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Introduction to Data Science in Python

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Introduction to Data Science in Python
University of Michigan Online Course Highlights
  • weeks long
  • 7 hours per week
  • Learn for FREE, Ugpradable
  • Self-Paced
  • Taught by: Christopher Brooks
  • View Course Syllabus

Online Course Details:

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.

WHAT YOU WILL LEARN

  • Describe common Python functionality and features used for data science
  • Explain distributions, sampling, and t-tests
  • Query DataFrame structures for cleaning and processing
  • Understand techniques such as lambdas and manipulating csv files

SKILLS YOU WILL GAIN

  • Python Programming
  • Numpy
  • Pandas
  • Data Cleansing

Take This Online Course

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