开始时间: 10/13/2018 持续时间: Unknown
The 5 courses in this University of Michigan specialization introduce learners to data science through the python programming language. This skills-based specialization is intended for learners who have basic a python or programming background, and want to apply statistical, machine learning, information visualization, text analysis, and social network analysis techniques through popular python toolkits such as pandas, matplotlib, scikit-learn, nltk, and networkx to gain insight into their data. Introduction to Data Science in Python (course 1), Applied Plotting, Charting & Data Representation in Python (course 2), and Applied Machine Learning in Python (course 3) should be taken in order and prior to any other course in the specialization. After completing those, courses 4 and 5 can be taken in any order. All 5 are required to earn a certificate.
Introduction to Data Science in Python
This course will introduce the learner to the basics of the python programming environment, including fundamental python programming techniques such as lambdas, reading and manipulating csv files, and the numpy library. The course will i
Applied Plotting, Charting & Data Representation in Python
This course will introduce the learner to information visualization basics, with a focus on reporting and charting using the matplotlib library. The course will start with a design and information literacy perspective, touching on what makes a good
Applied Machine Learning in Python
This course will introduce the learner to applied machine learning, focusing more on the techniques and methods than on the statistics behind these methods. The course will start with a discussion of how machine learning is different than des
Applied Text Mining in Python
This course will introduce the learner to text mining and text manipulation basics. The course begins with an understanding of how text is handled by python, the structure of text both to the machine and to humans, and an overview of the nltk frame
Applied Social Network Analysis in Python
This course will introduce the learner to network analysis through tutorials using the NetworkX library. The course begins with an understanding of what network analysis is and motivations for why we might model phenomena as networks. The second week in
密歇根大学的Python数据科学应用专项课程系列（Applied Data Science with Python），这个系列的目标主要是通过Python编程语言介绍数据科学的相关领域，包括应用统计学，机器学习，信息可视化，文本分析和社交网络分析等知识，并结合一些流行的Python工具包进行讲授，例如pandas, matplotlib, scikit-learn, nltk以及networkx等Python工具。感兴趣的同学可以关注：Gain new insights into your data-Learn to apply data science methods and techniques, and acquire analysis skills.