Lessons 1: Python Primer

• Python Overview
• Objects in Python
• Expressions, Operators, and Precedence
• Control Flow
• Functions
• Simple Input and Output
• Exception Handling
• Iterators and Generators
• Additional Python Conveniences
• Scopes and Namespaces
• Modules and the Import Statement
• Exercises

Lessons 2: Object-Oriented Programming

• Goals, Principles and Patterns
• Software Development
• Class Definitions
• Inheritance
• Namespaces and Object-Orientation
• Shallow and Deep Copying
• Exercises

Lessons 3: Algorithm Analysis

• Experimental Studies
• The Seven Functions Used in This Course
• Asymptotic Analysis
• Simple Justification Techniques
• Exercises

Lessons 4: Recursion

• Illustrative Examples
• Analysing Recursive Algorithms
• Recursion Run Amok
• Further Examples of Recursion
• Designing Recursive Algorithms
• Eliminating Tail Recursion
• Exercises

Lessons 5: Array-Based Sequences

• Python's Sequence Types
• Low-Level Arrays
• Dynamic Arrays and Amortisation
• Efficiency of Python's Sequence Types
• Using Array-Based Sequences
• Multidimensional Data Sets
• Exercises

Lessons 6: Stacks, Queues and Deques

• Stacks
• Queues
• Double-Ended Queues
• Exercises

Lessons 7: Linked Lists

• Singly Linked Lists
• Circularly Linked Lists
• Doubly Linked Lists
• The Positional List ADT
• Sorting a Positional List
• Case Study: Maintaining Access Frequencies
• Link-Based vs. Array-Based Sequences
• Exercises

Lessons 8: Trees

• General Trees
• Binary Trees
• Implementing Trees
• Tree Traversal Algorithms
• Case Study: An Expression Tree
• Exercises

Lessons 9: Priority Queues

• The Priority Queue Abstract Data Type
• Implementing a Priority Queue
• Heaps
• Sorting with a Priority Queue
• Adaptable Priority Queues
• Exercises

Lessons 10: Maps, Hash Tables, and Skip Lists

• Maps and Dictionaries
• Hash Tables
• Sorted Maps
• Skip Lists
• Sets, Multisets and Multimaps
• Exercises

Lessons 11: Search Trees

• Binary Search Trees
• Balanced Search Trees
• AVL Trees
• Splay Trees
• (2,4) Trees
• Red-Black Trees
• Exercises

Lessons 12: Sorting and Selection

• Why Study Sorting Algorithms?
• Merge-Sort
• Quick-Sort
• Studying Sorting through an Algorithmic Lens
• Comparing Sorting Algorithms
• Python's Built-In Sorting Functions
• Selection
• Exercises

Lessons 13: Text Processing

• Abundance of Digitised Text
• Pattern-Matching Algorithms
• Dynamic Programming
• Text Compression and the Greedy Method
• Tries
• Exercises

Lessons 14: Graph Algorithms

Lessons 15: Memory Management and B-Trees

• Memory Management
• Memory Hierarchies and Caching
• External Searching and B-Trees
• External-Memory Sorting
• Exercises

Appendix A: Character Strings in Python

Appendix B: Useful Mathematical Facts

Python Primer

• Using the Bitwise Operator
• Using the Equality Operator and the list Class
• Using Arithmetic Operators
• Performing Bitwise Operations
• Using the Comparison Operator
• Using the if-elif-else Statement - Part 1
• Using the if-elif-else Statement - Part 2
• Using the if-else Statement
• Determining the Armstrong Number
• Rectifying Errors
• Finding LCM of Two Numbers
• Creating a Function with its Default Value
• Handling Exception
• Using the dir Function
• Using the math Module

Object-Oriented Programming

• Understanding the init Method
• Understanding Numeric Progressions

Recursion

• Calculating the Product of Two Positive Integers
• Finding the Minimum Element

Array-Based Sequences

• Using the getsizeof Function
• Implementing a Dynamic Array
• Adding Elements to a List
• Using the extend Method
• Removing Elements from a List
• Constructing the Caesar Cipher Algorithm

Stacks, Queues, and Deques

• Using Stack Abstract Data Type Method

Linked Lists

• Implementing a Stack
• Implementing a Queue
• Implementing a Queue with a Circular Linked List
• Implementing a Deque with a Doubly Linked List

Maps, Hash Tables, and Skip Lists

• Adding Elements to a Set
• Performing Set Operations

Sorting and Selection

• Using a Sorting Function
• Using the len() Built-In Function

Text Processing

• Performing Pattern Matching