Table of Contents

1. Course Overview and Python

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
• Functions (including documentation and tests)
• Using the VSCode debugger to trace code
• Why Python?

2. Programming in Python

Topics

• Data types
• Control structures
• Refactoring and constants
• Testing functions that print or take user input
• Import code

3. More Programming in Python

Topics

• Mutation testing: how we grade your tests
• None
• Optional
• Data structures (list, set, and dict)
• Reading and writing text files
• Error handing

4. Review for Quiz 1

Topics

• Functions and documentation
• Unit testing
• Git
• Practice Quiz 1
• Homework help: Git / command line / Pawtograder review

5. Quiz 1

Topics

6. Ethics

Topics

• Learning outcomes
• Why Value-Sensitive Design?
• Steps for Value-Sensitive Design
• Value-Sensitive Design Case study: Finder, a dating app
• Privacy
• Privacy Case study: Gaggle, a messaging app for schools
• Your Case Study: Algorithmic hiring

7. Designing Classes

Topics

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

8. Using Objects

Topics

• State and aliasing
• The __str__() function
• Generics
• Abstraction
• The Single Responsbility Principle

9. Data Structures

Topics

• Lists
• split() and join()
• List indices
• List slices
• Modifying a list
• 2D lists
• List comprehension
• Sets
• Dictionaries
• (if time) map and filter
• The Accumulator Pattern
• functools.reduce() and itertools.accumulate()
• Named and default parameters
• Variable argument lists

10. 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

11. Statistics and Data Visualization

Topics

• Correlation
• Visualization with matplotlib

12. Design Patterns for Handling Data 1

Topics

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

13. Design Patterns for Handling Data 2

Topics

• Combining dataframes
• MapReduce

14. Data Ethics from the News

Topics

15. Review for Quiz 2

Topics

• Classes: constructors, methods, and attributes
• Using Objects
• Stakeholder-value matrices
• Lists, sets, and dictionaries
• Correlation
• Practice Quiz 2

16. Quiz 2

Topics

17. Properties, Visibility, and Immutability

Topics

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

18. Inheritance

Topics

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

19. Interfaces and Abstract Classes

Topics

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

20. Designing Programs with Inheritance

Topics

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

21. Static and Class Methods

Topics

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

22. Design patterns: Observer, "Data Pull", and Hashing

Topics

• Design Patterns
• Data Pull pattern
• Observer pattern
• Hashing

23. Iteration

Topics

• Iterable

24. Recursion

Topics

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

25. Review for Quiz 3

Topics

• Properties
• Inheritance and abstract methods
• Coupling / cohesion / encapsulation
• Practice Quiz 3

26. Quiz 3

Topics

27. Trees and Searching

Topics

• Trees
• Search Algorithms

28. Comparison and Scraping

Topics

• Comparison

29. Graphs and Union-Find

Topics

• Graphs
• Union-Find

30. Minimum Spanning Trees

Topics

• Minimum Spanning Trees
• Kruskals algorithm

31. The Decorator and Strategy Patterns

Topics

• Strategy Pattern
• Function Decorators
• Functions are objects that can be stored in mutable variables
• Creating a function decorator
• A common use of decorators: caching
• Example where caching helps a language model (BERT) run faster

32. The Model-View-Controller Paradigm

Topics

• Separating concerns between the Model, View, and Controller
• Separating extra concerns out of the Model

33. Controllers and Views, and Mocks (how we tested HW that required external resources)

Topics

• Synchronous versus Asynchronous Controllers
• GUI View using tkinkter
• Using a Mock Model to test a Controller

34. Review for Quiz 4

Topics

• Decorator, Strategy, Observer, and Data Pull Design Patterns
• Iterator and Comparable
• Practice Quiz 4

35. Quiz 4

Topics

36. 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

37. Quiz 5

Topics

38. Career Panel

Topics

• Technical interview prep (in the unlikely case of extra time)