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Coursera

Advanced Python: Data Science, Testing, and Distribution

via Coursera

Overview

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To round out your advanced implementation of Python, in this course, you'll clean and visualize data, and apply basic machine learning principles. You'll also handle exceptions and write and execute unit tests, as well as create and distribute Python packages. This is the third and final course in a multi-course Specialization. All of the courses in this Specialization require that you use the provided virtual machine, which includes an installation of Python. The course setup instructions provided in the first course go into more detail about the hardware and software requirements.

Syllabus

  • Programming Python for Data Science
    • Python® is one of the most popular programming languages in the field of data science. This includes everything from data cleaning, to data analysis, to data visualization, and much more—all of which Python excels at. In this lesson, you will program Python for data science applications.
  • Implementing Exception Handling and Unit Testing
    • Before your applications will be ready for people to use, you must ensure that they run error free and can handle any user, system, or data issues you can anticipate. In this lesson, you will handle exceptions and write and execute unit tests.
  • Packaging Applications for Distribution
    • Once you've created an application, you may want to think about sharing it with the world. The default Python® installation includes utilities to help you bundle all of the files required for your application into one place for easy distribution.
  • Completing the Course
    • You'll wrap things up and then validate what you've learned in this course by taking an assessment.

Taught by

Bill Rosenthal

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