In order to be successful in Data Science, you need to be skilled with using tools that Data Science professionals employ as part of their jobs. This course teaches you about the popular tools in Data Science and how to use them.

이 강좌에 대하여
Anyone can complete this course in a self-paced manner without any prior programming or Data Science experience.
직원에게 수요가 높은 기술을 교육하면 회사가 이점을 얻을 수 있습니까?
비즈니스를 위한 Coursera 경험해 보기배울 내용
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.
귀하가 습득할 기술
- Data Science
- Github
- Python Programming
- Jupyter notebooks
- Rstudio
Anyone can complete this course in a self-paced manner without any prior programming or Data Science experience.
직원에게 수요가 높은 기술을 교육하면 회사가 이점을 얻을 수 있습니까?
비즈니스를 위한 Coursera 경험해 보기제공자:
학사 학위 취득 시작
강의 계획표 - 이 강좌에서 배울 내용
Data Scientist's Toolkit
Open Source Tools
IBM Tools for Data Science
Final Assignment: Create and Share Your Jupyter Notebook
검토
- 5 stars66.82%
- 4 stars22.18%
- 3 stars6.75%
- 2 stars2.22%
- 1 star2%
TOOLS FOR DATA SCIENCE의 최상위 리뷰
i rather to chose what is data science is better in perspective of materials and assignment, because in tools for data science i feel a lot of boring because to much explanation for what have to use
Everything was good, except the stuff with Zeppelin notebooks. That was just confusing and it felt like there were large chunks of explanations missing for people with no programming background
Gives you a good idea and overview about different tools but can be overwhelming because of the amount of new information and some videos are not up to date. Week 3 especially had some weak videos.
There was a problem with the connection to R lab, never fixed. Also, some tutorials are outdated. These are the negative parts and why I give four stars. Other than that I like the course so far.
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