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.

Advanced Python: Data Science, Testing, and Distribution

Advanced Python: Data Science, Testing, and Distribution
This course is part of Advanced Programming Techniques with Python Specialization

Instructor: Bill Rosenthal
Access provided by Pega
Skills you'll gain
- Databases
- Data Cleansing
- Relational Databases
- Package and Software Management
- Object Oriented Programming (OOP)
- Machine Learning
- Data Science
- Scripting
- Python Programming
- Database Application
- Programming Principles
- Object Oriented Design
- Unit Testing
- Regression Analysis
- Data Preprocessing
- User Interface (UI) Design
- Scripting Languages
- Computer Programming
- Software Development
- Debugging
Details to know

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January 2026
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There are 4 modules in this course
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.
What's included
1 reading5 plugins
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.
What's included
4 plugins
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.
What's included
4 plugins
You'll wrap things up and then validate what you've learned in this course by taking an assessment.
What's included
1 reading1 assignment1 plugin
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