explanation
The Python for Statistical Analysis learning period is about acquiring applied statistical skills that help Python by solving real-world problems through software and libraries from cutting-edge industries. During this period, you dedicate yourself to a statistical application focus instead of learning theoretical topics for hours through examples from real-world encounters and trying to connect them to real-world problems. Learn the theory and immediately use it in Python for conventional problems, giving you the knowledge and skills you need. In this process, we use tools and workflows to operate in a modern way. It is similar to reinforcement learning in that it does not take time, but is instead a state-of-the-art technique used to solve technical problems. We’ll introduce you to the library’s code, ours, and finally the features of the modern publishing app we use. Collecting numbers is easy for computers to quickly move from the human realm. We are focusing more on interpretation and illustration of data in this day and age.
What courses will you learn in Python for statistical analysis:
- Insights deeper than data
- Use Python to solve common projects and complex problems related to statistics and machine learning.
- Interpretation methods, examples, output, etc., explained output, navigation, and graphic integration
- Learn how to test hypotheses and use efficient testing using Python.
Specification period
Publisher: Udemy
Teachers: Samuel Hinton and Regency Team
Language: English,
Education level: Beginner to advanced;
Number of classes: 56
Duration: 8 hours 37 minutes
This course covers Python 2020-11 for statistical analysis.
precondition:
image
sample video
installation manual
After extracting, use the back player to select the desired view.
Subtitles: English
Quality: 720
download link
Password file: free download software
file size
2.4GB