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    DVC and Git For Data Science

    Posted By: ELK1nG
    DVC and Git For Data Science

    DVC and Git For Data Science
    Published 04/2022
    MP4 | Video: h264, 1280x720 | Audio: AAC, 44.1 KHz, 2 Ch
    Genre: eLearning | Language: English + srt | Duration: 53 lectures (8h 44m) | Size: 4.1 GB

    Master the Basics of Git and Data Version Control (DVC) for Beginners

    What you'll learn
    Learn Version Control and Why We Need it?
    Understand the Need for Data Version Control
    Git and Github For Data Science Project
    Master DVC For Data Science Project
    Explore DAGsHub
    Build Your Own Custom Version Control Tool (Git) From Scratch

    Requirements
    Basic Understanding of Python and Machine Learning
    Determination and Willingness to Learn

    Description
    Our modern world runs on software and data, with Git - a version control tool we track and manage the different changes and versions of our software. Git is very useful in every programmer's work. It is a must-have tool for working in any software-related field, that includes data science to machine learning.

    What about the data and the ML models we build? How do we track and manage them?

    How do data scientist, machine learning engineers and AI developers track and manage the data and models they spend hours and days building?

    In this course we will explore Git and DVC - two essential version control tools that every data scientist, ML engineer and AI developer needs when working on their data science project.

    This is a very new field hence there are not a lot of materials on using git and dvc for data science projects. The goal of this exciting and unscripted course is to introduce you to Git and DVC for data science.

    We will also explore Data Version control, how to track your models and your datasets using DVC and Git.

    By the end of the course you will have a comprehensive overview of the fundamentals of Git and DVC and how to use these tools in managing and tracking your ML models and dataset for the entire machine learning project life cycle.

    This course is unscripted,fun and exciting but at the same time we will dive deep into DVC and Git For Data Science.

    Specifically you will learn

    Git Essentials

    How Git works

    Git Branching for Data Science Project

    Build our own custom Version Control Tools from scratch

    Data Version Control - The What,Why and How

    DVC Essentials

    How to track and version your ML Models

    DVC pipelines

    How to use DAGsHub and GitHub

    Label Studio

    Best practices in using Git and DVC

    Machine Learning Experiment Tracking

    etc

    Who this course is for
    Anyone interested in Learning Git and DVC
    Data Scientist curious about Data Version Control
    Students