Introduction to Data Science in Python by University of Michigan
This course will teach the learner the fundamentals of the Python programming environment, including lambdas, reading and manipulating csv files, and the numpy module. The course will cover data manipulation and cleaning techniques using the popular Python pandas data science library, as well as the abstraction of Series and DataFrame as central data structures for data analysis, as well as tutorials on how to effectively use functions like groupby, merge, and pivot tables. Students will be able to take tabular data, clean it, alter it, and execute basic inferential statistical analyses by the end of this course.
This course should be taken before Applied Plotting, Charting, and Data Representation in Python, Applied Machine Learning in Python, Applied Text Mining in Python, and Applied Social Network Analysis in Python.
This course offers:
- Flexible deadlines: Reset deadlines in accordance to your schedule.
- Certificate : Earn a Certificate upon completion
- 100% online
- Intermediate Level
- Approx. 31 hours to complete
- Subtitles:Arabic, French, Portuguese (European), Italian, Portuguese (Brazilian), Vietnamese, Korean, German, Russian, English, Spanish
- Course 1 of 5 in the Applied Data Science with Python Specialization
Coursera Rating: 4.5/5
Enroll here:https://www.coursera.org/learn/python-data-analysis
