Git, GitHub, and GitLab: From Beginner to Expert
MP4 | Video: h264, 1280x720 | Audio: AAC, 44.1 KHz, 2 Ch
Genre: eLearning | Language: English | Duration: 6 lectures (1h 53m) | Size: 682 MB
Learn everything you need to know about how to professionally use Git, Github, and Gitlab in Just 2 hours
What you'll learn
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 merging
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 merging. 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 merging 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 time 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 demonstration in Google Colab
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
Who this course is for
Beginner Git Users and Developers
Beginner Software Programmers
Beginner Software Engineers
Computer Science Students
Anyone interested in the GIT topic
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