Python for Data Science Essential Training Part 1

Topic
Advanced Analytics
Subtopic
Data Science
View the Course/Resource
Industry 4.0 Academy
Industry 4.0 Course Catalog
Cost: Subscription or purchase
Duration: 6 Hour(s)
Certification Available: Yes
Course Level: Intermediate to advanced
Prerequisites: None
Administered By: LinkedIn Learning/Pierson
Description
Python for Data Science Essential Training is one of the most popular data science courses at LinkedIn Learning. This is course 1 of 2.
What You'll Learn
In this course, instructor Lillian Pierson takes you step by step through a practical data science project: a web scraper that downloads and analyzes data from the web. Along the way, she introduces techniques to clean, reformat, transform, and describe raw data; generate visualizations; remove outliers; perform simple data analysis; and generate interactive graphs using the Plotly library. You should walk away from this training with basic coding experience that you can take to your organization and quickly apply to your own custom data science projects.

Industry 4.0 Academy Disclaimer

The courses offered in this catalog are a curated collection of learning materials that provide an overview of Industry 4.0. It is designed to provide resources that businesses can use to understand and implement Industry 4.0, covering topics such as technology adoption, data utilization, and workforce development. While some of the course providers may provide a certification, the intent of this website is to provide information on knowledge-building opportunities. RIT provides no certification or degree credit for any of this content.

Some materials are free, while others require a fee. Neither RIT or the Center of Excellence in Advanced and Sustainable Manufacturing (COE-ASM) has received compensation from the organizations that have created and published the course materials. The Industry 4.0 Academy supports a COE-ASM initiative to advance the adoption of Industry 4.0 technologies and practices among manufacturers in New York State and is funded by the New York State Department of Economic Development.