Table of Contents

1. Course Overview and Git

Topics

• Structure of this course and expectations for students
• Resources
• VSCode, Pawtograder, and GitHub
• The command line
• git
• Practices for code-level design (style guidlines)
• Types in Python code
• Using the VSCode debugger to trace code
• Why Python?

2. Functions, Documentation, Pytest, and Data Types

Topics

• Functions (including documentation and tests)
• Data types
• Mutation testing: how we grade your tests

3. Python Control Structures

Topics

• Control structures
• Refactoring and constants
• Import code

4. Text Files and User Input

Topics

• Data structures (list, set, and dict)
• None
• Optional
• Reading and writing text files
• Testing functions that print or take user input
• Error handing

5. Review for Quiz 1

Topics

• Functions and documentation
• Unit testing
• Git
• Homework help: Git / command line / Pawtograder review

6. Quiz 1

Topics

7. Ethics (Stakeholder-value matrices)

Topics

• Learning outcomes
• Why Value-Sensitive Design?
• Steps for Value-Sensitive Design
• Value-Sensitive Design Case study: Finder, a dating app

8. Ethics (Bias and Privacy)

Topics

• Privacy
• Privacy Case study: Gaggle, a messaging app for schools
• Your Case Study: Algorithmic hiring

9. Designing Classes

Topics

• How to make your own class: attributes, methods, and constructor
• Organizing tests using pytest
• Identifying test cases
• Well-named and organized tests which help the reader understand the purpose of a function
• Using setup_method and teardown_method

10. Using Objects

Topics

• State and aliasing
• The __str__() function
• The __eq__() function
• Abstraction
• (Side note if time) Generics

11. The Single Responsibility Principle, Named and Default Arguments

Topics

• The Single Responsbility Principle
• Named and default parameters
• Variable argument lists

12. Review for Quiz 2

Topics

• Classes: constructors, methods, and attributes
• Aliasing and Equality
• Stakeholder-value matrices

13. Quiz 2

Topics

14. Pythonic Lists

Topics

• Lists
• split() and join()
• List indices
• List slices
• Modifying a list
• 2D lists
• List comprehension

15. Pythonic Sets and Dictionaries

Topics

• Sets
• Dictionaries
• (if time) map and filter
• (if time) The Accumulator Pattern
• (if time) functools.reduce() and itertools.accumulate()

16. Pandas and Numpy

Topics

• Built-In Sequences
• Statistics and vector math with Numpy
• Processing tabular data using Pandas
• Creating and raising our own Errors
• The os module

17. Statistical Variables

Topics

18. Data Visualization

Topics

• Correlation
• Visualization with matplotlib

19. Design Patterns for Handling Data 1

Topics

• Functions are objects
• Sorting with Pandas
• Filtering with Pandas
• Scaling and normalizing data
• Argmax

20. Design Patterns for Handling Data 2

Topics

• Combining dataframes
• MapReduce

21. Review for Quiz 3

Topics

• Mean and Variance
• Lists, sets, and dictionaries

22. Quiz 3

Topics

23. Properties, Visibility, and Immutability

Topics

• Visibility restrictions in Python
• Encapsulation via Properties
• Immutability and Tuples

24. Inheritance

Topics

• Subclasses and superclasses
• Using super()
• Everything is a subclass of object
• UML diagrams
• The Liskov Subsitution Principle

25. Interfaces and Abstract Classes

Topics

• Abstract methods
• Interfaces
• Interfaces with duck typing in Python
• Python contracts

26. Designing Programs with Inheritance

Topics

• Inheritance versus composition
• Polymorphism
• Encapsulation
• Coupling and cohesion

27. Static and Class Methods

Topics

• Operating on a class rather than an instance
• @classmethod versus @staticmethod

28. Comparison and Iterable

Topics

• Iterable
• Comparison

29. Review for Quiz 4

Topics

• Properties
• Inheritance and abstract methods
• Iterator and Comparable

30. Quiz 4

Topics

31. Data Ethics from the News

Topics

32. Recursion

Topics

• Tracing a recursive function
• Implementing a recursive function
• In-class exercise: debate

33. Trees and Searching

Topics

• Trees
• Search Algorithms (if time, preview of CS2700)

34. Coding with AI

Topics

• Brief intro to generative AI
• Where do programmers code with AI?
• Common concerns
• Each task in the PDI process can use AI in some way:
• Research shows this is the standard workflow with AI that software developers are trending towards:
• Why we discourage vibe coding in the PDI sequence:
• Common uses for the web interface
• Common uses for Cursor / Windsurf / Github Copilot IDE plugin
• Common uses for Claude Code in the terminal

35. Review

Topics

36. Quiz 5

Topics

37. Career Panel

Topics