU's. Production quality is not the best, but I hope you may find it useful.

Introduction: GPU programming in python, why

Cupy intro

Cupy demonstration in Google Colab

Cupy summary

Numba.cuda and kernels intro

Grids, blocks and threads

Matrix multiplication kernel

Tiled matrix multiplication kernel and shared memory

Numba.cuda demonstration in Google colab

Final remarks

Bner Git Users and Developers
Bner Software Programmers
Bner Software Eeers
Computer Science Students
Anyone interested in the GIT topic


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