Data Science
24
Version Control with Git and GitHub
Home
1
Introduction
2
Schedule
R Programming
3
Installation
4
Introduction to R
5
Getting Started
6
IDEs
7
R packages
8
Basic operations
9
Data Types & Vectors
10
Data Structures
11
Indexing
12
Factors
13
Base Data I/O
14
Read and Write Excel Data
15
Vectorized Operations
16
Control Flow
17
Summarizing Data
18
Aggregate
19
Writing Functions
20
Function Scoping
21
The Apply Family
22
Base Graphics
Data Science
23
Terminal
24
Version Control with Git and GitHub
25
Demo Dataset
26
Probability
27
Statistics
28
Hypothesis Testing
29
Data Visualization
30
Introduction to Machine Learning
31
Clustering
32
Decomposition and Dimensionality Reduction
33
Supervised Learning
34
AI Assistants for Data Science
35
References
Table of contents
24.1
Learning objectives
24.2
Project organization
24.3
Git and GitHub
24.4
Clone, inspect, stage, and commit
24.5
Push and pull
24.6
Branches and collaboration
24.7
Rebase and conflicts
24.8
Hands-on practice
24.9
Checkpoint
24.10
Further study
Data Science
24
Version Control with Git and GitHub
24
Version Control with Git and GitHub
24.1
Learning objectives
Track changes to a data science project with Git.
Collaborate through a shared GitHub repository.
Explain the roles of commits, branches, and remotes.
24.2
Project organization
24.3
Git and GitHub
24.4
Clone, inspect, stage, and commit
24.5
Push and pull
24.6
Branches and collaboration
24.7
Rebase and conflicts
24.8
Hands-on practice
24.9
Checkpoint
24.10
Further study
23
Terminal
25
Demo Dataset