Introduction to Python Programming

Dr. Geoffrey Hubona is an associate professor of management information systems and data analytics at Texas A&M International Universityin Laredo, Texas, where he teaches Python and R programming, data analytics, and other information systems courses at the undergraduate and graduate levels. He has held both tenure-track and tenured faculty positions at four major state universities since 1993. In these positions, he taught dozens of various statistics, business information systems, and computer science courses to undergraduate, master’s, and Ph.D. students. Additionally, he has beendeeply involved in data science programmingfor over a decade and has designed data science certificate programs at multiple universities in South Texas.

Dr. Geoffrey Hubona

A hands-on, online Python programming class for beginners taught by an experienced data scientist and full-time university faculty member.

<h3>Registration ended on Friday, July 7 at 11:59 PM EDT. We will launch another similar course on Python which will begin in October. When it is posted on Eventbrite, there will be a link to that event here.</h3>This new online Introduction to Python Programming course is intended for interested students, academicians, and/or practitioners who wish to learn how to write programs using the Python programming language. The course targets “beginner” Python programmers who have little or no previous Python programming experience. It is also not necessary to have any prior programming experience in another computer language, although that is helpful. This online course includes six consecutive synchronous weekly summer 2½ hour live sessions, always on Saturdays from 11 AM EDT until 1:30 PM EDT, and beginning on July 8. Registered participants will also be provided, free of charge, <a href="https://www.udemy.com/user/drgeoffreyhubona/" target="_blank" data-msys-clicktrack="0" rel="nofollow noopener noreferrer">permanent asynchronous access to any or all of the two dozen+ research methods/data science online courses of his/her choosing that are listed here</a>. Permanent asynchronous online access to your chosen additional, supplemental research methods/data science courses will begin after the first July 8th session of this course. The course will be taught in an online, interactive “hands-on” format using the most current version of Python (currently 3.11.3) in conjunction with the IDLE interactive shell (sometimes called an Integrated Development Environment (IDE)). Participants will have a full view of my computer screen as I instruct and develop Python code on my computer. You will be able to hear my voice (if you have speakers) and you will be able to ask me questions via voice (if you have a microphone) and/or chat (using text messages). All materials for each weekly class session will be distributed to each course registrant at least 24 hours before that class session. All audio and video desktop class sessions will be recorded in high-quality files that will be made available to all course registrants within a day or two after each class session. The registration fee (USD $175) includes synchronous and interactive online attendance in all six live class sessions, complete audio and video recordings of all live class sessions, all Python code (“script”) that we create and demonstrate in class, all of the example Python programs, and all solutions to the weekly Python exercises. Also, permanent asynchronous access to the 2 dozen+ additional supplemental research methods/data science courses is included. There is nothing else that you need to buy to have your own complete record of the course including all course materials, Python scripts and programs, exercises and solutions. If you ever need to miss a live class session, for whatever reason, you can always “catch up” using the provided recordings and materials and/or use these to “brush up” later.Presented in the agenda is the outline of the six course topics. Each of the six weekly Saturday sessions will cover one topic. Each class session will include numerous sample Python programs and one major exercise for you to practice with before the subsequent weekly class session.

Agenda

1. What is Python?; 2. How to use IDLE to create programs; 3. Coding statements, comments, and functions; 4. Naming and assigning values to variables; 5. Exercise #1.

July 8: Introduction to Python

1. Working with numeric data; 2. Working with string data; 3. Using Python-native functions; 4. Example programs; 5. Exercise #2.

July 15: Writing Your First Programs

1. Boolean expressions; 2. Selection: If statements; 3. Iteration: While and For statements; 4. Example programs; 5. Exercise #3.

July 22: Control Statements

1. Defining a function; 2. The main() function; 3. Arguments: default values and named arguments; 4. Using local and global variables; 5. Importing modules; 6. Example programs; 7. Exercise #4.

July 29: Defining Functions and Using Modules

1. Creating and modifying Lists; 2. Working with Tuples; 3. Example programs; 4. Exercise #5.

Aug 5: Working With List and Tuples

1. Types of errors; 2. Handling exceptions; 3. File Input/Output; 4. How to read and write text, csv, and binary files; 5. Example programs.

Aug 12: Testing and Debugging Programs

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Introduction to Python Programming

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Introduction to Python Programming

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