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 introduce data manipulation and cleaning techniques using the popular python pandas data science library and introduce the abstraction of the Series and DataFrame as the central data structures for data analysis, along with tutorials on how to use functions such as groupby, merge, and pivot tables effectively. By the end of this course, students will be able to take tabular data, clean it, manipulate it, and run basic inferential statistical analyses.
The mission of the University of Michigan is to serve the people of Michigan and the world through preeminence in creating, communicating, preserving and applying knowledge, art, and academic values, and in developing leaders and citizens who will challenge the present and enrich the future.
- 5 stars66.25%
- 4 stars24.51%
- 3 stars5.36%
- 2 stars1.88%
- 1 star1.97%
来自INTRODUCTION TO DATA SCIENCE IN PYTHON的热门评论
To be an introductory course I struggled a lot, is a very practical course, and the assignements encourage you to learn more. This is the best technical course I have taken. Lo recomiendo ampliamente
Assignments are tough compared to the course lecture material. Therefore, alot of self learning is required other than the lectures. There should be more study material covered in the course videos
Um curso intenso e bastante prazeroso. Gostei de todas as etapas, os videos funcionam bem e estão construidos numa base introdutória, mas o desafio é pesquisar e pesquisar. Muito interessante mesmo!
Great course! I liked how the focus was mainly on the practical aspects of data science. No 'dry' course material. I know much more about the practical side of data analysis than before! Thank you!
关于 借助 Python 应用数据科学 专项课程
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 a basic 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.