Python is one of the more popular programming languages used by developers, data scientists, and software engineers. Touted as a lean language, it taps into the concept that "Less is more", communicating in one line of code the same task that would take 10-20 lines of code in other languages. As an object-oriented language, Python is used to build web apps, build desktop apps, analyze data, and make future predictions. Python is a powerful front-end and back-end language used in companies ranging from NASA to Google to Netflix.

Python runs on virtually any operating system and boasts a novice-friendly approach to learning programming. Python has become prevalent as it is easy to learn, and yet highly versatile and practical for complex tasks.

This Chancellor's Certificate is designed to help you understand and develop the skills needed for effective programming in Python. Gain the knowledge needed to build both web and programming applications. The certificate's core classes provide the foundation and essentials Python. The electives provide data gathering experience - as Python is often used in data analysis projects and can interact with programs written in R.

You'll learn:

  • Practical skills for writing and debugging Python applications.
  • How to use Python to streamline programming workflows.
  • How object oriented programming provides an efficient framework to bring your coding projects to completion.
  • An understanding of how data is organized and how to use Python for data analysis.

How to Enroll

  • Enroll online. The online Certificate Registration Code is CT814-X9014 for the CT817-X9017 for the Python Programming Certificate.
  • Call 314-984-9000 or email for information on how to enroll.

There is a nonrefundable fee of $25 which covers processing, recordkeeping and certificate costs.

Upon receipt of the application and fee, we will send a confirmation and a Notification of Completion form. Use this form to keep track of classes you're taking toward your certificate. When you complete your last class, return the Notification form.

We will verify successful completion of all requirements and send you the Chancellor's Certificate in Python Data Analysis.

Note: You will receive CEUs for successful completion of each certificate class. The hours you complete in these classes can also be applied toward the 96-hour Chancellor's Certificate on the Computer.

Certificate Prerequisites

Introduction to Programming Concepts or experience with another programming language.

Certificate Completion Requirements

All classes must be completed through the University of Missouri-St. Louis Computer Education & Training Center within a 24 month window. You can apply classes that you have previously taken at the Computer Education & Training Center as long as you complete all classes towards the certificate within 24 months of the first class attended and applied towards the certificate.

You are required to complete any course prerequisites listed for certificate classes. These classes will not count toward the hours required to complete the certificate. Be sure to check the course descriptions for specific prerequisites.

Please note that a class can only be applied to one specialized certificate.

You can earn this certificate in one of these two ways:

  • Complete a minimum of 84 hours - 65 hours from Core Courses and 19 hours from Electives.
  • Complete the Chancellor's Certificate in Data Analysis and then take 6.5 hours from the Electives category and 65 hours from Core Courses as shown below.

Core Courses (minimum 65 hours required)
  • Introduction to Python Programming
  • Intermediate Python Programming
  • Advanced Python Programming: Level 1
  • Advanced Python Programming: Level 2
  • Advanced Python Programming: Level 3

Electives (minimum 19 hours required)
  • Introduction to SQL
  • Intermediate Applications of SQL
  • Advanced Applications of SQL
  • Advanced SQL Queries: Level 1
  • Advanced SQL Queries: Level 2
  • Advanced SQL Queries: Level 3
  • SQL Query Optimization
  • Introduction to R
  • Intermediate Applications of R