Quinnipiac University

INF 605 Introduction to Programming - Python

About the Course

INF 605 Introduction to Programming - Python develops computational thinking while using Python as a tool to answer real-world questions with data. Students will gain experience exploring messy datasets, cleaning and preparing data, writing programs to automate analysis, and crafting compelling visualizations that communicate insights to both technical and non-technical audiences. The class emphasizes iterative design, statistical thinking, and the ethical implications of computing with practical applications in data science and analytics.

Course Schedule

Course Materials

📄 Course Syllabus

Available Lectures

Lecture Topic Materials
-- Course Introduction and Overview Syllabus review, course expectations
1 Introduction to Programming - Python Basics Notebook Google Drive
2 Boolean Logic and Conditional Statements Notebook Google Drive
3 Lists Fundamentals - Creating and Accessing Data Collections Notebook Google Drive
4 While Loops - Repetition with Unknown Iterations Notebook Google Drive
5 For Loops and range() - Structured Iteration Notebook Google Drive
6 Loop Control and Algorithms - break, continue, and Systematic Development Notebook Google Drive
7 List Comprehensions - Elegant Data Processing Notebook Google Drive
8 Functions - Code Organization and Reusability Notebook Google Drive
9 Exception Handling and List Methods - Defensive Programming Notebook Google Drive
10 Data Structures - Tuples, Dictionaries, and Sets Notebook Google Drive
11 Introduction to Object-Oriented Programming - Classes and Objects Notebook Google Drive
12 Advanced OOP - Inheritance and Polymorphism Notebook Google Drive
13 String Operations - Text Processing and Manipulation Notebook Google Drive
14 File Processing - Text, CSV, and JSON Notebook Google Drive
15 Data Formats - JSON, Excel, and Introduction to NumPy Notebook Google Drive
16 NumPy Fundamentals - Arrays and Vectorized Computing Notebook Google Drive
-- Midterm Exam (Take Home) Materials available during exam week
17 NumPy Advanced - Linear Algebra and Random Numbers Notebook Google Drive
18 Advanced NumPy - Filtering, Statistics, and Sorting Notebook Google Drive
19 pandas Series - Labeled Data Structures Notebook Google Drive
20 pandas DataFrames - Two-Dimensional Data Analysis Notebook Google Drive
21 Data Cleaning Fundamentals with pandas Notebook Google Drive
22 Data Transformation - Groupby and Aggregation Notebook Google Drive
23 Data Visualization with Matplotlib Notebook Google Drive
24 Advanced Visualization with Seaborn Notebook Google Drive
25 Course Review and Final Project Guidance Notebook Google Drive
-- Final Project Work Session Project work time
-- Final Project Presentations Presentation schedule TBA

Assignments

Programming Assignments

Assignment Topic Due Date Materials
1 Meta Internship Programming Challenge - Python Fundamentals Sun, Feb 15 Assignment Notebook Google Drive Submit
2 Campus Life Programming Challenge - Advanced Python Concepts Sun, Mar 8 Assignment Notebook Google Drive Submit
3 University IT Internship - Student Records System (OOP, Inheritance, File I/O) Sun, Mar 29 Assignment Notebook Google Drive Submit
4 Sports Analytics Internship - Advanced NumPy Data Analysis Sun, Apr 12 Assignment Notebook Google Drive Submit
5 E-Commerce Customer Analytics with pandas Sun, Apr 26 Assignment Notebook Google Drive Submit
6 Data Visualization with Matplotlib and Seaborn Sun, May 3 Assignment Notebook Google Drive Submit
More assignments coming soon...