Git For Data Science - A Guide For Data Scientists

Git For Data Science - A Guide For Data Scientists

Academic data scientists have taken up the role of AI engineers and it is now absolutely necessary to learn Git for data science. For performing collaborative coding in small as well as large data science organizational teams. For building a personal project portfolio on an online repository hosting platform such as GitHub, GitLab, etc. For tracking code as well as file changes. For contributing and learning from open-source data science projects.

Ever since the invention of Git, it has widely been used by software developers for tracking code as well as files changes.

However, in the past few years, the adoption rate of Git for data science has seen a tremendous increase as well. You might even find that the knowledge of Git is now a requirement for various data science vacancies posted on a daily basis on the internet.

What is Git?

Git is a distributed version control system for tracking changes in source code during software development. — Wikipedia

Git for Data Science

Git is one of the most commonly used command-line tools used for version control in software development. Through version control, developers are able to record, track and save changes to files over time so that they can quickly revert back to previous versions of the files whenever needed.

Also, popular platforms such as Github and Gitlab use Git as the underlying backbone to empower developers to seamlessly work together on the same project at the same time. Many open-source projects (including Linux) were made possible due to Git where thousands of people came together to work on a single project despite the difference in geographical locations.

Why should a data scientist learn Git for data science?

Today, academic data scientists have taken up the role of AI engineers in building the startups of the future and thus, this brings Git into the limelight as a near-to-perfect tool for version control.

Here are a few major reasons why a modern day data scientist should learn Git:

  • For performing collaborative coding in small as well as large data science organizational teams.
  • For building a personal project portfolio on an online repository hosting platform such as GitHub, GitLab, etc.
  • For tracking code as well as file changes.
  • For contributing and learning from open-source data science projects.

Fortunately, learning Git will be a piece of cake if you are able to remember the hundreds of algorithms you study in data science.

git data-science programming developer

Bootstrap 5 Complete Course with Examples

Bootstrap 5 Tutorial - Bootstrap 5 Crash Course for Beginners

Nest.JS Tutorial for Beginners

Hello Vue 3: A First Look at Vue 3 and the Composition API

Building a simple Applications with Vue 3

Deno Crash Course: Explore Deno and Create a full REST API with Deno

How to Build a Real-time Chat App with Deno and WebSockets

Convert HTML to Markdown Online

HTML entity encoder decoder Online

Data Science Course in Dallas

Become a data analysis expert using the R programming language in this [data science](https://360digitmg.com/usa/data-science-using-python-and-r-programming-in-dallas "data science") certification training in Dallas, TX. You will master data...

50 Data Science Jobs That Opened Just Last Week

Data Science and Analytics market evolves to adapt to the constantly changing economic and business environments. Our latest survey report suggests that as the overall Data Science and Analytics market evolves to adapt to the constantly changing economic and business environments, data scientists and AI practitioners should be aware of the skills and tools that the broader community is working on. A good grip in these skills will further help data science enthusiasts to get the best jobs that various industries in their data science functions are offering.

Applications Of Data Science On 3D Imagery Data

The agenda of the talk included an introduction to 3D data, its applications and case studies, 3D data alignment and more.

Here’s how I Learned Just Enough Programming for Data Science

How to approach learning programming and best books I recommend. There’s no doubt that data science requires decent programming skills, but how much is enough?

Data Science Explained | Data Science For Beginners | Data Science

This Data Science tutorial will help you in understanding what is Data Science, why we need Data Science, prerequisites for learning Data Science, what does ...