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Whether you’re building big data applications, developing data pipelines, or working on machine learning projects, it’s essential to manage changes to your code. Although developers and data scientists have employed a variety of tools for this over the years, an open source version control system called git has emerged as the standard tool for thousands of organizations around the world. Just Enough Git introduces students to this innovative distributed version control system through a series of lectures, demonstrations, and hands-on exercises.


What you will learn

Students who successfully complete this course will be able to:

Current courses include:

  • Understand how git compares to other revision control systems
  • Create and work with git repositories, both locally and in GitHub
  • Explore repository contents and add new files
  • Stage and commit modifications to files stored in a repository
  • Compare file modifications and resolve conflicting changes
  • Use branches and tags
  • Collaborate using git integration in Cloudera Data Science Workbench (CDSW)


What to expect

This course is best suited to developers and data scientists who feel comfortable performing basic operations from the Linux command line. No prior experience with git or other revision control systems is necessary.

Book the course

How would you like to train?

Course Outline

Understanding Git

  • Why Version Control?
  • What is Git?
  • How Does Git Compare to Other Version Control Tools?
  • Concepts and Terminology
  • Different Types of Git Clients
  • GitHub and Other Code Hosting Platforms


Using Git with a Local Repository

  • Initializing Git Configuration
  • Creating a Local Repository
  • Staging and Committing Your
  • Changes
  • Ignoring Files
  • Exploring a Repo
  • Comparing Commits

Using Git with Remote Repositories

  • Connecting to Remote Repositories
  • Pushing Your Changes
  • Getting the Code from a Remote Repository
  • Understanding and Using Branches
  • Merging and Resolving Conflicts
  • Understanding and Using Tags
  • Using Git for Collaboration with Cloudera Data Science Workbench

I immediately began using lessons from my Cloudera class to address and revisit several real-world issues and use cases that had been problematic, and was able to quickly create working code that yielded desired results.


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