Created by: Eric M. H. Goh, BSc, GDip, MTech, EMBA
Language: English
Released: 2019
Torrent Contains: 19 Files, 1 Folders
Course Source: https://www.skillshare.com/classes/Fundamentals-of-Python-for-Data-Mining/1433648294

Description

This course aims to cover the fundamentals of Python programming through real world examples, followed by a touch on Data Science. Python programming basics such as variables, data types, if statements, loops, functions, module, object and classes are very important and this course will try to teach these with a Console Calculator project.

The course will than run through the popular data mining libraries like pandas, matplotlib, scipy, sklearn briefly on iris dataset to do data manipulation, data visualizations, data exploration with statistics (inferential and descriptives), model and evaluation.

You do not need to know programming for this course.  

This course is based on my ebooks at SVBook.

What are the requirements?

• Computer

What am I going to get from this course?

• Python fundamentals, using Python libraries for data mining (pandas, scipy, matplotlib, ...)

What is the target audience?

• Beginners

Skills in this Class

• TECHNOLOGY
• PYTHON
• DATA SCIENCE

Projects & Resources

A walkthrough of the CRISP DM process using Python. CRISP DM process include data understanding, data preparation, prediction modeling and evaluation.

About Author

Eric Goh is a data scientist, software engineer, adjunct faculty and entrepreneur with years of experiences in multiple industries. His varied career includes data science, data and text mining, natural language processing, machine learning, intelligent system development, and engineering product design. He founded SVBook and extended it with DSTK.Tech and EMHAcademy. DSTK.Tech is where Eric develops his own DSTK data science softwares. Eric also published "Learn R for Applied Statistics...

For More Udemy Free Courses >>> https://ftuforum.com/
For more Lynda and other Courses >>> https://www.freecoursesonline.me/
Our Forum for discussion >>> https://discuss.ftuforum.com/