Introduction to Data Science in Python

Description

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.

This course should be taken before any of the other Applied Data Science with Python courses: Applied Plotting, Charting & Data Representation in Python, Applied Machine Learning in Python, Applied Text Mining in Python, Applied Social Network Analysis in Python.

Instructor

  • Christopher Brooks

    Christopher Brooks

    Research Assistant Professor

    School of Information

Reviews

4 out of 5 stars

November 13, 2019

Good intro to using pandas and going through datasets!

5 out of 5 stars

November 13, 2019

Learned a lot of new stuff, specially Pandas is cool, thanks!

5 out of 5 stars

November 13, 2019

This course was very helpful to educate an individual about Data Science.

5 out of 5 stars

November 13, 2019

Good course for those people who are new to Data Science or looking to switch your field to Data Science. It course helps you learn by doing a lot of problems so as to get you acquainted with the Data Science. Highly recommend for new comers to this field.