Python for Data Science
Learn to design and write high-performing Python code.Enroll
At a Glance
- Professional Education
- Open Enrollment
- Eight weeks Open Enrollment
Learn to leverage data using Python in creative and relevant ways to solve real-world problems.
The eight-week Python for Data Science program at the University of Chicago introduces the basic concepts of Python as a programming language. This highly technical program is project-based at its core and will present you with many practical examples before giving you the opportunity to create and run your own Python projects.Learn to leverage data using Python in creative and relevant ways to solve real-world problems.
Designed for professionals with a rudimentary knowledge of Python and machine learning or those eager to learn about data science. Business intelligence analysts with a strong foundation in the theory of data analysis and manipulation but limited Python exposure, as well as those who work with a quantitative mind but no technical toolkit, will benefit from this program.
In a world where data is considered a commodity, data science practitioners need to have a greater understanding of the components of designing and writing Python code. Our program will provide you with a comprehensive introduction to the most popular programming language and teach you how to leverage it to solve real-world problems.
After completing the program, you will be able to:
- Create persisting models to be deployed as an API or used for batch scoring.
- Design code that runs in parallel using multiprocessing and multithreading functionality.
- Discuss advanced Python functionalities like classes and functions.
- Eight weeks in length
- Weekly, self-paced interactive learning modules and assignments are time-sensitive and should be completed by the set deadlines
- Synchronous sessions and live question and answer sessions
- Mentors to provide continuous support and encourage a dynamic and positive learning environment
You will learn to:
- Understand the Python language
- Perform advanced data analysis and manipulation
- Write production-level Python code
- Train and evaluate machine-learning models
- Design and optimize Python code for performance and speed
- Write Python code to efficiently process large data sets
- Prepare machine-learning models for production use
From molecular engineering to computational analysis, big data and cutting-edge technology can help solve some of the hardest problems we face. Get up to speed on these rapidly-changing fields and apply a quantitative approach to any challenge.Learn more about Applied Science