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

July 11, 2019

the assignment is discounted from the lecture, it is way harder. But I learnt the most from the assignment and the forum. Overall, it improved my skill a lot!

5 out of 5 stars

July 11, 2019

Great course.Beginner Friendly.

5 out of 5 stars

July 11, 2019

it like it .

4 out of 5 stars

July 11, 2019

Very good course to manipulate data with python. My only issue is that the assignments need to be elaborate or described in better.