Coursera – Applied Data Science with Python Specialization 2022-2 – Download
Description
Applied data science with Python specialization, etc. The University of Michigan collection training is that the topic of scientific data applications with Python pays off. In the training set etc. Lecturers in 5 courses accompany you with the scientific data through the work familiar with the Python programming language. This series of education-based skills is aimed at those with elementary level knowledge of the Python programming language and advanced learning topics such as statistics, machine learning, etc. Visualization information, text analysis, and social networking are provided.
As you begin training sets and specializing in applied data science with Python, you will be familiar with scientific data in Python. Then enter the topics like drawing applications etc. Charts and representations of data through Python come into play. After mastering these topics, machine learning in Python will be discussed and you will need to prepare a scientific data project.
Cases in which this course is offered:
- Perform analysis to derive statistical data
- Diagnosis, good or bad, is the visualization of data
- Empower data analysis with machine learning
- Analysis of network connections in the social area
Profile of course
- Editor: Coursera
- University: Michigan
- Teachers: Christopher Brooks, Kevyn Collins-Thompson, VG Vinod Vydiswaran, Daniel Romero
- Level: intermediate
- Number of courses: 5 courses
- Language: English
The courses offered in the collection:
1. Introduction to Data Science in Python
2. Applied visualization, charting and data representation in Python
3. Applied Machine Learning in Python
4. Applied Text Mining in Python
5. Applied Social Network Analysis in Python
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This tutorial includes 5 courses.
Download links
Introduction to data science in Python
Applied visualization, charting and data representation in Python
Applied Machine Learning in Python
Applied Text Mining in Python
Applied Social Network Analysis in Python
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File size
3.6GB