Slides

Interesting in learning more about how to use experimental and analytical techniques to study algorithms and data structures? Checkout these slide decks to learn more! Each deck explores a specific topic in connection with chapters in the book A First Course on Data Structures in Python. Finally, make sure to review the course schedule for more details about how these slides connect to various course projects.

Introduction to Algorithm Analysis

How can we use Python packages to characterize the runtime environment used during experiments?

Exploring the Python Programming Language

What are some of the key features of Python and how do we measure their performance?

Object-Oriented Programming in Python

What are the key features of object-oriented programming in Python?

Software Testing

How do you establish a confidence in the correctness of a Python program?

Runtime Analysis through Experimental Evaluation

How do you use experiments to measure the performance of a Python program?

Running Time Analysis through Analytical Evaluation

How do you use proofs to measure the performance of a Python program?

Implementing Stacks, Queues, and Deques

How do you implement efficient stacks and queues in Python?

Implementing Linked-Based Data Structures

How do you design and implement linked-based data structures in Python?

Recursion and Dynamic Programming

How do you efficiently repeat operations?

Searching and Sorting

How do you efficiently process data?

Hash Tables

How do you effectively map data to a backing list?

Hierarchical Data Structures

How do you create and navigate tree structures?

Priority Queues

How do you support priority-oriented data access?

Graph Structures

How do you represent and process graph structured data?