- Version Control
- Statistical Programming
- Development Environment
- Data Visualization Software
- Data Science
- Computer Programming Tools
- R (Software)
- Git (Version Control System)
- Query Languages
- Other Programming Languages
- IBM Cloud
- Jupyter
Tools for Data Science
Completed by Kai Schröder
July 26, 2020
18 hours (approximately)
Kai Schröder's account is verified. Coursera certifies their successful completion of Tools for Data Science
What you will learn
Describe the Data Scientist’s tool kit which includes: Libraries & Packages, Data sets, Machine learning models, and Big Data tools
Utilize languages commonly used by data scientists like Python, R, and SQL
Demonstrate working knowledge of tools such as Jupyter notebooks and RStudio and utilize their various features
Create and manage source code for data science using Git repositories and GitHub.
Skills you will gain
